- abs(Column) - Static method in class org.apache.spark.sql.functions
-
Computes the absolute value.
- abs() - Method in class org.apache.spark.sql.types.Decimal
-
- absent() - Static method in class org.apache.spark.api.java.Optional
-
- AbsoluteError - Class in org.apache.spark.mllib.tree.loss
-
:: DeveloperApi ::
Class for absolute error loss calculation (for regression).
- AbsoluteError() - Constructor for class org.apache.spark.mllib.tree.loss.AbsoluteError
-
- accept(Parsers) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- accept(ES, Function1<ES, List<Object>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- accept(String, PartialFunction<Object, U>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- acceptIf(Function1<Object, Object>, Function1<Object, String>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- acceptMatch(String, PartialFunction<Object, U>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- acceptSeq(ES, Function1<ES, Iterable<Object>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- accId() - Method in class org.apache.spark.CleanAccum
-
- Accumulable<R,T> - Class in org.apache.spark
-
Deprecated.
use AccumulatorV2. Since 2.0.0.
- Accumulable(R, AccumulableParam<R, T>) - Constructor for class org.apache.spark.Accumulable
-
Deprecated.
- accumulable(T, AccumulableParam<T, R>) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Deprecated.
use AccumulatorV2. Since 2.0.0.
- accumulable(T, String, AccumulableParam<T, R>) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Deprecated.
use AccumulatorV2. Since 2.0.0.
- accumulable(R, AccumulableParam<R, T>) - Method in class org.apache.spark.SparkContext
-
Deprecated.
use AccumulatorV2. Since 2.0.0.
- accumulable(R, String, AccumulableParam<R, T>) - Method in class org.apache.spark.SparkContext
-
Deprecated.
use AccumulatorV2. Since 2.0.0.
- accumulableCollection(R, Function1<R, Growable<T>>, ClassTag<R>) - Method in class org.apache.spark.SparkContext
-
Deprecated.
use AccumulatorV2. Since 2.0.0.
- AccumulableInfo - Class in org.apache.spark.scheduler
-
:: DeveloperApi ::
Information about an
Accumulable modified during a task or stage.
- AccumulableInfo - Class in org.apache.spark.status.api.v1
-
- accumulableInfoFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
- accumulableInfoToJson(AccumulableInfo) - Static method in class org.apache.spark.util.JsonProtocol
-
- AccumulableParam<R,T> - Interface in org.apache.spark
-
Deprecated.
use AccumulatorV2. Since 2.0.0.
- accumulables() - Method in class org.apache.spark.scheduler.StageInfo
-
Terminal values of accumulables updated during this stage, including all the user-defined
accumulators.
- accumulables() - Method in class org.apache.spark.scheduler.TaskInfo
-
Intermediate updates to accumulables during this task.
- accumulables() - Method in class org.apache.spark.ui.jobs.UIData.StageUIData
-
- Accumulator<T> - Class in org.apache.spark
-
Deprecated.
use AccumulatorV2. Since 2.0.0.
- accumulator(int) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Deprecated.
use sc().longAccumulator(). Since 2.0.0.
- accumulator(int, String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Deprecated.
use sc().longAccumulator(String). Since 2.0.0.
- accumulator(double) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Deprecated.
use sc().doubleAccumulator(). Since 2.0.0.
- accumulator(double, String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Deprecated.
use sc().doubleAccumulator(String). Since 2.0.0.
- accumulator(T, AccumulatorParam<T>) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Deprecated.
use AccumulatorV2. Since 2.0.0.
- accumulator(T, String, AccumulatorParam<T>) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Deprecated.
use AccumulatorV2. Since 2.0.0.
- accumulator(T, AccumulatorParam<T>) - Method in class org.apache.spark.SparkContext
-
Deprecated.
use AccumulatorV2. Since 2.0.0.
- accumulator(T, String, AccumulatorParam<T>) - Method in class org.apache.spark.SparkContext
-
Deprecated.
use AccumulatorV2. Since 2.0.0.
- AccumulatorContext - Class in org.apache.spark.util
-
An internal class used to track accumulators by Spark itself.
- AccumulatorContext() - Constructor for class org.apache.spark.util.AccumulatorContext
-
- AccumulatorParam<T> - Interface in org.apache.spark
-
Deprecated.
use AccumulatorV2. Since 2.0.0.
- AccumulatorParam.DoubleAccumulatorParam$ - Class in org.apache.spark
-
Deprecated.
use AccumulatorV2. Since 2.0.0.
- AccumulatorParam.DoubleAccumulatorParam$() - Constructor for class org.apache.spark.AccumulatorParam.DoubleAccumulatorParam$
-
Deprecated.
- AccumulatorParam.FloatAccumulatorParam$ - Class in org.apache.spark
-
Deprecated.
use AccumulatorV2. Since 2.0.0.
- AccumulatorParam.FloatAccumulatorParam$() - Constructor for class org.apache.spark.AccumulatorParam.FloatAccumulatorParam$
-
Deprecated.
- AccumulatorParam.IntAccumulatorParam$ - Class in org.apache.spark
-
Deprecated.
use AccumulatorV2. Since 2.0.0.
- AccumulatorParam.IntAccumulatorParam$() - Constructor for class org.apache.spark.AccumulatorParam.IntAccumulatorParam$
-
Deprecated.
- AccumulatorParam.LongAccumulatorParam$ - Class in org.apache.spark
-
Deprecated.
use AccumulatorV2. Since 2.0.0.
- AccumulatorParam.LongAccumulatorParam$() - Constructor for class org.apache.spark.AccumulatorParam.LongAccumulatorParam$
-
Deprecated.
- AccumulatorParam.StringAccumulatorParam$ - Class in org.apache.spark
-
Deprecated.
use AccumulatorV2. Since 2.0.0.
- AccumulatorParam.StringAccumulatorParam$() - Constructor for class org.apache.spark.AccumulatorParam.StringAccumulatorParam$
-
Deprecated.
- accumulatorUpdates() - Method in class org.apache.spark.status.api.v1.StageData
-
- accumulatorUpdates() - Method in class org.apache.spark.status.api.v1.TaskData
-
- AccumulatorV2<IN,OUT> - Class in org.apache.spark.util
-
The base class for accumulators, that can accumulate inputs of type IN, and produce output of
type OUT.
- AccumulatorV2() - Constructor for class org.apache.spark.util.AccumulatorV2
-
- accumUpdates() - Method in class org.apache.spark.ExceptionFailure
-
- accumUpdates() - Method in class org.apache.spark.scheduler.SparkListenerExecutorMetricsUpdate
-
- accuracy() - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
-
Returns accuracy
(equals to the total number of correctly classified instances
out of the total number of instances.)
- accuracy() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
-
Returns accuracy
- acos(Column) - Static method in class org.apache.spark.sql.functions
-
Computes the cosine inverse of the given value; the returned angle is in the range
0.0 through pi.
- acos(String) - Static method in class org.apache.spark.sql.functions
-
Computes the cosine inverse of the given column; the returned angle is in the range
0.0 through pi.
- active() - Method in class org.apache.spark.sql.streaming.StreamingQueryManager
-
Returns a list of active queries associated with this SQLContext
- active() - Method in class org.apache.spark.streaming.scheduler.ReceiverInfo
-
- ACTIVE() - Static method in class org.apache.spark.streaming.scheduler.ReceiverState
-
- activeJobs() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- activeStages() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- activeStorageStatusList() - Method in class org.apache.spark.ui.exec.ExecutorsListener
-
- activeStorageStatusList() - Method in class org.apache.spark.ui.storage.StorageListener
-
- activeTasks() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
-
- add(T) - Method in class org.apache.spark.Accumulable
-
Deprecated.
Add more data to this accumulator / accumulable
- add(T) - Static method in class org.apache.spark.Accumulator
-
Deprecated.
- add(org.apache.spark.ml.feature.Instance, Vector, double[]) - Method in class org.apache.spark.ml.classification.LogisticAggregator
-
Add a new training instance to this LogisticAggregator, and update the loss and gradient
of the objective function.
- add(AFTPoint) - Method in class org.apache.spark.ml.regression.AFTAggregator
-
Add a new training data to this AFTAggregator, and update the loss and gradient
of the objective function.
- add(org.apache.spark.ml.feature.Instance) - Method in class org.apache.spark.ml.regression.LeastSquaresAggregator
-
Add a new training instance to this LeastSquaresAggregator, and update the loss and gradient
of the objective function.
- add(double[], MultivariateGaussian[], ExpectationSum, Vector<Object>) - Static method in class org.apache.spark.mllib.clustering.ExpectationSum
-
- add(Vector) - Method in class org.apache.spark.mllib.feature.IDF.DocumentFrequencyAggregator
-
Adds a new document.
- add(BlockMatrix) - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
-
Adds the given block matrix other to this block matrix: this + other.
- add(Vector) - Method in class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
-
Add a new sample to this summarizer, and update the statistical summary.
- add(StructField) - Method in class org.apache.spark.sql.types.StructType
-
- add(String, DataType) - Method in class org.apache.spark.sql.types.StructType
-
Creates a new
StructType by adding a new nullable field with no metadata.
- add(String, DataType, boolean) - Method in class org.apache.spark.sql.types.StructType
-
Creates a new
StructType by adding a new field with no metadata.
- add(String, DataType, boolean, Metadata) - Method in class org.apache.spark.sql.types.StructType
-
Creates a new
StructType by adding a new field and specifying metadata.
- add(String, String) - Method in class org.apache.spark.sql.types.StructType
-
Creates a new
StructType by adding a new nullable field with no metadata where the
dataType is specified as a String.
- add(String, String, boolean) - Method in class org.apache.spark.sql.types.StructType
-
Creates a new
StructType by adding a new field with no metadata where the
dataType is specified as a String.
- add(String, String, boolean, Metadata) - Method in class org.apache.spark.sql.types.StructType
-
Creates a new
StructType by adding a new field and specifying metadata where the
dataType is specified as a String.
- add(long, long) - Static method in class org.apache.spark.streaming.util.RawTextHelper
-
- add(IN) - Method in class org.apache.spark.util.AccumulatorV2
-
Takes the inputs and accumulates.
- add(T) - Method in class org.apache.spark.util.CollectionAccumulator
-
- add(Double) - Method in class org.apache.spark.util.DoubleAccumulator
-
Adds v to the accumulator, i.e.
- add(double) - Method in class org.apache.spark.util.DoubleAccumulator
-
Adds v to the accumulator, i.e.
- add(T) - Method in class org.apache.spark.util.LegacyAccumulatorWrapper
-
- add(Long) - Method in class org.apache.spark.util.LongAccumulator
-
Adds v to the accumulator, i.e.
- add(long) - Method in class org.apache.spark.util.LongAccumulator
-
Adds v to the accumulator, i.e.
- add(Object) - Method in class org.apache.spark.util.sketch.CountMinSketch
-
Increments item's count by one.
- add(Object, long) - Method in class org.apache.spark.util.sketch.CountMinSketch
-
Increments item's count by count.
- add_months(Column, int) - Static method in class org.apache.spark.sql.functions
-
Returns the date that is numMonths after startDate.
- addAccumulator(R, T) - Method in interface org.apache.spark.AccumulableParam
-
Deprecated.
Add additional data to the accumulator value.
- addAccumulator(T, T) - Method in interface org.apache.spark.AccumulatorParam
-
Deprecated.
- addAppArgs(String...) - Method in class org.apache.spark.launcher.SparkLauncher
-
Adds command line arguments for the application.
- addBinary(byte[]) - Method in class org.apache.spark.util.sketch.CountMinSketch
-
Increments item's count by one.
- addBinary(byte[], long) - Method in class org.apache.spark.util.sketch.CountMinSketch
-
Increments item's count by count.
- addDockerInfo(Protos.ContainerInfo.Builder, String, Option<List<Protos.Volume>>, Option<Protos.ContainerInfo.DockerInfo.Network>, Option<List<Protos.ContainerInfo.DockerInfo.PortMapping>>) - Static method in class org.apache.spark.scheduler.cluster.mesos.MesosSchedulerBackendUtil
-
Construct a DockerInfo structure and insert it into a ContainerInfo
- addFile(String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Add a file to be downloaded with this Spark job on every node.
- addFile(String) - Method in class org.apache.spark.launcher.SparkLauncher
-
Adds a file to be submitted with the application.
- addFile(String) - Method in class org.apache.spark.SparkContext
-
Add a file to be downloaded with this Spark job on every node.
- addFile(String, boolean) - Method in class org.apache.spark.SparkContext
-
Add a file to be downloaded with this Spark job on every node.
- addFilters(Seq<ServletContextHandler>, SparkConf) - Static method in class org.apache.spark.ui.JettyUtils
-
Add filters, if any, to the given list of ServletContextHandlers
- addGrid(Param<T>, Iterable<T>) - Method in class org.apache.spark.ml.tuning.ParamGridBuilder
-
Adds a param with multiple values (overwrites if the input param exists).
- addGrid(DoubleParam, double[]) - Method in class org.apache.spark.ml.tuning.ParamGridBuilder
-
Adds a double param with multiple values.
- addGrid(IntParam, int[]) - Method in class org.apache.spark.ml.tuning.ParamGridBuilder
-
Adds an int param with multiple values.
- addGrid(FloatParam, float[]) - Method in class org.apache.spark.ml.tuning.ParamGridBuilder
-
Adds a float param with multiple values.
- addGrid(LongParam, long[]) - Method in class org.apache.spark.ml.tuning.ParamGridBuilder
-
Adds a long param with multiple values.
- addGrid(BooleanParam) - Method in class org.apache.spark.ml.tuning.ParamGridBuilder
-
Adds a boolean param with true and false.
- addInPlace(R, R) - Method in interface org.apache.spark.AccumulableParam
-
Deprecated.
Merge two accumulated values together.
- addInPlace(double, double) - Method in class org.apache.spark.AccumulatorParam.DoubleAccumulatorParam$
-
Deprecated.
- addInPlace(float, float) - Method in class org.apache.spark.AccumulatorParam.FloatAccumulatorParam$
-
Deprecated.
- addInPlace(int, int) - Method in class org.apache.spark.AccumulatorParam.IntAccumulatorParam$
-
Deprecated.
- addInPlace(long, long) - Method in class org.apache.spark.AccumulatorParam.LongAccumulatorParam$
-
Deprecated.
- addInPlace(String, String) - Method in class org.apache.spark.AccumulatorParam.StringAccumulatorParam$
-
Deprecated.
- addJar(String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Adds a JAR dependency for all tasks to be executed on this SparkContext in the future.
- addJar(String) - Method in class org.apache.spark.launcher.SparkLauncher
-
Adds a jar file to be submitted with the application.
- addJar(String) - Method in class org.apache.spark.SparkContext
-
Adds a JAR dependency for all tasks to be executed on this SparkContext in the future.
- addListener(SparkAppHandle.Listener) - Method in interface org.apache.spark.launcher.SparkAppHandle
-
Adds a listener to be notified of changes to the handle's information.
- addListener(StreamingQueryListener) - Method in class org.apache.spark.sql.streaming.StreamingQueryManager
-
- addLocalConfiguration(String, int, int, int, JobConf) - Static method in class org.apache.spark.rdd.HadoopRDD
-
Add Hadoop configuration specific to a single partition and attempt.
- addLong(long) - Method in class org.apache.spark.util.sketch.CountMinSketch
-
Increments item's count by one.
- addLong(long, long) - Method in class org.apache.spark.util.sketch.CountMinSketch
-
Increments item's count by count.
- addPartToPGroup(Partition, PartitionGroup) - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
-
- addPyFile(String) - Method in class org.apache.spark.launcher.SparkLauncher
-
Adds a python file / zip / egg to be submitted with the application.
- address() - Method in class org.apache.spark.status.api.v1.RDDDataDistribution
-
- addShutdownHook(Function0<BoxedUnit>) - Static method in class org.apache.spark.util.ShutdownHookManager
-
Adds a shutdown hook with default priority.
- addShutdownHook(int, Function0<BoxedUnit>) - Static method in class org.apache.spark.util.ShutdownHookManager
-
Adds a shutdown hook with the given priority.
- addSparkArg(String) - Method in class org.apache.spark.launcher.SparkLauncher
-
Adds a no-value argument to the Spark invocation.
- addSparkArg(String, String) - Method in class org.apache.spark.launcher.SparkLauncher
-
Adds an argument with a value to the Spark invocation.
- addSparkListener(org.apache.spark.scheduler.SparkListenerInterface) - Method in class org.apache.spark.SparkContext
-
:: DeveloperApi ::
Register a listener to receive up-calls from events that happen during execution.
- addStreamingListener(StreamingListener) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
- addStreamingListener(StreamingListener) - Method in class org.apache.spark.streaming.StreamingContext
-
- addString(StringBuilder, String, String, String) - Static method in class org.apache.spark.sql.types.StructType
-
- addString(StringBuilder, String) - Static method in class org.apache.spark.sql.types.StructType
-
- addString(StringBuilder) - Static method in class org.apache.spark.sql.types.StructType
-
- addString(String) - Method in class org.apache.spark.util.sketch.CountMinSketch
-
Increments item's count by one.
- addString(String, long) - Method in class org.apache.spark.util.sketch.CountMinSketch
-
Increments item's count by count.
- addSuppressed(Throwable) - Static method in exception org.apache.spark.sql.AnalysisException
-
- addSuppressed(Throwable) - Static method in exception org.apache.spark.sql.streaming.StreamingQueryException
-
- addTaskCompletionListener(TaskCompletionListener) - Method in class org.apache.spark.TaskContext
-
Adds a (Java friendly) listener to be executed on task completion.
- addTaskCompletionListener(Function1<TaskContext, BoxedUnit>) - Method in class org.apache.spark.TaskContext
-
Adds a listener in the form of a Scala closure to be executed on task completion.
- addTaskFailureListener(TaskFailureListener) - Method in class org.apache.spark.TaskContext
-
Adds a listener to be executed on task failure.
- addTaskFailureListener(Function2<TaskContext, Throwable, BoxedUnit>) - Method in class org.apache.spark.TaskContext
-
Adds a listener to be executed on task failure.
- AFTAggregator - Class in org.apache.spark.ml.regression
-
AFTAggregator computes the gradient and loss for a AFT loss function,
as used in AFT survival regression for samples in sparse or dense vector in an online fashion.
- AFTAggregator(DenseVector<Object>, boolean, double[]) - Constructor for class org.apache.spark.ml.regression.AFTAggregator
-
- AFTCostFun - Class in org.apache.spark.ml.regression
-
AFTCostFun implements Breeze's DiffFunction[T] for AFT cost.
- AFTCostFun(RDD<AFTPoint>, boolean, double[]) - Constructor for class org.apache.spark.ml.regression.AFTCostFun
-
- AFTSurvivalRegression - Class in org.apache.spark.ml.regression
-
:: Experimental ::
Fit a parametric survival regression model named accelerated failure time (AFT) model
(https://en.wikipedia.org/wiki/Accelerated_failure_time_model)
based on the Weibull distribution of the survival time.
- AFTSurvivalRegression(String) - Constructor for class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- AFTSurvivalRegression() - Constructor for class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- AFTSurvivalRegressionModel - Class in org.apache.spark.ml.regression
-
- agg(Column, Column...) - Method in class org.apache.spark.sql.Dataset
-
Aggregates on the entire Dataset without groups.
- agg(Tuple2<String, String>, Seq<Tuple2<String, String>>) - Method in class org.apache.spark.sql.Dataset
-
(Scala-specific) Aggregates on the entire Dataset without groups.
- agg(Map<String, String>) - Method in class org.apache.spark.sql.Dataset
-
(Scala-specific) Aggregates on the entire Dataset without groups.
- agg(Map<String, String>) - Method in class org.apache.spark.sql.Dataset
-
(Java-specific) Aggregates on the entire Dataset without groups.
- agg(Column, Seq<Column>) - Method in class org.apache.spark.sql.Dataset
-
Aggregates on the entire Dataset without groups.
- agg(TypedColumn<V, U1>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
-
Computes the given aggregation, returning a
Dataset of tuples for each unique key
and the result of computing this aggregation over all elements in the group.
- agg(TypedColumn<V, U1>, TypedColumn<V, U2>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
-
Computes the given aggregations, returning a
Dataset of tuples for each unique key
and the result of computing these aggregations over all elements in the group.
- agg(TypedColumn<V, U1>, TypedColumn<V, U2>, TypedColumn<V, U3>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
-
Computes the given aggregations, returning a
Dataset of tuples for each unique key
and the result of computing these aggregations over all elements in the group.
- agg(TypedColumn<V, U1>, TypedColumn<V, U2>, TypedColumn<V, U3>, TypedColumn<V, U4>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
-
Computes the given aggregations, returning a
Dataset of tuples for each unique key
and the result of computing these aggregations over all elements in the group.
- agg(Column, Column...) - Method in class org.apache.spark.sql.RelationalGroupedDataset
-
Compute aggregates by specifying a series of aggregate columns.
- agg(Tuple2<String, String>, Seq<Tuple2<String, String>>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
-
(Scala-specific) Compute aggregates by specifying the column names and
aggregate methods.
- agg(Map<String, String>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
-
(Scala-specific) Compute aggregates by specifying a map from column name to
aggregate methods.
- agg(Map<String, String>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
-
(Java-specific) Compute aggregates by specifying a map from column name to
aggregate methods.
- agg(Column, Seq<Column>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
-
Compute aggregates by specifying a series of aggregate columns.
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Aggregate the elements of each partition, and then the results for all the partitions, using
given combine functions and a neutral "zero value".
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>, ClassTag<U>) - Static method in class org.apache.spark.api.r.RRDD
-
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>, ClassTag<U>) - Method in class org.apache.spark.rdd.RDD
-
Aggregate the elements of each partition, and then the results for all the partitions, using
given combine functions and a neutral "zero value".
- aggregate(U, Function2<U, T, U>, Function2<U, U, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- aggregate(Function0<B>, Function2<B, A, B>, Function2<B, B, B>) - Static method in class org.apache.spark.sql.types.StructType
-
- aggregateByKey(U, Partitioner, Function2<U, V, U>, Function2<U, U, U>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Aggregate the values of each key, using given combine functions and a neutral "zero value".
- aggregateByKey(U, int, Function2<U, V, U>, Function2<U, U, U>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Aggregate the values of each key, using given combine functions and a neutral "zero value".
- aggregateByKey(U, Function2<U, V, U>, Function2<U, U, U>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Aggregate the values of each key, using given combine functions and a neutral "zero value".
- aggregateByKey(U, Partitioner, Function2<U, V, U>, Function2<U, U, U>, ClassTag<U>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Aggregate the values of each key, using given combine functions and a neutral "zero value".
- aggregateByKey(U, int, Function2<U, V, U>, Function2<U, U, U>, ClassTag<U>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Aggregate the values of each key, using given combine functions and a neutral "zero value".
- aggregateByKey(U, Function2<U, V, U>, Function2<U, U, U>, ClassTag<U>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Aggregate the values of each key, using given combine functions and a neutral "zero value".
- AggregatedDialect - Class in org.apache.spark.sql.jdbc
-
AggregatedDialect can unify multiple dialects into one virtual Dialect.
- AggregatedDialect(List<JdbcDialect>) - Constructor for class org.apache.spark.sql.jdbc.AggregatedDialect
-
- aggregateMessages(Function1<EdgeContext<VD, ED, A>, BoxedUnit>, Function2<A, A, A>, TripletFields, ClassTag<A>) - Method in class org.apache.spark.graphx.Graph
-
Aggregates values from the neighboring edges and vertices of each vertex.
- aggregateMessages(Function1<EdgeContext<VD, ED, A>, BoxedUnit>, Function2<A, A, A>, TripletFields, ClassTag<A>) - Static method in class org.apache.spark.graphx.impl.GraphImpl
-
- aggregateMessages$default$3() - Static method in class org.apache.spark.graphx.impl.GraphImpl
-
- aggregateMessagesWithActiveSet(Function1<EdgeContext<VD, ED, A>, BoxedUnit>, Function2<A, A, A>, TripletFields, Option<Tuple2<VertexRDD<?>, EdgeDirection>>, ClassTag<A>) - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- aggregateUsingIndex(RDD<Tuple2<Object, VD2>>, Function2<VD2, VD2, VD2>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- aggregateUsingIndex(RDD<Tuple2<Object, VD2>>, Function2<VD2, VD2, VD2>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.VertexRDD
-
Aggregates vertices in messages that have the same ids using reduceFunc, returning a
VertexRDD co-indexed with this.
- AggregatingEdgeContext<VD,ED,A> - Class in org.apache.spark.graphx.impl
-
- AggregatingEdgeContext(Function2<A, A, A>, Object, BitSet) - Constructor for class org.apache.spark.graphx.impl.AggregatingEdgeContext
-
- Aggregator<K,V,C> - Class in org.apache.spark
-
:: DeveloperApi ::
A set of functions used to aggregate data.
- Aggregator(Function1<V, C>, Function2<C, V, C>, Function2<C, C, C>) - Constructor for class org.apache.spark.Aggregator
-
- aggregator() - Method in class org.apache.spark.ShuffleDependency
-
- Aggregator<IN,BUF,OUT> - Class in org.apache.spark.sql.expressions
-
:: Experimental ::
A base class for user-defined aggregations, which can be used in Dataset operations to take
all of the elements of a group and reduce them to a single value.
- Aggregator() - Constructor for class org.apache.spark.sql.expressions.Aggregator
-
- aic(RDD<Tuple3<Object, Object, Object>>, double, double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Binomial$
-
- aic(RDD<Tuple3<Object, Object, Object>>, double, double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gamma$
-
- aic(RDD<Tuple3<Object, Object, Object>>, double, double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gaussian$
-
- aic(RDD<Tuple3<Object, Object, Object>>, double, double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Poisson$
-
- aic() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
-
Akaike Information Criterion (AIC) for the fitted model.
- Algo - Class in org.apache.spark.mllib.tree.configuration
-
Enum to select the algorithm for the decision tree
- Algo() - Constructor for class org.apache.spark.mllib.tree.configuration.Algo
-
- algo() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- algo() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
-
- algo() - Method in class org.apache.spark.mllib.tree.model.GradientBoostedTreesModel
-
- algo() - Method in class org.apache.spark.mllib.tree.model.RandomForestModel
-
- algorithm() - Method in class org.apache.spark.mllib.regression.StreamingLinearRegressionWithSGD
-
- alias(String) - Method in class org.apache.spark.sql.Column
-
Gives the column an alias.
- alias(String) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset with an alias set.
- alias(Symbol) - Method in class org.apache.spark.sql.Dataset
-
(Scala-specific) Returns a new Dataset with an alias set.
- All - Static variable in class org.apache.spark.graphx.TripletFields
-
Expose all the fields (source, edge, and destination).
- allAttributes() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- allAttributes() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- allAttributes() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- AllJobsCancelled - Class in org.apache.spark.scheduler
-
- AllJobsCancelled() - Constructor for class org.apache.spark.scheduler.AllJobsCancelled
-
- AllReceiverIds - Class in org.apache.spark.streaming.scheduler
-
A message used by ReceiverTracker to ask all receiver's ids still stored in
ReceiverTrackerEndpoint.
- AllReceiverIds() - Constructor for class org.apache.spark.streaming.scheduler.AllReceiverIds
-
- allSources() - Static method in class org.apache.spark.metrics.source.StaticSources
-
The set of all static sources.
- alpha() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- alpha() - Method in class org.apache.spark.mllib.random.WeibullGenerator
-
- ALS - Class in org.apache.spark.ml.recommendation
-
Alternating Least Squares (ALS) matrix factorization.
- ALS(String) - Constructor for class org.apache.spark.ml.recommendation.ALS
-
- ALS() - Constructor for class org.apache.spark.ml.recommendation.ALS
-
- ALS - Class in org.apache.spark.mllib.recommendation
-
Alternating Least Squares matrix factorization.
- ALS() - Constructor for class org.apache.spark.mllib.recommendation.ALS
-
Constructs an ALS instance with default parameters: {numBlocks: -1, rank: 10, iterations: 10,
lambda: 0.01, implicitPrefs: false, alpha: 1.0}.
- ALS.InBlock$ - Class in org.apache.spark.ml.recommendation
-
- ALS.InBlock$() - Constructor for class org.apache.spark.ml.recommendation.ALS.InBlock$
-
- ALS.Rating<ID> - Class in org.apache.spark.ml.recommendation
-
:: DeveloperApi ::
Rating class for better code readability.
- ALS.Rating(ID, ID, float) - Constructor for class org.apache.spark.ml.recommendation.ALS.Rating
-
- ALS.Rating$ - Class in org.apache.spark.ml.recommendation
-
- ALS.Rating$() - Constructor for class org.apache.spark.ml.recommendation.ALS.Rating$
-
- ALS.RatingBlock$ - Class in org.apache.spark.ml.recommendation
-
- ALS.RatingBlock$() - Constructor for class org.apache.spark.ml.recommendation.ALS.RatingBlock$
-
- ALSModel - Class in org.apache.spark.ml.recommendation
-
Model fitted by ALS.
- am() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterClusterManager
-
- AnalysisException - Exception in org.apache.spark.sql
-
:: DeveloperApi ::
Thrown when a query fails to analyze, usually because the query itself is invalid.
- analyzed() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- and(Column) - Method in class org.apache.spark.sql.Column
-
Boolean AND.
- And - Class in org.apache.spark.sql.sources
-
A filter that evaluates to true iff both left or right evaluate to true.
- And(Filter, Filter) - Constructor for class org.apache.spark.sql.sources.And
-
- andThen(Function1<B, C>) - Static method in class org.apache.spark.sql.types.StructType
-
- antecedent() - Method in class org.apache.spark.mllib.fpm.AssociationRules.Rule
-
- ANY() - Static method in class org.apache.spark.scheduler.TaskLocality
-
- AnyDataType - Class in org.apache.spark.sql.types
-
An AbstractDataType that matches any concrete data types.
- AnyDataType() - Constructor for class org.apache.spark.sql.types.AnyDataType
-
- anyNull() - Method in interface org.apache.spark.sql.Row
-
Returns true if there are any NULL values in this row.
- appAttemptId() - Method in class org.apache.spark.scheduler.SparkListenerApplicationStart
-
- Append() - Static method in class org.apache.spark.sql.streaming.OutputMode
-
OutputMode in which only the new rows in the streaming DataFrame/Dataset will be
written to the sink.
- appendBias(Vector) - Static method in class org.apache.spark.mllib.util.MLUtils
-
Returns a new vector with 1.0 (bias) appended to the input vector.
- appendColumn(StructType, String, DataType, boolean) - Static method in class org.apache.spark.ml.util.SchemaUtils
-
Appends a new column to the input schema.
- appendColumn(StructType, StructField) - Static method in class org.apache.spark.ml.util.SchemaUtils
-
Appends a new column to the input schema.
- appendReadColumns(Configuration, Seq<Integer>, Seq<String>) - Static method in class org.apache.spark.sql.hive.HiveShim
-
- appHistoryInfoToPublicAppInfo(ApplicationHistoryInfo) - Static method in class org.apache.spark.status.api.v1.ApplicationsListResource
-
- appId() - Method in class org.apache.spark.scheduler.SparkListenerApplicationStart
-
- APPLICATION_EXECUTOR_LIMIT() - Static method in class org.apache.spark.ui.ToolTips
-
- applicationAttemptId() - Method in class org.apache.spark.SparkContext
-
- ApplicationAttemptInfo - Class in org.apache.spark.status.api.v1
-
- applicationEndFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
- applicationEndToJson(SparkListenerApplicationEnd) - Static method in class org.apache.spark.util.JsonProtocol
-
- applicationId() - Method in class org.apache.spark.SparkContext
-
A unique identifier for the Spark application.
- ApplicationInfo - Class in org.apache.spark.status.api.v1
-
- ApplicationsListResource - Class in org.apache.spark.status.api.v1
-
- ApplicationsListResource() - Constructor for class org.apache.spark.status.api.v1.ApplicationsListResource
-
- applicationStartFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
- applicationStartToJson(SparkListenerApplicationStart) - Static method in class org.apache.spark.util.JsonProtocol
-
- ApplicationStatus - Enum in org.apache.spark.status.api.v1
-
- apply(RDD<Tuple2<Object, VD>>, RDD<Edge<ED>>, VD, StorageLevel, StorageLevel, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.Graph
-
Construct a graph from a collection of vertices and
edges with attributes.
- apply(RDD<Edge<ED>>, VD, StorageLevel, StorageLevel, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.impl.GraphImpl
-
Create a graph from edges, setting referenced vertices to `defaultVertexAttr`.
- apply(RDD<Tuple2<Object, VD>>, RDD<Edge<ED>>, VD, StorageLevel, StorageLevel, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.impl.GraphImpl
-
Create a graph from vertices and edges, setting missing vertices to `defaultVertexAttr`.
- apply(VertexRDD<VD>, EdgeRDD<ED>, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.impl.GraphImpl
-
Create a graph from a VertexRDD and an EdgeRDD with arbitrary replicated vertices.
- apply(Graph<VD, ED>, A, int, EdgeDirection, Function3<Object, VD, A, VD>, Function1<EdgeTriplet<VD, ED>, Iterator<Tuple2<Object, A>>>, Function2<A, A, A>, ClassTag<VD>, ClassTag<ED>, ClassTag<A>) - Static method in class org.apache.spark.graphx.Pregel
-
Execute a Pregel-like iterative vertex-parallel abstraction.
- apply(RDD<Tuple2<Object, VD>>, ClassTag<VD>) - Static method in class org.apache.spark.graphx.VertexRDD
-
Constructs a standalone
VertexRDD (one that is not set up for efficient joins with an
EdgeRDD) from an RDD of vertex-attribute pairs.
- apply(RDD<Tuple2<Object, VD>>, EdgeRDD<?>, VD, ClassTag<VD>) - Static method in class org.apache.spark.graphx.VertexRDD
-
Constructs a VertexRDD from an RDD of vertex-attribute pairs.
- apply(RDD<Tuple2<Object, VD>>, EdgeRDD<?>, VD, Function2<VD, VD, VD>, ClassTag<VD>) - Static method in class org.apache.spark.graphx.VertexRDD
-
Constructs a VertexRDD from an RDD of vertex-attribute pairs.
- apply(DenseMatrix<Object>, DenseMatrix<Object>, Function1<Object, Object>) - Static method in class org.apache.spark.ml.ann.ApplyInPlace
-
- apply(DenseMatrix<Object>, DenseMatrix<Object>, DenseMatrix<Object>, Function2<Object, Object, Object>) - Static method in class org.apache.spark.ml.ann.ApplyInPlace
-
- apply(String) - Method in class org.apache.spark.ml.attribute.AttributeGroup
-
Gets an attribute by its name.
- apply(int) - Method in class org.apache.spark.ml.attribute.AttributeGroup
-
Gets an attribute by its index.
- apply(int, int) - Method in class org.apache.spark.ml.linalg.DenseMatrix
-
- apply(int) - Method in class org.apache.spark.ml.linalg.DenseVector
-
- apply(int, int) - Method in interface org.apache.spark.ml.linalg.Matrix
-
Gets the (i, j)-th element.
- apply(int, int) - Method in class org.apache.spark.ml.linalg.SparseMatrix
-
- apply(int) - Static method in class org.apache.spark.ml.linalg.SparseVector
-
- apply(int) - Method in interface org.apache.spark.ml.linalg.Vector
-
Gets the value of the ith element.
- apply(Param<T>) - Method in class org.apache.spark.ml.param.ParamMap
-
Gets the value of the input param or its default value if it does not exist.
- apply(Split) - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.SplitData$
-
- apply(BinaryConfusionMatrix) - Static method in class org.apache.spark.mllib.evaluation.binary.FalsePositiveRate
-
- apply(BinaryConfusionMatrix) - Static method in class org.apache.spark.mllib.evaluation.binary.Precision
-
- apply(BinaryConfusionMatrix) - Static method in class org.apache.spark.mllib.evaluation.binary.Recall
-
- apply(int, int) - Method in class org.apache.spark.mllib.linalg.DenseMatrix
-
- apply(int) - Method in class org.apache.spark.mllib.linalg.DenseVector
-
- apply(int, int) - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Gets the (i, j)-th element.
- apply(int, int) - Method in class org.apache.spark.mllib.linalg.SparseMatrix
-
- apply(int) - Static method in class org.apache.spark.mllib.linalg.SparseVector
-
- apply(int) - Method in interface org.apache.spark.mllib.linalg.Vector
-
Gets the value of the ith element.
- apply(int) - Static method in class org.apache.spark.mllib.tree.configuration.Algo
-
- apply(int) - Static method in class org.apache.spark.mllib.tree.configuration.EnsembleCombiningStrategy
-
- apply(int) - Static method in class org.apache.spark.mllib.tree.configuration.FeatureType
-
- apply(int) - Static method in class org.apache.spark.mllib.tree.configuration.QuantileStrategy
-
- apply(int, Predict, double, boolean) - Static method in class org.apache.spark.mllib.tree.model.Node
-
Construct a node with nodeIndex, predict, impurity and isLeaf parameters.
- apply(int) - Static method in class org.apache.spark.rdd.CheckpointState
-
- apply(long, String, Option<String>, String, boolean) - Static method in class org.apache.spark.scheduler.AccumulableInfo
-
Deprecated.
do not create AccumulableInfo. Since 2.0.0.
- apply(long, String, Option<String>, String) - Static method in class org.apache.spark.scheduler.AccumulableInfo
-
Deprecated.
do not create AccumulableInfo. Since 2.0.0.
- apply(long, String, String) - Static method in class org.apache.spark.scheduler.AccumulableInfo
-
Deprecated.
do not create AccumulableInfo. Since 2.0.0.
- apply(String, long, Enumeration.Value, ByteBuffer) - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StatusUpdate$
-
Alternate factory method that takes a ByteBuffer directly for the data field
- apply(long, TaskMetrics) - Static method in class org.apache.spark.scheduler.RuntimePercentage
-
- apply(int) - Static method in class org.apache.spark.scheduler.SchedulingMode
-
- apply(int) - Static method in class org.apache.spark.scheduler.TaskLocality
-
- apply(Object) - Method in class org.apache.spark.sql.Column
-
Extracts a value or values from a complex type.
- apply(String) - Method in class org.apache.spark.sql.Dataset
-
Selects column based on the column name and return it as a
Column.
- apply(Column...) - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
-
Creates a Column for this UDAF using given Columns as input arguments.
- apply(Seq<Column>) - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
-
Creates a Column for this UDAF using given Columns as input arguments.
- apply(Seq<Column>) - Method in class org.apache.spark.sql.expressions.UserDefinedFunction
-
- apply(int) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- apply(ScriptInputOutputSchema) - Static method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- apply(int) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- apply(int) - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- apply(Dataset<Row>, Seq<Expression>, RelationalGroupedDataset.GroupType) - Static method in class org.apache.spark.sql.RelationalGroupedDataset
-
- apply(int) - Method in interface org.apache.spark.sql.Row
-
Returns the value at position i.
- apply(String) - Static method in class org.apache.spark.sql.streaming.ProcessingTime
-
- apply(Duration) - Static method in class org.apache.spark.sql.streaming.ProcessingTime
-
- apply(DataType) - Static method in class org.apache.spark.sql.types.ArrayType
-
Construct a
ArrayType object with the given element type.
- apply(double) - Static method in class org.apache.spark.sql.types.Decimal
-
- apply(long) - Static method in class org.apache.spark.sql.types.Decimal
-
- apply(int) - Static method in class org.apache.spark.sql.types.Decimal
-
- apply(BigDecimal) - Static method in class org.apache.spark.sql.types.Decimal
-
- apply(BigDecimal) - Static method in class org.apache.spark.sql.types.Decimal
-
- apply(BigInteger) - Static method in class org.apache.spark.sql.types.Decimal
-
- apply(BigInt) - Static method in class org.apache.spark.sql.types.Decimal
-
- apply(BigDecimal, int, int) - Static method in class org.apache.spark.sql.types.Decimal
-
- apply(BigDecimal, int, int) - Static method in class org.apache.spark.sql.types.Decimal
-
- apply(long, int, int) - Static method in class org.apache.spark.sql.types.Decimal
-
- apply(String) - Static method in class org.apache.spark.sql.types.Decimal
-
- apply(DataType, DataType) - Static method in class org.apache.spark.sql.types.MapType
-
Construct a
MapType object with the given key type and value type.
- apply(String) - Method in class org.apache.spark.sql.types.StructType
-
- apply(Set<String>) - Method in class org.apache.spark.sql.types.StructType
-
Returns a
StructType containing
StructFields of the given names, preserving the
original order of fields.
- apply(int) - Method in class org.apache.spark.sql.types.StructType
-
- apply(String) - Static method in class org.apache.spark.storage.BlockId
-
Converts a BlockId "name" String back into a BlockId.
- apply(String, String, int) - Static method in class org.apache.spark.storage.BlockManagerId
-
- apply(ObjectInput) - Static method in class org.apache.spark.storage.BlockManagerId
-
- apply(boolean, boolean, boolean, boolean, int) - Static method in class org.apache.spark.storage.StorageLevel
-
:: DeveloperApi ::
Create a new StorageLevel object.
- apply(boolean, boolean, boolean, int) - Static method in class org.apache.spark.storage.StorageLevel
-
:: DeveloperApi ::
Create a new StorageLevel object without setting useOffHeap.
- apply(int, int) - Static method in class org.apache.spark.storage.StorageLevel
-
:: DeveloperApi ::
Create a new StorageLevel object from its integer representation.
- apply(ObjectInput) - Static method in class org.apache.spark.storage.StorageLevel
-
:: DeveloperApi ::
Read StorageLevel object from ObjectInput stream.
- apply(String, int) - Static method in class org.apache.spark.streaming.kafka.Broker
-
- apply(Map<String, String>) - Method in class org.apache.spark.streaming.kafka.KafkaCluster.SimpleConsumerConfig$
-
Make a consumer config without requiring group.id or zookeeper.connect,
since communicating with brokers also needs common settings such as timeout
- apply(String, int, long, long) - Static method in class org.apache.spark.streaming.kafka.OffsetRange
-
- apply(TopicAndPartition, long, long) - Static method in class org.apache.spark.streaming.kafka.OffsetRange
-
- apply(long) - Static method in class org.apache.spark.streaming.Milliseconds
-
- apply(long) - Static method in class org.apache.spark.streaming.Minutes
-
- apply(int) - Static method in class org.apache.spark.streaming.scheduler.ReceiverState
-
- apply(long) - Static method in class org.apache.spark.streaming.Seconds
-
- apply(int) - Static method in class org.apache.spark.TaskState
-
- apply(ShuffleReadMetrics) - Method in class org.apache.spark.ui.jobs.UIData.ShuffleReadMetricsUIData$
-
- apply(ShuffleWriteMetrics) - Method in class org.apache.spark.ui.jobs.UIData.ShuffleWriteMetricsUIData$
-
- apply(TaskInfo, Option<TaskMetrics>) - Method in class org.apache.spark.ui.jobs.UIData.TaskUIData$
-
- apply(TraversableOnce<Object>) - Static method in class org.apache.spark.util.StatCounter
-
Build a StatCounter from a list of values.
- apply(Seq<Object>) - Static method in class org.apache.spark.util.StatCounter
-
Build a StatCounter from a list of values passed as variable-length arguments.
- ApplyInPlace - Class in org.apache.spark.ml.ann
-
Implements in-place application of functions in the arrays
- ApplyInPlace() - Constructor for class org.apache.spark.ml.ann.ApplyInPlace
-
- applyOrElse(A1, Function1<A1, B1>) - Static method in class org.apache.spark.sql.types.StructType
-
- applySchema(RDD<Row>, StructType) - Method in class org.apache.spark.sql.SQLContext
-
Deprecated.
Use createDataFrame instead. Since 1.3.0.
- applySchema(JavaRDD<Row>, StructType) - Method in class org.apache.spark.sql.SQLContext
-
Deprecated.
Use createDataFrame instead. Since 1.3.0.
- applySchema(RDD<?>, Class<?>) - Method in class org.apache.spark.sql.SQLContext
-
Deprecated.
Use createDataFrame instead. Since 1.3.0.
- applySchema(JavaRDD<?>, Class<?>) - Method in class org.apache.spark.sql.SQLContext
-
Deprecated.
Use createDataFrame instead. Since 1.3.0.
- appName() - Method in class org.apache.spark.api.java.JavaSparkContext
-
- appName() - Method in class org.apache.spark.scheduler.SparkListenerApplicationStart
-
- appName() - Method in class org.apache.spark.SparkContext
-
- appName(String) - Method in class org.apache.spark.sql.SparkSession.Builder
-
Sets a name for the application, which will be shown in the Spark web UI.
- approxCountDistinct(Column) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the approximate number of distinct items in a group.
- approxCountDistinct(String) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the approximate number of distinct items in a group.
- approxCountDistinct(Column, double) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the approximate number of distinct items in a group.
- approxCountDistinct(String, double) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the approximate number of distinct items in a group.
- ApproxHist() - Static method in class org.apache.spark.mllib.tree.configuration.QuantileStrategy
-
- approxQuantile(String, double[], double) - Method in class org.apache.spark.sql.DataFrameStatFunctions
-
Calculates the approximate quantiles of a numerical column of a DataFrame.
- AreaUnderCurve - Class in org.apache.spark.mllib.evaluation
-
Computes the area under the curve (AUC) using the trapezoidal rule.
- AreaUnderCurve() - Constructor for class org.apache.spark.mllib.evaluation.AreaUnderCurve
-
- areaUnderPR() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
-
Computes the area under the precision-recall curve.
- areaUnderROC() - Method in class org.apache.spark.ml.classification.BinaryLogisticRegressionSummary
-
Computes the area under the receiver operating characteristic (ROC) curve.
- areaUnderROC() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
-
Computes the area under the receiver operating characteristic (ROC) curve.
- argmax() - Method in class org.apache.spark.ml.linalg.DenseVector
-
- argmax() - Method in class org.apache.spark.ml.linalg.SparseVector
-
- argmax() - Method in interface org.apache.spark.ml.linalg.Vector
-
Find the index of a maximal element.
- argmax() - Method in class org.apache.spark.mllib.linalg.DenseVector
-
- argmax() - Method in class org.apache.spark.mllib.linalg.SparseVector
-
- argmax() - Method in interface org.apache.spark.mllib.linalg.Vector
-
Find the index of a maximal element.
- argString() - Method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- argString() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- argString() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- array(DataType) - Method in class org.apache.spark.sql.ColumnName
-
Creates a new StructField of type array.
- array(Column...) - Static method in class org.apache.spark.sql.functions
-
Creates a new array column.
- array(String, String...) - Static method in class org.apache.spark.sql.functions
-
Creates a new array column.
- array(Seq<Column>) - Static method in class org.apache.spark.sql.functions
-
Creates a new array column.
- array(String, Seq<String>) - Static method in class org.apache.spark.sql.functions
-
Creates a new array column.
- array_contains(Column, Object) - Static method in class org.apache.spark.sql.functions
-
Returns true if the array contains value
- arrayLengthGt(double) - Static method in class org.apache.spark.ml.param.ParamValidators
-
Check that the array length is greater than lowerBound.
- ArrayType - Class in org.apache.spark.sql.types
-
- ArrayType(DataType, boolean) - Constructor for class org.apache.spark.sql.types.ArrayType
-
- as(Encoder<U>) - Method in class org.apache.spark.sql.Column
-
Provides a type hint about the expected return value of this column.
- as(String) - Method in class org.apache.spark.sql.Column
-
Gives the column an alias.
- as(Seq<String>) - Method in class org.apache.spark.sql.Column
-
(Scala-specific) Assigns the given aliases to the results of a table generating function.
- as(String[]) - Method in class org.apache.spark.sql.Column
-
Assigns the given aliases to the results of a table generating function.
- as(Symbol) - Method in class org.apache.spark.sql.Column
-
Gives the column an alias.
- as(String, Metadata) - Method in class org.apache.spark.sql.Column
-
Gives the column an alias with metadata.
- as(Encoder<U>) - Method in class org.apache.spark.sql.Dataset
-
:: Experimental ::
Returns a new Dataset where each record has been mapped on to the specified type.
- as(String) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset with an alias set.
- as(Symbol) - Method in class org.apache.spark.sql.Dataset
-
(Scala-specific) Returns a new Dataset with an alias set.
- asBreeze() - Method in interface org.apache.spark.ml.linalg.Matrix
-
Converts to a breeze matrix.
- asBreeze() - Method in interface org.apache.spark.ml.linalg.Vector
-
Converts the instance to a breeze vector.
- asBreeze() - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Converts to a breeze matrix.
- asBreeze() - Method in interface org.apache.spark.mllib.linalg.Vector
-
Converts the instance to a breeze vector.
- asc() - Method in class org.apache.spark.sql.Column
-
Returns an ordering used in sorting.
- asc(String) - Static method in class org.apache.spark.sql.functions
-
Returns a sort expression based on ascending order of the column.
- ascii(Column) - Static method in class org.apache.spark.sql.functions
-
Computes the numeric value of the first character of the string column, and returns the
result as an int column.
- asCode() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- asCode() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- asCode() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- asin(Column) - Static method in class org.apache.spark.sql.functions
-
Computes the sine inverse of the given value; the returned angle is in the range
-pi/2 through pi/2.
- asin(String) - Static method in class org.apache.spark.sql.functions
-
Computes the sine inverse of the given column; the returned angle is in the range
-pi/2 through pi/2.
- asIterator() - Method in class org.apache.spark.serializer.DeserializationStream
-
Read the elements of this stream through an iterator.
- asJavaPairRDD() - Method in class org.apache.spark.api.r.PairwiseRRDD
-
- asJavaRDD() - Method in class org.apache.spark.api.r.RRDD
-
- asJavaRDD() - Method in class org.apache.spark.api.r.StringRRDD
-
- asKeyValueIterator() - Method in class org.apache.spark.serializer.DeserializationStream
-
Read the elements of this stream through an iterator over key-value pairs.
- AskPermissionToCommitOutput - Class in org.apache.spark.scheduler
-
- AskPermissionToCommitOutput(int, int, int) - Constructor for class org.apache.spark.scheduler.AskPermissionToCommitOutput
-
- askRpcTimeout(SparkConf) - Static method in class org.apache.spark.util.RpcUtils
-
Returns the default Spark timeout to use for RPC ask operations.
- askSlaves() - Method in class org.apache.spark.storage.BlockManagerMessages.GetBlockStatus
-
- askSlaves() - Method in class org.apache.spark.storage.BlockManagerMessages.GetMatchingBlockIds
-
- asML() - Method in class org.apache.spark.mllib.linalg.DenseMatrix
-
- asML() - Method in class org.apache.spark.mllib.linalg.DenseVector
-
- asML() - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Convert this matrix to the new mllib-local representation.
- asML() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
-
- asML() - Method in class org.apache.spark.mllib.linalg.SparseVector
-
- asML() - Method in interface org.apache.spark.mllib.linalg.Vector
-
Convert this vector to the new mllib-local representation.
- asRDDId() - Method in class org.apache.spark.storage.BlockId
-
- asRDDId() - Static method in class org.apache.spark.storage.BroadcastBlockId
-
- asRDDId() - Static method in class org.apache.spark.storage.RDDBlockId
-
- asRDDId() - Static method in class org.apache.spark.storage.ShuffleBlockId
-
- asRDDId() - Static method in class org.apache.spark.storage.ShuffleDataBlockId
-
- asRDDId() - Static method in class org.apache.spark.storage.ShuffleIndexBlockId
-
- asRDDId() - Static method in class org.apache.spark.storage.StreamBlockId
-
- asRDDId() - Static method in class org.apache.spark.storage.TaskResultBlockId
-
- assertNotSpilled(SparkContext, String, Function0<T>) - Static method in class org.apache.spark.TestUtils
-
Run some code involving jobs submitted to the given context and assert that the jobs
did not spill.
- assertSpilled(SparkContext, String, Function0<T>) - Static method in class org.apache.spark.TestUtils
-
Run some code involving jobs submitted to the given context and assert that the jobs spilled.
- assignments() - Method in class org.apache.spark.mllib.clustering.PowerIterationClusteringModel
-
- AssociationRules - Class in org.apache.spark.mllib.fpm
-
Generates association rules from a RDD[FreqItemset[Item].
- AssociationRules() - Constructor for class org.apache.spark.mllib.fpm.AssociationRules
-
Constructs a default instance with default parameters {minConfidence = 0.8}.
- AssociationRules.Rule<Item> - Class in org.apache.spark.mllib.fpm
-
An association rule between sets of items.
- AsyncRDDActions<T> - Class in org.apache.spark.rdd
-
A set of asynchronous RDD actions available through an implicit conversion.
- AsyncRDDActions(RDD<T>, ClassTag<T>) - Constructor for class org.apache.spark.rdd.AsyncRDDActions
-
- atan(Column) - Static method in class org.apache.spark.sql.functions
-
Computes the tangent inverse of the given value.
- atan(String) - Static method in class org.apache.spark.sql.functions
-
Computes the tangent inverse of the given column.
- atan2(Column, Column) - Static method in class org.apache.spark.sql.functions
-
Returns the angle theta from the conversion of rectangular coordinates (x, y) to
polar coordinates (r, theta).
- atan2(Column, String) - Static method in class org.apache.spark.sql.functions
-
Returns the angle theta from the conversion of rectangular coordinates (x, y) to
polar coordinates (r, theta).
- atan2(String, Column) - Static method in class org.apache.spark.sql.functions
-
Returns the angle theta from the conversion of rectangular coordinates (x, y) to
polar coordinates (r, theta).
- atan2(String, String) - Static method in class org.apache.spark.sql.functions
-
Returns the angle theta from the conversion of rectangular coordinates (x, y) to
polar coordinates (r, theta).
- atan2(Column, double) - Static method in class org.apache.spark.sql.functions
-
Returns the angle theta from the conversion of rectangular coordinates (x, y) to
polar coordinates (r, theta).
- atan2(String, double) - Static method in class org.apache.spark.sql.functions
-
Returns the angle theta from the conversion of rectangular coordinates (x, y) to
polar coordinates (r, theta).
- atan2(double, Column) - Static method in class org.apache.spark.sql.functions
-
Returns the angle theta from the conversion of rectangular coordinates (x, y) to
polar coordinates (r, theta).
- atan2(double, String) - Static method in class org.apache.spark.sql.functions
-
Returns the angle theta from the conversion of rectangular coordinates (x, y) to
polar coordinates (r, theta).
- attempt() - Method in class org.apache.spark.status.api.v1.TaskData
-
- attemptId() - Method in class org.apache.spark.scheduler.StageInfo
-
- attemptId() - Method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
-
- attemptId() - Method in class org.apache.spark.status.api.v1.StageData
-
- attemptNumber() - Method in class org.apache.spark.scheduler.AskPermissionToCommitOutput
-
- attemptNumber() - Method in class org.apache.spark.scheduler.TaskInfo
-
- attemptNumber() - Method in class org.apache.spark.TaskCommitDenied
-
- attemptNumber() - Method in class org.apache.spark.TaskContext
-
How many times this task has been attempted.
- attempts() - Method in class org.apache.spark.status.api.v1.ApplicationInfo
-
- attr() - Method in class org.apache.spark.graphx.Edge
-
- attr() - Method in class org.apache.spark.graphx.EdgeContext
-
The attribute associated with the edge.
- attr() - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
-
- Attribute - Class in org.apache.spark.ml.attribute
-
:: DeveloperApi ::
Abstract class for ML attributes.
- Attribute() - Constructor for class org.apache.spark.ml.attribute.Attribute
-
- attribute() - Method in class org.apache.spark.sql.sources.EqualNullSafe
-
- attribute() - Method in class org.apache.spark.sql.sources.EqualTo
-
- attribute() - Method in class org.apache.spark.sql.sources.GreaterThan
-
- attribute() - Method in class org.apache.spark.sql.sources.GreaterThanOrEqual
-
- attribute() - Method in class org.apache.spark.sql.sources.In
-
- attribute() - Method in class org.apache.spark.sql.sources.IsNotNull
-
- attribute() - Method in class org.apache.spark.sql.sources.IsNull
-
- attribute() - Method in class org.apache.spark.sql.sources.LessThan
-
- attribute() - Method in class org.apache.spark.sql.sources.LessThanOrEqual
-
- attribute() - Method in class org.apache.spark.sql.sources.StringContains
-
- attribute() - Method in class org.apache.spark.sql.sources.StringEndsWith
-
- attribute() - Method in class org.apache.spark.sql.sources.StringStartsWith
-
- AttributeGroup - Class in org.apache.spark.ml.attribute
-
:: DeveloperApi ::
Attributes that describe a vector ML column.
- AttributeGroup(String) - Constructor for class org.apache.spark.ml.attribute.AttributeGroup
-
Creates an attribute group without attribute info.
- AttributeGroup(String, int) - Constructor for class org.apache.spark.ml.attribute.AttributeGroup
-
Creates an attribute group knowing only the number of attributes.
- AttributeGroup(String, Attribute[]) - Constructor for class org.apache.spark.ml.attribute.AttributeGroup
-
Creates an attribute group with attributes.
- AttributeKeys - Class in org.apache.spark.ml.attribute
-
Keys used to store attributes.
- AttributeKeys() - Constructor for class org.apache.spark.ml.attribute.AttributeKeys
-
- attributes() - Method in class org.apache.spark.ml.attribute.AttributeGroup
-
Optional array of attributes.
- ATTRIBUTES() - Static method in class org.apache.spark.ml.attribute.AttributeKeys
-
- AttributeType - Class in org.apache.spark.ml.attribute
-
:: DeveloperApi ::
An enum-like type for attribute types: AttributeType$.Numeric, AttributeType$.Nominal,
and AttributeType$.Binary.
- AttributeType(String) - Constructor for class org.apache.spark.ml.attribute.AttributeType
-
- attrType() - Method in class org.apache.spark.ml.attribute.Attribute
-
Attribute type.
- attrType() - Method in class org.apache.spark.ml.attribute.BinaryAttribute
-
- attrType() - Method in class org.apache.spark.ml.attribute.NominalAttribute
-
- attrType() - Method in class org.apache.spark.ml.attribute.NumericAttribute
-
- attrType() - Static method in class org.apache.spark.ml.attribute.UnresolvedAttribute
-
- available() - Method in class org.apache.spark.io.LZ4BlockInputStream
-
- available() - Method in class org.apache.spark.storage.BufferReleasingInputStream
-
- Average() - Static method in class org.apache.spark.mllib.tree.configuration.EnsembleCombiningStrategy
-
- avg(MapFunction<T, Double>) - Static method in class org.apache.spark.sql.expressions.javalang.typed
-
Average aggregate function.
- avg(Function1<IN, Object>) - Static method in class org.apache.spark.sql.expressions.scalalang.typed
-
Average aggregate function.
- avg(Column) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the average of the values in a group.
- avg(String) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the average of the values in a group.
- avg(String...) - Method in class org.apache.spark.sql.RelationalGroupedDataset
-
Compute the mean value for each numeric columns for each group.
- avg(Seq<String>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
-
Compute the mean value for each numeric columns for each group.
- avg() - Method in class org.apache.spark.util.DoubleAccumulator
-
Returns the average of elements added to the accumulator.
- avg() - Method in class org.apache.spark.util.LongAccumulator
-
Returns the average of elements added to the accumulator.
- avgMetrics() - Method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- awaitAnyTermination() - Method in class org.apache.spark.sql.streaming.StreamingQueryManager
-
Wait until any of the queries on the associated SQLContext has terminated since the
creation of the context, or since resetTerminated() was called.
- awaitAnyTermination(long) - Method in class org.apache.spark.sql.streaming.StreamingQueryManager
-
Wait until any of the queries on the associated SQLContext has terminated since the
creation of the context, or since resetTerminated() was called.
- awaitResult(Awaitable<T>, Duration) - Static method in class org.apache.spark.util.ThreadUtils
-
Preferred alternative to Await.result().
- awaitTermination() - Method in interface org.apache.spark.sql.streaming.StreamingQuery
-
Waits for the termination of this query, either by query.stop() or by an exception.
- awaitTermination(long) - Method in interface org.apache.spark.sql.streaming.StreamingQuery
-
Waits for the termination of this query, either by query.stop() or by an exception.
- awaitTermination() - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Wait for the execution to stop.
- awaitTermination() - Method in class org.apache.spark.streaming.StreamingContext
-
Wait for the execution to stop.
- awaitTerminationOrTimeout(long) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Wait for the execution to stop.
- awaitTerminationOrTimeout(long) - Method in class org.apache.spark.streaming.StreamingContext
-
Wait for the execution to stop.
- axpy(double, Vector, Vector) - Static method in class org.apache.spark.ml.linalg.BLAS
-
y += a * x
- axpy(double, Vector, Vector) - Static method in class org.apache.spark.mllib.linalg.BLAS
-
y += a * x
- cache() - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Persist this RDD with the default storage level (`MEMORY_ONLY`).
- cache() - Method in class org.apache.spark.api.java.JavaPairRDD
-
Persist this RDD with the default storage level (`MEMORY_ONLY`).
- cache() - Method in class org.apache.spark.api.java.JavaRDD
-
Persist this RDD with the default storage level (`MEMORY_ONLY`).
- cache() - Static method in class org.apache.spark.api.r.RRDD
-
- cache() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- cache() - Method in class org.apache.spark.graphx.Graph
-
Caches the vertices and edges associated with this graph at the previously-specified target
storage levels, which default to MEMORY_ONLY.
- cache() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
Persists the edge partitions using `targetStorageLevel`, which defaults to MEMORY_ONLY.
- cache() - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- cache() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
Persists the vertex partitions at `targetStorageLevel`, which defaults to MEMORY_ONLY.
- cache() - Static method in class org.apache.spark.graphx.VertexRDD
-
- cache() - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
-
Caches the underlying RDD.
- cache() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- cache() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- cache() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- cache() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- cache() - Method in class org.apache.spark.rdd.RDD
-
Persist this RDD with the default storage level (`MEMORY_ONLY`).
- cache() - Static method in class org.apache.spark.rdd.UnionRDD
-
- cache() - Method in class org.apache.spark.sql.Dataset
-
Persist this Dataset with the default storage level (MEMORY_AND_DISK).
- cache() - Method in class org.apache.spark.streaming.api.java.JavaDStream
-
Persist RDDs of this DStream with the default storage level (MEMORY_ONLY_SER)
- cache() - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- cache() - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Persist RDDs of this DStream with the default storage level (MEMORY_ONLY_SER)
- cache() - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- cache() - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- cache() - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- cache() - Method in class org.apache.spark.streaming.dstream.DStream
-
Persist RDDs of this DStream with the default storage level (MEMORY_ONLY_SER)
- cacheNodeIds() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- cacheNodeIds() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- cacheNodeIds() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- cacheNodeIds() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- cacheNodeIds() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- cacheNodeIds() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- cacheNodeIds() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- cacheNodeIds() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- cacheNodeIds() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- cacheNodeIds() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- cacheNodeIds() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- cacheNodeIds() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- cacheSize() - Method in interface org.apache.spark.SparkExecutorInfo
-
- cacheSize() - Method in class org.apache.spark.SparkExecutorInfoImpl
-
- cacheSize() - Method in class org.apache.spark.storage.StorageStatus
-
Return the memory used by caching RDDs
- cacheTable(String) - Method in class org.apache.spark.sql.catalog.Catalog
-
Caches the specified table in-memory.
- cacheTable(String) - Method in class org.apache.spark.sql.internal.CatalogImpl
-
Caches the specified table in-memory.
- cacheTable(String) - Method in class org.apache.spark.sql.SQLContext
-
Caches the specified table in-memory.
- calculate(DenseVector<Object>) - Method in class org.apache.spark.ml.classification.LogisticCostFun
-
- calculate(DenseVector<Object>) - Method in class org.apache.spark.ml.regression.AFTCostFun
-
- calculate(DenseVector<Object>) - Method in class org.apache.spark.ml.regression.LeastSquaresCostFun
-
- calculate(double[], double) - Static method in class org.apache.spark.mllib.tree.impurity.Entropy
-
:: DeveloperApi ::
information calculation for multiclass classification
- calculate(double, double, double) - Static method in class org.apache.spark.mllib.tree.impurity.Entropy
-
:: DeveloperApi ::
variance calculation
- calculate(double[], double) - Static method in class org.apache.spark.mllib.tree.impurity.Gini
-
:: DeveloperApi ::
information calculation for multiclass classification
- calculate(double, double, double) - Static method in class org.apache.spark.mllib.tree.impurity.Gini
-
:: DeveloperApi ::
variance calculation
- calculate(double[], double) - Method in interface org.apache.spark.mllib.tree.impurity.Impurity
-
:: DeveloperApi ::
information calculation for multiclass classification
- calculate(double, double, double) - Method in interface org.apache.spark.mllib.tree.impurity.Impurity
-
:: DeveloperApi ::
information calculation for regression
- calculate(double[], double) - Static method in class org.apache.spark.mllib.tree.impurity.Variance
-
:: DeveloperApi ::
information calculation for multiclass classification
- calculate(double, double, double) - Static method in class org.apache.spark.mllib.tree.impurity.Variance
-
:: DeveloperApi ::
variance calculation
- CalendarIntervalType - Class in org.apache.spark.sql.types
-
:: DeveloperApi ::
The data type representing calendar time intervals.
- CalendarIntervalType - Static variable in class org.apache.spark.sql.types.DataTypes
-
Gets the CalendarIntervalType object.
- call(K, Iterator<V1>, Iterator<V2>) - Method in interface org.apache.spark.api.java.function.CoGroupFunction
-
- call(T) - Method in interface org.apache.spark.api.java.function.DoubleFlatMapFunction
-
- call(T) - Method in interface org.apache.spark.api.java.function.DoubleFunction
-
- call(T) - Method in interface org.apache.spark.api.java.function.FilterFunction
-
- call(T) - Method in interface org.apache.spark.api.java.function.FlatMapFunction
-
- call(T1, T2) - Method in interface org.apache.spark.api.java.function.FlatMapFunction2
-
- call(K, Iterator<V>) - Method in interface org.apache.spark.api.java.function.FlatMapGroupsFunction
-
- call(T) - Method in interface org.apache.spark.api.java.function.ForeachFunction
-
- call(Iterator<T>) - Method in interface org.apache.spark.api.java.function.ForeachPartitionFunction
-
- call(T1) - Method in interface org.apache.spark.api.java.function.Function
-
- call() - Method in interface org.apache.spark.api.java.function.Function0
-
- call(T1, T2) - Method in interface org.apache.spark.api.java.function.Function2
-
- call(T1, T2, T3) - Method in interface org.apache.spark.api.java.function.Function3
-
- call(T1, T2, T3, T4) - Method in interface org.apache.spark.api.java.function.Function4
-
- call(T) - Method in interface org.apache.spark.api.java.function.MapFunction
-
- call(K, Iterator<V>) - Method in interface org.apache.spark.api.java.function.MapGroupsFunction
-
- call(Iterator<T>) - Method in interface org.apache.spark.api.java.function.MapPartitionsFunction
-
- call(T) - Method in interface org.apache.spark.api.java.function.PairFlatMapFunction
-
- call(T) - Method in interface org.apache.spark.api.java.function.PairFunction
-
- call(T, T) - Method in interface org.apache.spark.api.java.function.ReduceFunction
-
- call(T) - Method in interface org.apache.spark.api.java.function.VoidFunction
-
- call(T1, T2) - Method in interface org.apache.spark.api.java.function.VoidFunction2
-
- call(T1) - Method in interface org.apache.spark.sql.api.java.UDF1
-
- call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10) - Method in interface org.apache.spark.sql.api.java.UDF10
-
- call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11) - Method in interface org.apache.spark.sql.api.java.UDF11
-
- call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12) - Method in interface org.apache.spark.sql.api.java.UDF12
-
- call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12, T13) - Method in interface org.apache.spark.sql.api.java.UDF13
-
- call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12, T13, T14) - Method in interface org.apache.spark.sql.api.java.UDF14
-
- call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12, T13, T14, T15) - Method in interface org.apache.spark.sql.api.java.UDF15
-
- call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12, T13, T14, T15, T16) - Method in interface org.apache.spark.sql.api.java.UDF16
-
- call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12, T13, T14, T15, T16, T17) - Method in interface org.apache.spark.sql.api.java.UDF17
-
- call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12, T13, T14, T15, T16, T17, T18) - Method in interface org.apache.spark.sql.api.java.UDF18
-
- call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12, T13, T14, T15, T16, T17, T18, T19) - Method in interface org.apache.spark.sql.api.java.UDF19
-
- call(T1, T2) - Method in interface org.apache.spark.sql.api.java.UDF2
-
- call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12, T13, T14, T15, T16, T17, T18, T19, T20) - Method in interface org.apache.spark.sql.api.java.UDF20
-
- call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12, T13, T14, T15, T16, T17, T18, T19, T20, T21) - Method in interface org.apache.spark.sql.api.java.UDF21
-
- call(T1, T2, T3, T4, T5, T6, T7, T8, T9, T10, T11, T12, T13, T14, T15, T16, T17, T18, T19, T20, T21, T22) - Method in interface org.apache.spark.sql.api.java.UDF22
-
- call(T1, T2, T3) - Method in interface org.apache.spark.sql.api.java.UDF3
-
- call(T1, T2, T3, T4) - Method in interface org.apache.spark.sql.api.java.UDF4
-
- call(T1, T2, T3, T4, T5) - Method in interface org.apache.spark.sql.api.java.UDF5
-
- call(T1, T2, T3, T4, T5, T6) - Method in interface org.apache.spark.sql.api.java.UDF6
-
- call(T1, T2, T3, T4, T5, T6, T7) - Method in interface org.apache.spark.sql.api.java.UDF7
-
- call(T1, T2, T3, T4, T5, T6, T7, T8) - Method in interface org.apache.spark.sql.api.java.UDF8
-
- call(T1, T2, T3, T4, T5, T6, T7, T8, T9) - Method in interface org.apache.spark.sql.api.java.UDF9
-
- callSite() - Method in class org.apache.spark.storage.RDDInfo
-
- callUDF(String, Column...) - Static method in class org.apache.spark.sql.functions
-
Call an user-defined function.
- callUDF(String, Seq<Column>) - Static method in class org.apache.spark.sql.functions
-
Call an user-defined function.
- cancel() - Method in class org.apache.spark.ComplexFutureAction
-
- cancel() - Method in interface org.apache.spark.FutureAction
-
Cancels the execution of this action.
- cancel() - Method in class org.apache.spark.SimpleFutureAction
-
- cancelAllJobs() - Method in class org.apache.spark.api.java.JavaSparkContext
-
Cancel all jobs that have been scheduled or are running.
- cancelAllJobs() - Method in class org.apache.spark.SparkContext
-
Cancel all jobs that have been scheduled or are running.
- cancelJobGroup(String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Cancel active jobs for the specified group.
- cancelJobGroup(String) - Method in class org.apache.spark.SparkContext
-
Cancel active jobs for the specified group.
- canEqual(Object) - Static method in class org.apache.spark.Aggregator
-
- canEqual(Object) - Static method in class org.apache.spark.CleanAccum
-
- canEqual(Object) - Static method in class org.apache.spark.CleanBroadcast
-
- canEqual(Object) - Static method in class org.apache.spark.CleanCheckpoint
-
- canEqual(Object) - Static method in class org.apache.spark.CleanRDD
-
- canEqual(Object) - Static method in class org.apache.spark.CleanShuffle
-
- canEqual(Object) - Static method in class org.apache.spark.ExceptionFailure
-
- canEqual(Object) - Static method in class org.apache.spark.ExecutorLostFailure
-
- canEqual(Object) - Static method in class org.apache.spark.ExecutorRegistered
-
- canEqual(Object) - Static method in class org.apache.spark.ExecutorRemoved
-
- canEqual(Object) - Static method in class org.apache.spark.ExpireDeadHosts
-
- canEqual(Object) - Static method in class org.apache.spark.FetchFailed
-
- canEqual(Object) - Static method in class org.apache.spark.graphx.Edge
-
- canEqual(Object) - Static method in class org.apache.spark.ml.feature.Dot
-
- canEqual(Object) - Static method in class org.apache.spark.ml.feature.LabeledPoint
-
- canEqual(Object) - Static method in class org.apache.spark.ml.param.ParamPair
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.feature.VocabWord
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.linalg.distributed.IndexedRow
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.linalg.distributed.MatrixEntry
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.linalg.QRDecomposition
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.linalg.SingularValueDecomposition
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.recommendation.Rating
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.regression.LabeledPoint
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.stat.test.BinarySample
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- canEqual(Object) - Static method in class org.apache.spark.mllib.tree.model.Split
-
- canEqual(Object) - Static method in class org.apache.spark.Resubmitted
-
- canEqual(Object) - Static method in class org.apache.spark.rpc.netty.OnStart
-
- canEqual(Object) - Static method in class org.apache.spark.rpc.netty.OnStop
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.AccumulableInfo
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.AllJobsCancelled
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.AskPermissionToCommitOutput
-
- canEqual(Object) - Method in class org.apache.spark.scheduler.cluster.ExecutorInfo
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.JobSucceeded
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.local.KillTask
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.local.ReviveOffers
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.local.StatusUpdate
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.local.StopExecutor
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.ResubmitFailedStages
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.RuntimePercentage
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerApplicationEnd
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerApplicationStart
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerBlockManagerAdded
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerBlockManagerRemoved
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerBlockUpdated
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerEnvironmentUpdate
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerExecutorAdded
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerExecutorMetricsUpdate
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerExecutorRemoved
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerJobEnd
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerJobStart
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerStageCompleted
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerStageSubmitted
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerTaskEnd
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerTaskGettingResult
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerTaskStart
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerUnpersistRDD
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.StopCoordinator
-
- canEqual(Object) - Static method in class org.apache.spark.sql.DatasetHolder
-
- canEqual(Object) - Static method in class org.apache.spark.sql.expressions.UserDefinedFunction
-
- canEqual(Object) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- canEqual(Object) - Static method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- canEqual(Object) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- canEqual(Object) - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- canEqual(Object) - Static method in class org.apache.spark.sql.internal.HiveSerDe
-
- canEqual(Object) - Static method in class org.apache.spark.sql.jdbc.JdbcType
-
- canEqual(Object) - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
-
- canEqual(Object) - Static method in class org.apache.spark.sql.jdbc.OracleDialect
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.And
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.EqualNullSafe
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.EqualTo
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.GreaterThan
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.GreaterThanOrEqual
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.In
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.IsNotNull
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.IsNull
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.LessThan
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.LessThanOrEqual
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.Not
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.Or
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.StringContains
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.StringEndsWith
-
- canEqual(Object) - Static method in class org.apache.spark.sql.sources.StringStartsWith
-
- canEqual(Object) - Static method in class org.apache.spark.sql.streaming.ProcessingTime
-
- canEqual(Object) - Static method in class org.apache.spark.sql.types.ArrayType
-
- canEqual(Object) - Static method in class org.apache.spark.sql.types.DecimalType
-
- canEqual(Object) - Static method in class org.apache.spark.sql.types.MapType
-
- canEqual(Object) - Static method in class org.apache.spark.sql.types.StructField
-
- canEqual(Object) - Static method in class org.apache.spark.sql.types.StructType
-
- canEqual(Object) - Static method in class org.apache.spark.StopMapOutputTracker
-
- canEqual(Object) - Static method in class org.apache.spark.storage.BlockStatus
-
- canEqual(Object) - Static method in class org.apache.spark.storage.BlockUpdatedInfo
-
- canEqual(Object) - Static method in class org.apache.spark.storage.BroadcastBlockId
-
- canEqual(Object) - Static method in class org.apache.spark.storage.memory.DeserializedMemoryEntry
-
- canEqual(Object) - Static method in class org.apache.spark.storage.memory.SerializedMemoryEntry
-
- canEqual(Object) - Static method in class org.apache.spark.storage.RDDBlockId
-
- canEqual(Object) - Static method in class org.apache.spark.storage.ShuffleBlockId
-
- canEqual(Object) - Static method in class org.apache.spark.storage.ShuffleDataBlockId
-
- canEqual(Object) - Static method in class org.apache.spark.storage.ShuffleIndexBlockId
-
- canEqual(Object) - Static method in class org.apache.spark.storage.StreamBlockId
-
- canEqual(Object) - Static method in class org.apache.spark.storage.TaskResultBlockId
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.Duration
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.AllReceiverIds
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.BatchInfo
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.GetAllReceiverInfo
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.OutputOperationInfo
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.ReceiverInfo
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.StopAllReceivers
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchCompleted
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchStarted
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchSubmitted
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerOutputOperationCompleted
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerOutputOperationStarted
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverError
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStarted
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStopped
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.scheduler.StreamInputInfo
-
- canEqual(Object) - Static method in class org.apache.spark.streaming.Time
-
- canEqual(Object) - Static method in class org.apache.spark.Success
-
- canEqual(Object) - Static method in class org.apache.spark.TaskCommitDenied
-
- canEqual(Object) - Static method in class org.apache.spark.TaskKilled
-
- canEqual(Object) - Static method in class org.apache.spark.TaskResultLost
-
- canEqual(Object) - Static method in class org.apache.spark.TaskSchedulerIsSet
-
- canEqual(Object) - Static method in class org.apache.spark.UnknownReason
-
- canEqual(Object) - Static method in class org.apache.spark.util.MethodIdentifier
-
- canEqual(Object) - Method in class org.apache.spark.util.MutablePair
-
- canHandle(String) - Method in class org.apache.spark.sql.jdbc.AggregatedDialect
-
- canHandle(String) - Static method in class org.apache.spark.sql.jdbc.DB2Dialect
-
- canHandle(String) - Static method in class org.apache.spark.sql.jdbc.DerbyDialect
-
- canHandle(String) - Method in class org.apache.spark.sql.jdbc.JdbcDialect
-
Check if this dialect instance can handle a certain jdbc url.
- canHandle(String) - Static method in class org.apache.spark.sql.jdbc.MsSqlServerDialect
-
- canHandle(String) - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
-
- canHandle(String) - Static method in class org.apache.spark.sql.jdbc.NoopDialect
-
- canHandle(String) - Static method in class org.apache.spark.sql.jdbc.OracleDialect
-
- canHandle(String) - Static method in class org.apache.spark.sql.jdbc.PostgresDialect
-
- canonicalized() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- cartesian(JavaRDDLike<U, ?>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- cartesian(JavaRDDLike<U, ?>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- cartesian(JavaRDDLike<U, ?>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- cartesian(JavaRDDLike<U, ?>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return the Cartesian product of this RDD and another one, that is, the RDD of all pairs of
elements (a, b) where a is in this and b is in other.
- cartesian(RDD<U>, ClassTag<U>) - Static method in class org.apache.spark.api.r.RRDD
-
- cartesian(RDD<U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- cartesian(RDD<U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- cartesian(RDD<U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- cartesian(RDD<U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- cartesian(RDD<U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- cartesian(RDD<U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- cartesian(RDD<U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- cartesian(RDD<U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- cartesian(RDD<U>, ClassTag<U>) - Method in class org.apache.spark.rdd.RDD
-
Return the Cartesian product of this RDD and another one, that is, the RDD of all pairs of
elements (a, b) where a is in this and b is in other.
- cartesian(RDD<U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- caseSensitive() - Method in class org.apache.spark.ml.feature.StopWordsRemover
-
Whether to do a case sensitive comparison over the stop words.
- cast(DataType) - Method in class org.apache.spark.sql.Column
-
Casts the column to a different data type.
- cast(String) - Method in class org.apache.spark.sql.Column
-
Casts the column to a different data type, using the canonical string representation
of the type.
- Catalog - Class in org.apache.spark.sql.catalog
-
Catalog interface for Spark.
- Catalog() - Constructor for class org.apache.spark.sql.catalog.Catalog
-
- catalog() - Method in class org.apache.spark.sql.SparkSession
-
Interface through which the user may create, drop, alter or query underlying
databases, tables, functions etc.
- CatalogImpl - Class in org.apache.spark.sql.internal
-
Internal implementation of the user-facing Catalog.
- CatalogImpl(SparkSession) - Constructor for class org.apache.spark.sql.internal.CatalogImpl
-
- catalogString() - Method in class org.apache.spark.sql.types.ArrayType
-
- catalogString() - Static method in class org.apache.spark.sql.types.BinaryType
-
- catalogString() - Static method in class org.apache.spark.sql.types.BooleanType
-
- catalogString() - Static method in class org.apache.spark.sql.types.ByteType
-
- catalogString() - Static method in class org.apache.spark.sql.types.CalendarIntervalType
-
- catalogString() - Method in class org.apache.spark.sql.types.DataType
-
String representation for the type saved in external catalogs.
- catalogString() - Static method in class org.apache.spark.sql.types.DateType
-
- catalogString() - Static method in class org.apache.spark.sql.types.DecimalType
-
- catalogString() - Static method in class org.apache.spark.sql.types.DoubleType
-
- catalogString() - Static method in class org.apache.spark.sql.types.FloatType
-
- catalogString() - Static method in class org.apache.spark.sql.types.IntegerType
-
- catalogString() - Static method in class org.apache.spark.sql.types.LongType
-
- catalogString() - Method in class org.apache.spark.sql.types.MapType
-
- catalogString() - Static method in class org.apache.spark.sql.types.NullType
-
- catalogString() - Static method in class org.apache.spark.sql.types.NumericType
-
- catalogString() - Static method in class org.apache.spark.sql.types.ShortType
-
- catalogString() - Static method in class org.apache.spark.sql.types.StringType
-
- catalogString() - Method in class org.apache.spark.sql.types.StructType
-
- catalogString() - Static method in class org.apache.spark.sql.types.TimestampType
-
- CatalystScan - Interface in org.apache.spark.sql.sources
-
::Experimental::
An interface for experimenting with a more direct connection to the query planner.
- Categorical() - Static method in class org.apache.spark.mllib.tree.configuration.FeatureType
-
- categoricalFeaturesInfo() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- CategoricalSplit - Class in org.apache.spark.ml.tree
-
Split which tests a categorical feature.
- categories() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.SplitData
-
- categories() - Method in class org.apache.spark.mllib.tree.model.Split
-
- categoryMaps() - Method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- cause() - Method in exception org.apache.spark.sql.AnalysisException
-
- cause() - Method in exception org.apache.spark.sql.streaming.StreamingQueryException
-
- CausedBy - Class in org.apache.spark.util
-
Extractor Object for pulling out the root cause of an error.
- CausedBy() - Constructor for class org.apache.spark.util.CausedBy
-
- cbrt(Column) - Static method in class org.apache.spark.sql.functions
-
Computes the cube-root of the given value.
- cbrt(String) - Static method in class org.apache.spark.sql.functions
-
Computes the cube-root of the given column.
- ceil(Column) - Static method in class org.apache.spark.sql.functions
-
Computes the ceiling of the given value.
- ceil(String) - Static method in class org.apache.spark.sql.functions
-
Computes the ceiling of the given column.
- ceil() - Method in class org.apache.spark.sql.types.Decimal
-
- censorCol() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- censorCol() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- chainl1(Function0<Parsers.Parser<T>>, Function0<Parsers.Parser<Function2<T, T, T>>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- chainl1(Function0<Parsers.Parser<T>>, Function0<Parsers.Parser<U>>, Function0<Parsers.Parser<Function2<T, U, T>>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- chainr1(Function0<Parsers.Parser<T>>, Function0<Parsers.Parser<Function2<T, U, U>>>, Function2<T, U, U>, U) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- changePrecision(int, int) - Method in class org.apache.spark.sql.types.Decimal
-
Update precision and scale while keeping our value the same, and return true if successful.
- changePrecision(int, int, int) - Method in class org.apache.spark.sql.types.Decimal
-
- checkColumnType(StructType, String, DataType, String) - Static method in class org.apache.spark.ml.util.SchemaUtils
-
Check whether the given schema contains a column of the required data type.
- checkColumnTypes(StructType, String, Seq<DataType>, String) - Static method in class org.apache.spark.ml.util.SchemaUtils
-
Check whether the given schema contains a column of one of the require data types.
- checkErrors(Either<ArrayBuffer<Throwable>, T>) - Static method in class org.apache.spark.streaming.kafka.KafkaCluster
-
If the result is right, return it, otherwise throw SparkException
- checkFileExists(String, Configuration) - Static method in class org.apache.spark.streaming.util.HdfsUtils
-
Check if the file exists at the given path.
- checkHost(String, String) - Static method in class org.apache.spark.util.Utils
-
- checkHostPort(String, String) - Static method in class org.apache.spark.util.Utils
-
- checkNumericType(StructType, String, String) - Static method in class org.apache.spark.ml.util.SchemaUtils
-
Check whether the given schema contains a column of the numeric data type.
- checkpoint() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- checkpoint() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- checkpoint() - Static method in class org.apache.spark.api.java.JavaRDD
-
- checkpoint() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Mark this RDD for checkpointing.
- checkpoint() - Static method in class org.apache.spark.api.r.RRDD
-
- checkpoint() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- checkpoint() - Method in class org.apache.spark.graphx.Graph
-
Mark this Graph for checkpointing.
- checkpoint() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- checkpoint() - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- checkpoint() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- checkpoint() - Static method in class org.apache.spark.graphx.VertexRDD
-
- checkpoint() - Method in class org.apache.spark.rdd.HadoopRDD
-
- checkpoint() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- checkpoint() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- checkpoint() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- checkpoint() - Method in class org.apache.spark.rdd.RDD
-
Mark this RDD for checkpointing.
- checkpoint() - Static method in class org.apache.spark.rdd.UnionRDD
-
- checkpoint(Duration) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- checkpoint(Duration) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Enable periodic checkpointing of RDDs of this DStream.
- checkpoint(Duration) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- checkpoint(Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- checkpoint(Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- checkpoint(Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- checkpoint(Duration) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- checkpoint(String) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Sets the context to periodically checkpoint the DStream operations for master
fault-tolerance.
- checkpoint(Duration) - Method in class org.apache.spark.streaming.dstream.DStream
-
Enable periodic checkpointing of RDDs of this DStream
- checkpoint(String) - Method in class org.apache.spark.streaming.StreamingContext
-
Set the context to periodically checkpoint the DStream operations for driver
fault-tolerance.
- Checkpointed() - Static method in class org.apache.spark.rdd.CheckpointState
-
- CheckpointingInProgress() - Static method in class org.apache.spark.rdd.CheckpointState
-
- checkpointInterval() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- checkpointInterval() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- checkpointInterval() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- checkpointInterval() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- checkpointInterval() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- checkpointInterval() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- checkpointInterval() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- checkpointInterval() - Static method in class org.apache.spark.ml.clustering.LDA
-
- checkpointInterval() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- checkpointInterval() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- checkpointInterval() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- checkpointInterval() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- checkpointInterval() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- checkpointInterval() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- checkpointInterval() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- checkpointInterval() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- checkpointInterval() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- CheckpointReader - Class in org.apache.spark.streaming
-
- CheckpointReader() - Constructor for class org.apache.spark.streaming.CheckpointReader
-
- CheckpointState - Class in org.apache.spark.rdd
-
Enumeration to manage state transitions of an RDD through checkpointing
[ Initialized --> checkpointing in progress --> checkpointed ].
- CheckpointState() - Constructor for class org.apache.spark.rdd.CheckpointState
-
- checkState(boolean, Function0<String>) - Static method in class org.apache.spark.streaming.util.HdfsUtils
-
- child() - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- child() - Method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- child() - Method in class org.apache.spark.sql.sources.Not
-
- CHILD_CONNECTION_TIMEOUT - Static variable in class org.apache.spark.launcher.SparkLauncher
-
Maximum time (in ms) to wait for a child process to connect back to the launcher server
when using @link{#start()}.
- CHILD_PROCESS_LOGGER_NAME - Static variable in class org.apache.spark.launcher.SparkLauncher
-
Logger name to use when launching a child process.
- children() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- children() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- children() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- childrenResolved() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- chiSqFunc() - Method in class org.apache.spark.mllib.stat.test.ChiSqTest.Method
-
- ChiSqSelector - Class in org.apache.spark.ml.feature
-
Chi-Squared feature selection, which selects categorical features to use for predicting a
categorical label.
- ChiSqSelector(String) - Constructor for class org.apache.spark.ml.feature.ChiSqSelector
-
- ChiSqSelector() - Constructor for class org.apache.spark.ml.feature.ChiSqSelector
-
- ChiSqSelector - Class in org.apache.spark.mllib.feature
-
Creates a ChiSquared feature selector.
- ChiSqSelector(int) - Constructor for class org.apache.spark.mllib.feature.ChiSqSelector
-
- ChiSqSelectorModel - Class in org.apache.spark.ml.feature
-
- ChiSqSelectorModel - Class in org.apache.spark.mllib.feature
-
Chi Squared selector model.
- ChiSqSelectorModel(int[]) - Constructor for class org.apache.spark.mllib.feature.ChiSqSelectorModel
-
- ChiSqSelectorModel.SaveLoadV1_0$ - Class in org.apache.spark.mllib.feature
-
- ChiSqSelectorModel.SaveLoadV1_0$() - Constructor for class org.apache.spark.mllib.feature.ChiSqSelectorModel.SaveLoadV1_0$
-
- ChiSqSelectorModel.SaveLoadV1_0$.Data - Class in org.apache.spark.mllib.feature
-
Model data for import/export
- ChiSqSelectorModel.SaveLoadV1_0$.Data(int) - Constructor for class org.apache.spark.mllib.feature.ChiSqSelectorModel.SaveLoadV1_0$.Data
-
- chiSqTest(Vector, Vector) - Static method in class org.apache.spark.mllib.stat.Statistics
-
Conduct Pearson's chi-squared goodness of fit test of the observed data against the
expected distribution.
- chiSqTest(Vector) - Static method in class org.apache.spark.mllib.stat.Statistics
-
Conduct Pearson's chi-squared goodness of fit test of the observed data against the uniform
distribution, with each category having an expected frequency of 1 / observed.size.
- chiSqTest(Matrix) - Static method in class org.apache.spark.mllib.stat.Statistics
-
Conduct Pearson's independence test on the input contingency matrix, which cannot contain
negative entries or columns or rows that sum up to 0.
- chiSqTest(RDD<LabeledPoint>) - Static method in class org.apache.spark.mllib.stat.Statistics
-
Conduct Pearson's independence test for every feature against the label across the input RDD.
- chiSqTest(JavaRDD<LabeledPoint>) - Static method in class org.apache.spark.mllib.stat.Statistics
-
Java-friendly version of chiSqTest()
- ChiSqTest - Class in org.apache.spark.mllib.stat.test
-
Conduct the chi-squared test for the input RDDs using the specified method.
- ChiSqTest() - Constructor for class org.apache.spark.mllib.stat.test.ChiSqTest
-
- ChiSqTest.Method - Class in org.apache.spark.mllib.stat.test
-
param: name String name for the method.
- ChiSqTest.Method(String, Function2<Object, Object, Object>) - Constructor for class org.apache.spark.mllib.stat.test.ChiSqTest.Method
-
- ChiSqTest.Method$ - Class in org.apache.spark.mllib.stat.test
-
- ChiSqTest.Method$() - Constructor for class org.apache.spark.mllib.stat.test.ChiSqTest.Method$
-
- ChiSqTest.NullHypothesis$ - Class in org.apache.spark.mllib.stat.test
-
- ChiSqTest.NullHypothesis$() - Constructor for class org.apache.spark.mllib.stat.test.ChiSqTest.NullHypothesis$
-
- ChiSqTestResult - Class in org.apache.spark.mllib.stat.test
-
Object containing the test results for the chi-squared hypothesis test.
- chiSquared(Vector, Vector, String) - Static method in class org.apache.spark.mllib.stat.test.ChiSqTest
-
- chiSquaredFeatures(RDD<LabeledPoint>, String) - Static method in class org.apache.spark.mllib.stat.test.ChiSqTest
-
Conduct Pearson's independence test for each feature against the label across the input RDD.
- chiSquaredMatrix(Matrix, String) - Static method in class org.apache.spark.mllib.stat.test.ChiSqTest
-
- chmod700(File) - Static method in class org.apache.spark.util.Utils
-
JDK equivalent of chmod 700 file.
- CholeskyDecomposition - Class in org.apache.spark.mllib.linalg
-
Compute Cholesky decomposition.
- CholeskyDecomposition() - Constructor for class org.apache.spark.mllib.linalg.CholeskyDecomposition
-
- chunkedByteBuffer() - Method in class org.apache.spark.util.io.ChunkedByteBufferInputStream
-
- ChunkedByteBufferInputStream - Class in org.apache.spark.util.io
-
Reads data from a ChunkedByteBuffer.
- ChunkedByteBufferInputStream(ChunkedByteBuffer, boolean) - Constructor for class org.apache.spark.util.io.ChunkedByteBufferInputStream
-
- classForName(String) - Static method in class org.apache.spark.util.Utils
-
Preferred alternative to Class.forName(className)
- Classification() - Static method in class org.apache.spark.mllib.tree.configuration.Algo
-
- ClassificationModel<FeaturesType,M extends ClassificationModel<FeaturesType,M>> - Class in org.apache.spark.ml.classification
-
:: DeveloperApi ::
- ClassificationModel() - Constructor for class org.apache.spark.ml.classification.ClassificationModel
-
- ClassificationModel - Interface in org.apache.spark.mllib.classification
-
Represents a classification model that predicts to which of a set of categories an example
belongs.
- Classifier<FeaturesType,E extends Classifier<FeaturesType,E,M>,M extends ClassificationModel<FeaturesType,M>> - Class in org.apache.spark.ml.classification
-
:: DeveloperApi ::
- Classifier() - Constructor for class org.apache.spark.ml.classification.Classifier
-
- classifier() - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- classifier() - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- classIsLoadable(String) - Static method in class org.apache.spark.util.Utils
-
Determines whether the provided class is loadable in the current thread.
- className() - Method in class org.apache.spark.ExceptionFailure
-
- className() - Method in class org.apache.spark.sql.catalog.Function
-
- classpathEntries() - Method in class org.apache.spark.ui.env.EnvironmentListener
-
- classTag() - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
- classTag() - Method in class org.apache.spark.api.java.JavaPairRDD
-
- classTag() - Method in class org.apache.spark.api.java.JavaRDD
-
- classTag() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
- classTag() - Method in class org.apache.spark.storage.memory.DeserializedMemoryEntry
-
- classTag() - Method in interface org.apache.spark.storage.memory.MemoryEntry
-
- classTag() - Method in class org.apache.spark.storage.memory.SerializedMemoryEntry
-
- classTag() - Method in class org.apache.spark.streaming.api.java.JavaDStream
-
- classTag() - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
- classTag() - Method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- classTag() - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- classTag() - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- classTag() - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- classTag() - Method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- clean(long, boolean) - Method in class org.apache.spark.streaming.util.WriteAheadLog
-
Clean all the records that are older than the threshold time.
- clean(Object, boolean, boolean) - Static method in class org.apache.spark.util.ClosureCleaner
-
Clean the given closure in place.
- CleanAccum - Class in org.apache.spark
-
- CleanAccum(long) - Constructor for class org.apache.spark.CleanAccum
-
- CleanBroadcast - Class in org.apache.spark
-
- CleanBroadcast(long) - Constructor for class org.apache.spark.CleanBroadcast
-
- CleanCheckpoint - Class in org.apache.spark
-
- CleanCheckpoint(int) - Constructor for class org.apache.spark.CleanCheckpoint
-
- CleanRDD - Class in org.apache.spark
-
- CleanRDD(int) - Constructor for class org.apache.spark.CleanRDD
-
- CleanShuffle - Class in org.apache.spark
-
- CleanShuffle(int) - Constructor for class org.apache.spark.CleanShuffle
-
- CleanupTask - Interface in org.apache.spark
-
Classes that represent cleaning tasks.
- CleanupTaskWeakReference - Class in org.apache.spark
-
A WeakReference associated with a CleanupTask.
- CleanupTaskWeakReference(CleanupTask, Object, ReferenceQueue<Object>) - Constructor for class org.apache.spark.CleanupTaskWeakReference
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.clustering.KMeans
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.clustering.LDA
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.evaluation.RegressionEvaluator
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.Binarizer
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.Bucketizer
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.ColumnPruner
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.CountVectorizer
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.DCT
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.ElementwiseProduct
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.HashingTF
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.IDF
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.IDFModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.IndexToString
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.Interaction
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.MaxAbsScaler
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.MinMaxScaler
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.NGram
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.Normalizer
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.OneHotEncoder
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.PCA
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.PCAModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.PolynomialExpansion
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.RegexTokenizer
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.RFormula
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.SQLTransformer
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.StandardScaler
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.StandardScalerModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.StopWordsRemover
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.StringIndexer
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.StringIndexerModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.Tokenizer
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.VectorAssembler
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.VectorAttributeRewriter
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.VectorIndexer
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.VectorSlicer
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- clear(Param<?>) - Method in interface org.apache.spark.ml.param.Params
-
Clears the user-supplied value for the input param.
- clear(Param<?>) - Static method in class org.apache.spark.ml.Pipeline
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.PipelineModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.recommendation.ALS
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.recommendation.ALSModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.IsotonicRegression
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
-
- clear() - Method in class org.apache.spark.sql.util.ExecutionListenerManager
-
- clear() - Static method in class org.apache.spark.util.AccumulatorContext
-
- clearActive() - Static method in class org.apache.spark.sql.SQLContext
-
Deprecated.
Use SparkSession.clearActiveSession instead. Since 2.0.0.
- clearActiveSession() - Static method in class org.apache.spark.sql.SparkSession
-
Clears the active SparkSession for current thread.
- clearCache() - Method in class org.apache.spark.sql.catalog.Catalog
-
Removes all cached tables from the in-memory cache.
- clearCache() - Method in class org.apache.spark.sql.internal.CatalogImpl
-
Removes all cached tables from the in-memory cache.
- clearCache() - Method in class org.apache.spark.sql.SQLContext
-
Removes all cached tables from the in-memory cache.
- clearCallSite() - Method in class org.apache.spark.api.java.JavaSparkContext
-
Pass-through to SparkContext.setCallSite.
- clearCallSite() - Method in class org.apache.spark.SparkContext
-
Clear the thread-local property for overriding the call sites
of actions and RDDs.
- clearDefaultSession() - Static method in class org.apache.spark.sql.SparkSession
-
Clears the default SparkSession that is returned by the builder.
- clearDependencies() - Method in class org.apache.spark.rdd.CoGroupedRDD
-
- clearDependencies() - Method in class org.apache.spark.rdd.ShuffledRDD
-
- clearDependencies() - Method in class org.apache.spark.rdd.UnionRDD
-
- clearJobGroup() - Method in class org.apache.spark.api.java.JavaSparkContext
-
Clear the current thread's job group ID and its description.
- clearJobGroup() - Method in class org.apache.spark.SparkContext
-
Clear the current thread's job group ID and its description.
- clearThreshold() - Method in class org.apache.spark.mllib.classification.LogisticRegressionModel
-
Clears the threshold so that predict will output raw prediction scores.
- clearThreshold() - Method in class org.apache.spark.mllib.classification.SVMModel
-
Clears the threshold so that predict will output raw prediction scores.
- clone() - Method in class org.apache.spark.SparkConf
-
Copy this object
- clone() - Method in class org.apache.spark.sql.types.Decimal
-
- clone() - Method in class org.apache.spark.storage.StorageLevel
-
- clone() - Method in class org.apache.spark.util.random.BernoulliCellSampler
-
- clone() - Method in class org.apache.spark.util.random.BernoulliSampler
-
- clone() - Method in class org.apache.spark.util.random.PoissonSampler
-
- clone() - Method in interface org.apache.spark.util.random.RandomSampler
-
return a copy of the RandomSampler object
- clone(T, SerializerInstance, ClassTag<T>) - Static method in class org.apache.spark.util.Utils
-
Clone an object using a Spark serializer.
- cloneComplement() - Method in class org.apache.spark.util.random.BernoulliCellSampler
-
Return a sampler that is the complement of the range specified of the current sampler.
- close() - Method in class org.apache.spark.api.java.JavaSparkContext
-
- close() - Method in class org.apache.spark.io.SnappyOutputStreamWrapper
-
- close() - Method in class org.apache.spark.serializer.DeserializationStream
-
- close() - Method in class org.apache.spark.serializer.SerializationStream
-
- close(Throwable) - Method in class org.apache.spark.sql.ForeachWriter
-
Called when stopping to process one partition of new data in the executor side.
- close() - Method in class org.apache.spark.storage.BufferReleasingInputStream
-
- close() - Method in class org.apache.spark.storage.TimeTrackingOutputStream
-
- close() - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
- close() - Method in class org.apache.spark.streaming.util.WriteAheadLog
-
Close this log and release any resources.
- close() - Method in class org.apache.spark.util.io.ChunkedByteBufferInputStream
-
- ClosureCleaner - Class in org.apache.spark.util
-
A cleaner that renders closures serializable if they can be done so safely.
- ClosureCleaner() - Constructor for class org.apache.spark.util.ClosureCleaner
-
- closureSerializer() - Method in class org.apache.spark.SparkEnv
-
- cls() - Method in class org.apache.spark.util.MethodIdentifier
-
- clsTag() - Method in interface org.apache.spark.sql.Encoder
-
A ClassTag that can be used to construct and Array to contain a collection of `T`.
- cluster() - Method in class org.apache.spark.ml.clustering.GaussianMixtureSummary
-
Cluster centers of the transformed data.
- cluster() - Method in class org.apache.spark.ml.clustering.KMeansSummary
-
Cluster centers of the transformed data.
- cluster() - Method in class org.apache.spark.mllib.clustering.PowerIterationClustering.Assignment
-
- clusterCenters() - Method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- clusterCenters() - Method in class org.apache.spark.ml.clustering.KMeansModel
-
- clusterCenters() - Method in class org.apache.spark.mllib.clustering.BisectingKMeansModel
-
Leaf cluster centers.
- clusterCenters() - Method in class org.apache.spark.mllib.clustering.KMeansModel
-
- clusterCenters() - Method in class org.apache.spark.mllib.clustering.StreamingKMeansModel
-
- clusterSizes() - Method in class org.apache.spark.ml.clustering.GaussianMixtureSummary
-
Size of (number of data points in) each cluster.
- clusterSizes() - Method in class org.apache.spark.ml.clustering.KMeansSummary
-
Size of (number of data points in) each cluster.
- clusterWeights() - Method in class org.apache.spark.mllib.clustering.StreamingKMeansModel
-
- cn() - Method in class org.apache.spark.mllib.feature.VocabWord
-
- coalesce(int) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Return a new RDD that is reduced into numPartitions partitions.
- coalesce(int, boolean) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Return a new RDD that is reduced into numPartitions partitions.
- coalesce(int) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return a new RDD that is reduced into numPartitions partitions.
- coalesce(int, boolean) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return a new RDD that is reduced into numPartitions partitions.
- coalesce(int) - Method in class org.apache.spark.api.java.JavaRDD
-
Return a new RDD that is reduced into numPartitions partitions.
- coalesce(int, boolean) - Method in class org.apache.spark.api.java.JavaRDD
-
Return a new RDD that is reduced into numPartitions partitions.
- coalesce(int, boolean, Option<PartitionCoalescer>, Ordering<T>) - Static method in class org.apache.spark.api.r.RRDD
-
- coalesce(int, boolean, Option<PartitionCoalescer>, Ordering<T>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- coalesce(int, boolean, Option<PartitionCoalescer>, Ordering<T>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- coalesce(int, boolean, Option<PartitionCoalescer>, Ordering<T>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- coalesce(int, boolean, Option<PartitionCoalescer>, Ordering<T>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- coalesce(int, RDD<?>) - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
-
Runs the packing algorithm and returns an array of PartitionGroups that if possible are
load balanced and grouped by locality
- coalesce(int, boolean, Option<PartitionCoalescer>, Ordering<T>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- coalesce(int, boolean, Option<PartitionCoalescer>, Ordering<T>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- coalesce(int, boolean, Option<PartitionCoalescer>, Ordering<T>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- coalesce(int, RDD<?>) - Method in interface org.apache.spark.rdd.PartitionCoalescer
-
Coalesce the partitions of the given RDD.
- coalesce(int, boolean, Option<PartitionCoalescer>, Ordering<T>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- coalesce(int, boolean, Option<PartitionCoalescer>, Ordering<T>) - Method in class org.apache.spark.rdd.RDD
-
Return a new RDD that is reduced into numPartitions partitions.
- coalesce(int, boolean, Option<PartitionCoalescer>, Ordering<T>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- coalesce(int) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset that has exactly numPartitions partitions.
- coalesce(Column...) - Static method in class org.apache.spark.sql.functions
-
Returns the first column that is not null, or null if all inputs are null.
- coalesce(Seq<Column>) - Static method in class org.apache.spark.sql.functions
-
Returns the first column that is not null, or null if all inputs are null.
- coalesce$default$2() - Static method in class org.apache.spark.api.r.RRDD
-
- coalesce$default$2() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- coalesce$default$2() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- coalesce$default$2() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- coalesce$default$2() - Static method in class org.apache.spark.graphx.VertexRDD
-
- coalesce$default$2() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- coalesce$default$2() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- coalesce$default$2() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- coalesce$default$2() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- coalesce$default$2() - Static method in class org.apache.spark.rdd.UnionRDD
-
- coalesce$default$3() - Static method in class org.apache.spark.api.r.RRDD
-
- coalesce$default$3() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- coalesce$default$3() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- coalesce$default$3() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- coalesce$default$3() - Static method in class org.apache.spark.graphx.VertexRDD
-
- coalesce$default$3() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- coalesce$default$3() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- coalesce$default$3() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- coalesce$default$3() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- coalesce$default$3() - Static method in class org.apache.spark.rdd.UnionRDD
-
- coalesce$default$4(int, boolean, Option<PartitionCoalescer>) - Static method in class org.apache.spark.api.r.RRDD
-
- coalesce$default$4(int, boolean, Option<PartitionCoalescer>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- coalesce$default$4(int, boolean, Option<PartitionCoalescer>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- coalesce$default$4(int, boolean, Option<PartitionCoalescer>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- coalesce$default$4(int, boolean, Option<PartitionCoalescer>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- coalesce$default$4(int, boolean, Option<PartitionCoalescer>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- coalesce$default$4(int, boolean, Option<PartitionCoalescer>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- coalesce$default$4(int, boolean, Option<PartitionCoalescer>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- coalesce$default$4(int, boolean, Option<PartitionCoalescer>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- coalesce$default$4(int, boolean, Option<PartitionCoalescer>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- CoarseGrainedClusterMessages - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages
-
- CoarseGrainedClusterMessages.AddWebUIFilter - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.AddWebUIFilter(String, Map<String, String>, String) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.AddWebUIFilter
-
- CoarseGrainedClusterMessages.AddWebUIFilter$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.AddWebUIFilter$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.AddWebUIFilter$
-
- CoarseGrainedClusterMessages.GetExecutorLossReason - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.GetExecutorLossReason(String) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.GetExecutorLossReason
-
- CoarseGrainedClusterMessages.GetExecutorLossReason$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.GetExecutorLossReason$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.GetExecutorLossReason$
-
- CoarseGrainedClusterMessages.KillExecutors - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.KillExecutors(Seq<String>) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillExecutors
-
- CoarseGrainedClusterMessages.KillExecutors$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.KillExecutors$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillExecutors$
-
- CoarseGrainedClusterMessages.KillTask - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.KillTask(long, String, boolean) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillTask
-
- CoarseGrainedClusterMessages.KillTask$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.KillTask$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillTask$
-
- CoarseGrainedClusterMessages.LaunchTask - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.LaunchTask(org.apache.spark.util.SerializableBuffer) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.LaunchTask
-
- CoarseGrainedClusterMessages.LaunchTask$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.LaunchTask$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.LaunchTask$
-
- CoarseGrainedClusterMessages.RegisterClusterManager - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RegisterClusterManager(org.apache.spark.rpc.RpcEndpointRef) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterClusterManager
-
- CoarseGrainedClusterMessages.RegisterClusterManager$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RegisterClusterManager$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterClusterManager$
-
- CoarseGrainedClusterMessages.RegisteredExecutor$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RegisteredExecutor$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisteredExecutor$
-
- CoarseGrainedClusterMessages.RegisterExecutor - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RegisterExecutor(String, org.apache.spark.rpc.RpcEndpointRef, String, int, Map<String, String>) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutor
-
- CoarseGrainedClusterMessages.RegisterExecutor$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RegisterExecutor$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutor$
-
- CoarseGrainedClusterMessages.RegisterExecutorFailed - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RegisterExecutorFailed(String) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutorFailed
-
- CoarseGrainedClusterMessages.RegisterExecutorFailed$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RegisterExecutorFailed$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutorFailed$
-
- CoarseGrainedClusterMessages.RegisterExecutorResponse - Interface in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RemoveExecutor - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RemoveExecutor(String, org.apache.spark.scheduler.ExecutorLossReason) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RemoveExecutor
-
- CoarseGrainedClusterMessages.RemoveExecutor$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RemoveExecutor$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RemoveExecutor$
-
- CoarseGrainedClusterMessages.RequestExecutors - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RequestExecutors(int, int, Map<String, Object>) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RequestExecutors
-
- CoarseGrainedClusterMessages.RequestExecutors$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RequestExecutors$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RequestExecutors$
-
- CoarseGrainedClusterMessages.RetrieveLastAllocatedExecutorId$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RetrieveLastAllocatedExecutorId$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RetrieveLastAllocatedExecutorId$
-
- CoarseGrainedClusterMessages.RetrieveSparkProps$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RetrieveSparkProps$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RetrieveSparkProps$
-
- CoarseGrainedClusterMessages.ReviveOffers$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.ReviveOffers$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.ReviveOffers$
-
- CoarseGrainedClusterMessages.SetupDriver - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.SetupDriver(org.apache.spark.rpc.RpcEndpointRef) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.SetupDriver
-
- CoarseGrainedClusterMessages.SetupDriver$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.SetupDriver$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.SetupDriver$
-
- CoarseGrainedClusterMessages.Shutdown$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.Shutdown$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.Shutdown$
-
- CoarseGrainedClusterMessages.StatusUpdate - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.StatusUpdate(String, long, Enumeration.Value, org.apache.spark.util.SerializableBuffer) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StatusUpdate
-
- CoarseGrainedClusterMessages.StatusUpdate$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.StatusUpdate$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StatusUpdate$
-
- CoarseGrainedClusterMessages.StopDriver$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.StopDriver$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StopDriver$
-
- CoarseGrainedClusterMessages.StopExecutor$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.StopExecutor$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StopExecutor$
-
- CoarseGrainedClusterMessages.StopExecutors$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.StopExecutors$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StopExecutors$
-
- code() - Method in class org.apache.spark.mllib.feature.VocabWord
-
- CodegenMetrics - Class in org.apache.spark.metrics.source
-
:: Experimental ::
Metrics for code generation.
- CodegenMetrics() - Constructor for class org.apache.spark.metrics.source.CodegenMetrics
-
- codeLen() - Method in class org.apache.spark.mllib.feature.VocabWord
-
- coefficients() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- coefficients() - Method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- coefficients() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- coefficients() - Method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- coefficientStandardErrors() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionTrainingSummary
-
Standard error of estimated coefficients and intercept.
- coefficientStandardErrors() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
-
Standard error of estimated coefficients and intercept.
- cogroup(JavaPairRDD<K, W>, Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
-
For each key k in this or other, return a resulting RDD that contains a tuple with the
list of values for that key in this as well as other.
- cogroup(JavaPairRDD<K, W1>, JavaPairRDD<K, W2>, Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
-
For each key k in this or other1 or other2, return a resulting RDD that contains a
tuple with the list of values for that key in this, other1 and other2.
- cogroup(JavaPairRDD<K, W1>, JavaPairRDD<K, W2>, JavaPairRDD<K, W3>, Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
-
For each key k in this or other1 or other2 or other3,
return a resulting RDD that contains a tuple with the list of values
for that key in this, other1, other2 and other3.
- cogroup(JavaPairRDD<K, W>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
For each key k in this or other, return a resulting RDD that contains a tuple with the
list of values for that key in this as well as other.
- cogroup(JavaPairRDD<K, W1>, JavaPairRDD<K, W2>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
For each key k in this or other1 or other2, return a resulting RDD that contains a
tuple with the list of values for that key in this, other1 and other2.
- cogroup(JavaPairRDD<K, W1>, JavaPairRDD<K, W2>, JavaPairRDD<K, W3>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
For each key k in this or other1 or other2 or other3,
return a resulting RDD that contains a tuple with the list of values
for that key in this, other1, other2 and other3.
- cogroup(JavaPairRDD<K, W>, int) - Method in class org.apache.spark.api.java.JavaPairRDD
-
For each key k in this or other, return a resulting RDD that contains a tuple with the
list of values for that key in this as well as other.
- cogroup(JavaPairRDD<K, W1>, JavaPairRDD<K, W2>, int) - Method in class org.apache.spark.api.java.JavaPairRDD
-
For each key k in this or other1 or other2, return a resulting RDD that contains a
tuple with the list of values for that key in this, other1 and other2.
- cogroup(JavaPairRDD<K, W1>, JavaPairRDD<K, W2>, JavaPairRDD<K, W3>, int) - Method in class org.apache.spark.api.java.JavaPairRDD
-
For each key k in this or other1 or other2 or other3,
return a resulting RDD that contains a tuple with the list of values
for that key in this, other1, other2 and other3.
- cogroup(RDD<Tuple2<K, W1>>, RDD<Tuple2<K, W2>>, RDD<Tuple2<K, W3>>, Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
For each key k in this or other1 or other2 or other3,
return a resulting RDD that contains a tuple with the list of values
for that key in this, other1, other2 and other3.
- cogroup(RDD<Tuple2<K, W>>, Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
For each key k in this or other, return a resulting RDD that contains a tuple with the
list of values for that key in this as well as other.
- cogroup(RDD<Tuple2<K, W1>>, RDD<Tuple2<K, W2>>, Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
For each key k in this or other1 or other2, return a resulting RDD that contains a
tuple with the list of values for that key in this, other1 and other2.
- cogroup(RDD<Tuple2<K, W1>>, RDD<Tuple2<K, W2>>, RDD<Tuple2<K, W3>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
For each key k in this or other1 or other2 or other3,
return a resulting RDD that contains a tuple with the list of values
for that key in this, other1, other2 and other3.
- cogroup(RDD<Tuple2<K, W>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
For each key k in this or other, return a resulting RDD that contains a tuple with the
list of values for that key in this as well as other.
- cogroup(RDD<Tuple2<K, W1>>, RDD<Tuple2<K, W2>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
For each key k in this or other1 or other2, return a resulting RDD that contains a
tuple with the list of values for that key in this, other1 and other2.
- cogroup(RDD<Tuple2<K, W>>, int) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
For each key k in this or other, return a resulting RDD that contains a tuple with the
list of values for that key in this as well as other.
- cogroup(RDD<Tuple2<K, W1>>, RDD<Tuple2<K, W2>>, int) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
For each key k in this or other1 or other2, return a resulting RDD that contains a
tuple with the list of values for that key in this, other1 and other2.
- cogroup(RDD<Tuple2<K, W1>>, RDD<Tuple2<K, W2>>, RDD<Tuple2<K, W3>>, int) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
For each key k in this or other1 or other2 or other3,
return a resulting RDD that contains a tuple with the list of values
for that key in this, other1, other2 and other3.
- cogroup(KeyValueGroupedDataset<K, U>, Function3<K, Iterator<V>, Iterator<U>, TraversableOnce<R>>, Encoder<R>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
-
Applies the given function to each cogrouped data.
- cogroup(KeyValueGroupedDataset<K, U>, CoGroupFunction<K, V, U, R>, Encoder<R>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
-
Applies the given function to each cogrouped data.
- cogroup(JavaPairDStream<K, W>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying 'cogroup' between RDDs of this DStream and other DStream.
- cogroup(JavaPairDStream<K, W>, int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying 'cogroup' between RDDs of this DStream and other DStream.
- cogroup(JavaPairDStream<K, W>, Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying 'cogroup' between RDDs of this DStream and other DStream.
- cogroup(JavaPairDStream<K, W>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- cogroup(JavaPairDStream<K, W>, int) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- cogroup(JavaPairDStream<K, W>, Partitioner) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- cogroup(JavaPairDStream<K, W>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- cogroup(JavaPairDStream<K, W>, int) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- cogroup(JavaPairDStream<K, W>, Partitioner) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- cogroup(DStream<Tuple2<K, W>>, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying 'cogroup' between RDDs of this DStream and other DStream.
- cogroup(DStream<Tuple2<K, W>>, int, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying 'cogroup' between RDDs of this DStream and other DStream.
- cogroup(DStream<Tuple2<K, W>>, Partitioner, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying 'cogroup' between RDDs of this DStream and other DStream.
- CoGroupedRDD<K> - Class in org.apache.spark.rdd
-
:: DeveloperApi ::
A RDD that cogroups its parents.
- CoGroupedRDD(Seq<RDD<? extends Product2<K, ?>>>, Partitioner, ClassTag<K>) - Constructor for class org.apache.spark.rdd.CoGroupedRDD
-
- CoGroupFunction<K,V1,V2,R> - Interface in org.apache.spark.api.java.function
-
A function that returns zero or more output records from each grouping key and its values from 2
Datasets.
- col(String) - Method in class org.apache.spark.sql.Dataset
-
Selects column based on the column name and return it as a
Column.
- col(String) - Static method in class org.apache.spark.sql.functions
-
Returns a
Column based on the given column name.
- colIter() - Method in class org.apache.spark.ml.linalg.DenseMatrix
-
- colIter() - Method in interface org.apache.spark.ml.linalg.Matrix
-
Returns an iterator of column vectors.
- colIter() - Method in class org.apache.spark.ml.linalg.SparseMatrix
-
- colIter() - Method in class org.apache.spark.mllib.linalg.DenseMatrix
-
- colIter() - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Returns an iterator of column vectors.
- colIter() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
-
- collect() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- collect() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- collect() - Static method in class org.apache.spark.api.java.JavaRDD
-
- collect() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return an array that contains all of the elements in this RDD.
- collect() - Static method in class org.apache.spark.api.r.RRDD
-
- collect(PartialFunction<T, U>, ClassTag<U>) - Static method in class org.apache.spark.api.r.RRDD
-
- collect() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- collect(PartialFunction<T, U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- collect() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- collect() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- collect(PartialFunction<T, U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- collect() - Static method in class org.apache.spark.graphx.VertexRDD
-
- collect(PartialFunction<T, U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- collect() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- collect(PartialFunction<T, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- collect() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- collect(PartialFunction<T, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- collect() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- collect(PartialFunction<T, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- collect() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- collect(PartialFunction<T, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- collect() - Method in class org.apache.spark.rdd.RDD
-
Return an array that contains all of the elements in this RDD.
- collect(PartialFunction<T, U>, ClassTag<U>) - Method in class org.apache.spark.rdd.RDD
-
Return an RDD that contains all matching values by applying f.
- collect() - Static method in class org.apache.spark.rdd.UnionRDD
-
- collect(PartialFunction<T, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- collect() - Method in class org.apache.spark.sql.Dataset
-
Returns an array that contains all of
Rows in this Dataset.
- collect(PartialFunction<BaseType, B>) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- collect(PartialFunction<BaseType, B>) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- collect(PartialFunction<BaseType, B>) - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- collect(PartialFunction<A, B>, CanBuildFrom<Repr, B, That>) - Static method in class org.apache.spark.sql.types.StructType
-
- collect_list(Column) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns a list of objects with duplicates.
- collect_list(String) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns a list of objects with duplicates.
- collect_set(Column) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns a set of objects with duplicate elements eliminated.
- collect_set(String) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns a set of objects with duplicate elements eliminated.
- collectAsList() - Method in class org.apache.spark.sql.Dataset
-
Returns a Java list that contains all of
Rows in this Dataset.
- collectAsMap() - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return the key-value pairs in this RDD to the master as a Map.
- collectAsMap() - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Return the key-value pairs in this RDD to the master as a Map.
- collectAsync() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- collectAsync() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- collectAsync() - Static method in class org.apache.spark.api.java.JavaRDD
-
- collectAsync() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
The asynchronous version of collect, which returns a future for
retrieving an array containing all of the elements in this RDD.
- collectAsync() - Method in class org.apache.spark.rdd.AsyncRDDActions
-
Returns a future for retrieving all elements of this RDD.
- collectEdges(EdgeDirection) - Method in class org.apache.spark.graphx.GraphOps
-
Returns an RDD that contains for each vertex v its local edges,
i.e., the edges that are incident on v, in the user-specified direction.
- collectFirst(PartialFunction<BaseType, B>) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- collectFirst(PartialFunction<BaseType, B>) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- collectFirst(PartialFunction<BaseType, B>) - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- collectFirst(PartialFunction<A, B>) - Static method in class org.apache.spark.sql.types.StructType
-
- collectionAccumulator() - Method in class org.apache.spark.SparkContext
-
Create and register a CollectionAccumulator, which starts with empty list and accumulates
inputs by adding them into the list.
- collectionAccumulator(String) - Method in class org.apache.spark.SparkContext
-
Create and register a CollectionAccumulator, which starts with empty list and accumulates
inputs by adding them into the list.
- CollectionAccumulator<T> - Class in org.apache.spark.util
-
- CollectionAccumulator() - Constructor for class org.apache.spark.util.CollectionAccumulator
-
- CollectionsUtils - Class in org.apache.spark.util
-
- CollectionsUtils() - Constructor for class org.apache.spark.util.CollectionsUtils
-
- collectNeighborIds(EdgeDirection) - Method in class org.apache.spark.graphx.GraphOps
-
Collect the neighbor vertex ids for each vertex.
- collectNeighbors(EdgeDirection) - Method in class org.apache.spark.graphx.GraphOps
-
Collect the neighbor vertex attributes for each vertex.
- collectPartitions(int[]) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- collectPartitions(int[]) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- collectPartitions(int[]) - Static method in class org.apache.spark.api.java.JavaRDD
-
- collectPartitions(int[]) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return an array that contains all of the elements in a specific partition of this RDD.
- colPtrs() - Method in class org.apache.spark.ml.linalg.SparseMatrix
-
- colPtrs() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
-
- colsPerBlock() - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
-
- colStats(RDD<Vector>) - Static method in class org.apache.spark.mllib.stat.Statistics
-
Computes column-wise summary statistics for the input RDD[Vector].
- Column - Class in org.apache.spark.sql.catalog
-
A column in Spark, as returned by
listColumns method in
Catalog.
- Column(String, String, String, boolean, boolean, boolean) - Constructor for class org.apache.spark.sql.catalog.Column
-
- Column - Class in org.apache.spark.sql
-
A column that will be computed based on the data in a DataFrame.
- Column(Expression) - Constructor for class org.apache.spark.sql.Column
-
- Column(String) - Constructor for class org.apache.spark.sql.Column
-
- column(String) - Static method in class org.apache.spark.sql.functions
-
Returns a
Column based on the given column name.
- ColumnName - Class in org.apache.spark.sql
-
:: Experimental ::
A convenient class used for constructing schema.
- ColumnName(String) - Constructor for class org.apache.spark.sql.ColumnName
-
- ColumnPruner - Class in org.apache.spark.ml.feature
-
Utility transformer for removing temporary columns from a DataFrame.
- ColumnPruner(String, Set<String>) - Constructor for class org.apache.spark.ml.feature.ColumnPruner
-
- ColumnPruner(Set<String>) - Constructor for class org.apache.spark.ml.feature.ColumnPruner
-
- columns() - Method in class org.apache.spark.sql.Dataset
-
Returns all column names as an array.
- columnSimilarities() - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
-
Compute all cosine similarities between columns of this matrix using the brute-force
approach of computing normalized dot products.
- columnSimilarities() - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
-
Compute all cosine similarities between columns of this matrix using the brute-force
approach of computing normalized dot products.
- columnSimilarities(double) - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
-
Compute similarities between columns of this matrix using a sampling approach.
- columnsToPrune() - Method in class org.apache.spark.ml.feature.ColumnPruner
-
- combinations(int) - Static method in class org.apache.spark.sql.types.StructType
-
- combineByKey(Function<V, C>, Function2<C, V, C>, Function2<C, C, C>, Partitioner, boolean, Serializer) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Generic function to combine the elements for each key using a custom set of aggregation
functions.
- combineByKey(Function<V, C>, Function2<C, V, C>, Function2<C, C, C>, Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Generic function to combine the elements for each key using a custom set of aggregation
functions.
- combineByKey(Function<V, C>, Function2<C, V, C>, Function2<C, C, C>, int) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Simplified version of combineByKey that hash-partitions the output RDD and uses map-side
aggregation.
- combineByKey(Function<V, C>, Function2<C, V, C>, Function2<C, C, C>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Simplified version of combineByKey that hash-partitions the resulting RDD using the existing
partitioner/parallelism level and using map-side aggregation.
- combineByKey(Function1<V, C>, Function2<C, V, C>, Function2<C, C, C>, Partitioner, boolean, Serializer) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Generic function to combine the elements for each key using a custom set of aggregation
functions.
- combineByKey(Function1<V, C>, Function2<C, V, C>, Function2<C, C, C>, int) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Simplified version of combineByKeyWithClassTag that hash-partitions the output RDD.
- combineByKey(Function1<V, C>, Function2<C, V, C>, Function2<C, C, C>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Simplified version of combineByKeyWithClassTag that hash-partitions the resulting RDD using the
existing partitioner/parallelism level.
- combineByKey(Function<V, C>, Function2<C, V, C>, Function2<C, C, C>, Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Combine elements of each key in DStream's RDDs using custom function.
- combineByKey(Function<V, C>, Function2<C, V, C>, Function2<C, C, C>, Partitioner, boolean) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Combine elements of each key in DStream's RDDs using custom function.
- combineByKey(Function<V, C>, Function2<C, V, C>, Function2<C, C, C>, Partitioner) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- combineByKey(Function<V, C>, Function2<C, V, C>, Function2<C, C, C>, Partitioner, boolean) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- combineByKey(Function<V, C>, Function2<C, V, C>, Function2<C, C, C>, Partitioner) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- combineByKey(Function<V, C>, Function2<C, V, C>, Function2<C, C, C>, Partitioner, boolean) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- combineByKey(Function1<V, C>, Function2<C, V, C>, Function2<C, C, C>, Partitioner, boolean, ClassTag<C>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Combine elements of each key in DStream's RDDs using custom functions.
- combineByKeyWithClassTag(Function1<V, C>, Function2<C, V, C>, Function2<C, C, C>, Partitioner, boolean, Serializer, ClassTag<C>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
:: Experimental ::
Generic function to combine the elements for each key using a custom set of aggregation
functions.
- combineByKeyWithClassTag(Function1<V, C>, Function2<C, V, C>, Function2<C, C, C>, int, ClassTag<C>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
:: Experimental ::
Simplified version of combineByKeyWithClassTag that hash-partitions the output RDD.
- combineByKeyWithClassTag(Function1<V, C>, Function2<C, V, C>, Function2<C, C, C>, ClassTag<C>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
:: Experimental ::
Simplified version of combineByKeyWithClassTag that hash-partitions the resulting RDD using the
existing partitioner/parallelism level.
- combineCombinersByKey(Iterator<? extends Product2<K, C>>, TaskContext) - Method in class org.apache.spark.Aggregator
-
- combineValuesByKey(Iterator<? extends Product2<K, V>>, TaskContext) - Method in class org.apache.spark.Aggregator
-
- commit(Function0<Parsers.Parser<T>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- commitTask(OutputCommitter, TaskAttemptContext, int, int) - Static method in class org.apache.spark.mapred.SparkHadoopMapRedUtil
-
Commits a task output.
- commonHeaderNodes() - Static method in class org.apache.spark.ui.UIUtils
-
- companion() - Static method in class org.apache.spark.sql.types.StructType
-
- compare(PartitionGroup, PartitionGroup) - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
-
- compare(Option<PartitionGroup>, Option<PartitionGroup>) - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
-
- compare(Decimal) - Method in class org.apache.spark.sql.types.Decimal
-
- compare(RDDInfo) - Method in class org.apache.spark.storage.RDDInfo
-
- compareTo(A) - Static method in class org.apache.spark.sql.types.Decimal
-
- compareTo(A) - Static method in class org.apache.spark.storage.RDDInfo
-
- compareTo(SparkShutdownHook) - Method in class org.apache.spark.util.SparkShutdownHook
-
- Complete() - Static method in class org.apache.spark.sql.streaming.OutputMode
-
OutputMode in which all the rows in the streaming DataFrame/Dataset will be written
to the sink every time these is some updates.
- completed() - Method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
-
- completedIndices() - Method in class org.apache.spark.ui.jobs.UIData.StageUIData
-
- completedJobs() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- completedStageIndices() - Method in class org.apache.spark.ui.jobs.UIData.JobUIData
-
- completedStages() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- completedTasks() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
-
- completionTime() - Method in class org.apache.spark.scheduler.StageInfo
-
Time when all tasks in the stage completed or when the stage was cancelled.
- completionTime() - Method in class org.apache.spark.status.api.v1.JobData
-
- completionTime() - Method in class org.apache.spark.status.api.v1.StageData
-
- completionTime() - Method in class org.apache.spark.ui.jobs.UIData.JobUIData
-
- ComplexFutureAction<T> - Class in org.apache.spark
-
A
FutureAction for actions that could trigger multiple Spark jobs.
- ComplexFutureAction(Function1<JobSubmitter, Future<T>>) - Constructor for class org.apache.spark.ComplexFutureAction
-
- compose(Function1<A, T1>) - Static method in class org.apache.spark.sql.types.StructType
-
- compressed() - Static method in class org.apache.spark.ml.linalg.DenseVector
-
- compressed() - Static method in class org.apache.spark.ml.linalg.SparseVector
-
- compressed() - Method in interface org.apache.spark.ml.linalg.Vector
-
Returns a vector in either dense or sparse format, whichever uses less storage.
- compressed() - Static method in class org.apache.spark.mllib.linalg.DenseVector
-
- compressed() - Static method in class org.apache.spark.mllib.linalg.SparseVector
-
- compressed() - Method in interface org.apache.spark.mllib.linalg.Vector
-
Returns a vector in either dense or sparse format, whichever uses less storage.
- compressedInputStream(InputStream) - Method in interface org.apache.spark.io.CompressionCodec
-
- compressedInputStream(InputStream) - Method in class org.apache.spark.io.LZ4CompressionCodec
-
- compressedInputStream(InputStream) - Method in class org.apache.spark.io.LZFCompressionCodec
-
- compressedInputStream(InputStream) - Method in class org.apache.spark.io.SnappyCompressionCodec
-
- compressedOutputStream(OutputStream) - Method in interface org.apache.spark.io.CompressionCodec
-
- compressedOutputStream(OutputStream) - Method in class org.apache.spark.io.LZ4CompressionCodec
-
- compressedOutputStream(OutputStream) - Method in class org.apache.spark.io.LZFCompressionCodec
-
- compressedOutputStream(OutputStream) - Method in class org.apache.spark.io.SnappyCompressionCodec
-
- CompressionCodec - Interface in org.apache.spark.io
-
:: DeveloperApi ::
CompressionCodec allows the customization of choosing different compression implementations
to be used in block storage.
- compute(Partition, TaskContext) - Method in class org.apache.spark.api.r.BaseRRDD
-
- compute(Partition, TaskContext) - Static method in class org.apache.spark.api.r.RRDD
-
- compute(Partition, TaskContext) - Method in class org.apache.spark.graphx.EdgeRDD
-
- compute(Partition, TaskContext) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- compute(Partition, TaskContext) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- compute(Partition, TaskContext) - Method in class org.apache.spark.graphx.VertexRDD
-
Provides the RDD[(VertexId, VD)] equivalent output.
- compute(Vector, double, Vector) - Method in class org.apache.spark.mllib.optimization.Gradient
-
Compute the gradient and loss given the features of a single data point.
- compute(Vector, double, Vector, Vector) - Method in class org.apache.spark.mllib.optimization.Gradient
-
Compute the gradient and loss given the features of a single data point,
add the gradient to a provided vector to avoid creating new objects, and return loss.
- compute(Vector, double, Vector) - Method in class org.apache.spark.mllib.optimization.HingeGradient
-
- compute(Vector, double, Vector, Vector) - Method in class org.apache.spark.mllib.optimization.HingeGradient
-
- compute(Vector, Vector, double, int, double) - Method in class org.apache.spark.mllib.optimization.L1Updater
-
- compute(Vector, double, Vector) - Method in class org.apache.spark.mllib.optimization.LeastSquaresGradient
-
- compute(Vector, double, Vector, Vector) - Method in class org.apache.spark.mllib.optimization.LeastSquaresGradient
-
- compute(Vector, double, Vector, Vector) - Method in class org.apache.spark.mllib.optimization.LogisticGradient
-
- compute(Vector, Vector, double, int, double) - Method in class org.apache.spark.mllib.optimization.SimpleUpdater
-
- compute(Vector, Vector, double, int, double) - Method in class org.apache.spark.mllib.optimization.SquaredL2Updater
-
- compute(Vector, Vector, double, int, double) - Method in class org.apache.spark.mllib.optimization.Updater
-
Compute an updated value for weights given the gradient, stepSize, iteration number and
regularization parameter.
- compute(Partition, TaskContext) - Method in class org.apache.spark.rdd.CoGroupedRDD
-
- compute(Partition, TaskContext) - Method in class org.apache.spark.rdd.HadoopRDD
-
- compute(Partition, TaskContext) - Method in class org.apache.spark.rdd.JdbcRDD
-
- compute(Partition, TaskContext) - Method in class org.apache.spark.rdd.NewHadoopRDD
-
- compute(Partition, TaskContext) - Method in class org.apache.spark.rdd.PartitionPruningRDD
-
- compute(Partition, TaskContext) - Method in class org.apache.spark.rdd.RDD
-
:: DeveloperApi ::
Implemented by subclasses to compute a given partition.
- compute(Partition, TaskContext) - Method in class org.apache.spark.rdd.ShuffledRDD
-
- compute(Partition, TaskContext) - Method in class org.apache.spark.rdd.UnionRDD
-
- compute(Time) - Method in class org.apache.spark.streaming.api.java.JavaDStream
-
Generate an RDD for the given duration
- compute(Time) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- compute(Time) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Method that generates a RDD for the given Duration
- compute(Time) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- compute(Time) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- compute(Time) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- compute(Time) - Method in class org.apache.spark.streaming.dstream.ConstantInputDStream
-
- compute(Time) - Method in class org.apache.spark.streaming.dstream.DStream
-
Method that generates a RDD for the given time
- compute(Time) - Method in class org.apache.spark.streaming.dstream.ReceiverInputDStream
-
- computeColumnSummaryStatistics() - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
-
Computes column-wise summary statistics.
- computeCorrelation(RDD<Object>, RDD<Object>) - Static method in class org.apache.spark.mllib.stat.correlation.PearsonCorrelation
-
Compute the Pearson correlation for two datasets.
- computeCorrelation(RDD<Object>, RDD<Object>) - Static method in class org.apache.spark.mllib.stat.correlation.SpearmanCorrelation
-
Compute Spearman's correlation for two datasets.
- computeCorrelationMatrix(RDD<Vector>) - Static method in class org.apache.spark.mllib.stat.correlation.PearsonCorrelation
-
Compute the Pearson correlation matrix S, for the input matrix, where S(i, j) is the
correlation between column i and j.
- computeCorrelationMatrix(RDD<Vector>) - Static method in class org.apache.spark.mllib.stat.correlation.SpearmanCorrelation
-
Compute Spearman's correlation matrix S, for the input matrix, where S(i, j) is the
correlation between column i and j.
- computeCorrelationMatrixFromCovariance(Matrix) - Static method in class org.apache.spark.mllib.stat.correlation.PearsonCorrelation
-
Compute the Pearson correlation matrix from the covariance matrix.
- computeCorrelationWithMatrixImpl(RDD<Object>, RDD<Object>) - Static method in class org.apache.spark.mllib.stat.correlation.PearsonCorrelation
-
- computeCorrelationWithMatrixImpl(RDD<Object>, RDD<Object>) - Static method in class org.apache.spark.mllib.stat.correlation.SpearmanCorrelation
-
- computeCost(Dataset<?>) - Method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
Computes the sum of squared distances between the input points and their corresponding cluster
centers.
- computeCost(Dataset<?>) - Method in class org.apache.spark.ml.clustering.KMeansModel
-
Return the K-means cost (sum of squared distances of points to their nearest center) for this
model on the given data.
- computeCost(Vector) - Method in class org.apache.spark.mllib.clustering.BisectingKMeansModel
-
Computes the squared distance between the input point and the cluster center it belongs to.
- computeCost(RDD<Vector>) - Method in class org.apache.spark.mllib.clustering.BisectingKMeansModel
-
Computes the sum of squared distances between the input points and their corresponding cluster
centers.
- computeCost(JavaRDD<Vector>) - Method in class org.apache.spark.mllib.clustering.BisectingKMeansModel
-
Java-friendly version of computeCost().
- computeCost(RDD<Vector>) - Method in class org.apache.spark.mllib.clustering.KMeansModel
-
Return the K-means cost (sum of squared distances of points to their nearest center) for this
model on the given data.
- computeCovariance() - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
-
Computes the covariance matrix, treating each row as an observation.
- computeError(RDD<LabeledPoint>, DecisionTreeRegressionModel[], double[], Loss) - Static method in class org.apache.spark.ml.tree.impl.GradientBoostedTrees
-
Method to calculate error of the base learner for the gradient boosting calculation.
- computeError(org.apache.spark.mllib.tree.model.TreeEnsembleModel, RDD<LabeledPoint>) - Method in interface org.apache.spark.mllib.tree.loss.Loss
-
Method to calculate error of the base learner for the gradient boosting calculation.
- computeError(double, double) - Method in interface org.apache.spark.mllib.tree.loss.Loss
-
Method to calculate loss when the predictions are already known.
- computeFractionForSampleSize(int, long, boolean) - Static method in class org.apache.spark.util.random.SamplingUtils
-
Returns a sampling rate that guarantees a sample of size >= sampleSizeLowerBound 99.99% of
the time.
- computeGramianMatrix() - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
-
Computes the Gramian matrix A^T A.
- computeGramianMatrix() - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
-
Computes the Gramian matrix A^T A.
- computeInitialPredictionAndError(RDD<LabeledPoint>, double, DecisionTreeRegressionModel, Loss) - Static method in class org.apache.spark.ml.tree.impl.GradientBoostedTrees
-
Compute the initial predictions and errors for a dataset for the first
iteration of gradient boosting.
- computeInitialPredictionAndError(RDD<LabeledPoint>, double, DecisionTreeModel, Loss) - Static method in class org.apache.spark.mllib.tree.model.GradientBoostedTreesModel
-
:: DeveloperApi ::
Compute the initial predictions and errors for a dataset for the first
iteration of gradient boosting.
- computePreferredLocations(Seq<InputFormatInfo>) - Static method in class org.apache.spark.scheduler.InputFormatInfo
-
Computes the preferred locations based on input(s) and returned a location to block map.
- computePrincipalComponents(int) - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
-
Computes the top k principal components only.
- computePrincipalComponentsAndExplainedVariance(int) - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
-
Computes the top k principal components and a vector of proportions of
variance explained by each principal component.
- computeSVD(int, boolean, double) - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
-
Computes the singular value decomposition of this IndexedRowMatrix.
- computeSVD(int, boolean, double) - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
-
Computes singular value decomposition of this matrix.
- computeThresholdByKey(Map<K, AcceptanceResult>, Map<K, Object>) - Static method in class org.apache.spark.util.random.StratifiedSamplingUtils
-
Given the result returned by getCounts, determine the threshold for accepting items to
generate exact sample size.
- concat(Column...) - Static method in class org.apache.spark.sql.functions
-
Concatenates multiple input string columns together into a single string column.
- concat(Seq<Column>) - Static method in class org.apache.spark.sql.functions
-
Concatenates multiple input string columns together into a single string column.
- concat_ws(String, Column...) - Static method in class org.apache.spark.sql.functions
-
Concatenates multiple input string columns together into a single string column,
using the given separator.
- concat_ws(String, Seq<Column>) - Static method in class org.apache.spark.sql.functions
-
Concatenates multiple input string columns together into a single string column,
using the given separator.
- conf() - Method in class org.apache.spark.SparkEnv
-
- conf() - Method in class org.apache.spark.sql.SparkSession
-
Runtime configuration interface for Spark.
- confidence() - Method in class org.apache.spark.mllib.fpm.AssociationRules.Rule
-
Returns the confidence of the rule.
- confidence() - Method in class org.apache.spark.partial.BoundedDouble
-
- confidence() - Method in class org.apache.spark.util.sketch.CountMinSketch
-
- config(String, String) - Method in class org.apache.spark.sql.SparkSession.Builder
-
Sets a config option.
- config(String, long) - Method in class org.apache.spark.sql.SparkSession.Builder
-
Sets a config option.
- config(String, double) - Method in class org.apache.spark.sql.SparkSession.Builder
-
Sets a config option.
- config(String, boolean) - Method in class org.apache.spark.sql.SparkSession.Builder
-
Sets a config option.
- config(SparkConf) - Method in class org.apache.spark.sql.SparkSession.Builder
-
Sets a list of config options based on the given SparkConf.
- config() - Method in class org.apache.spark.streaming.kafka.KafkaCluster
-
- ConfigEntryWithDefault<T> - Class in org.apache.spark.internal.config
-
- ConfigEntryWithDefault(String, T, Function1<String, T>, Function1<T, String>, String, boolean) - Constructor for class org.apache.spark.internal.config.ConfigEntryWithDefault
-
- ConfigHelpers - Class in org.apache.spark.internal.config
-
- ConfigHelpers() - Constructor for class org.apache.spark.internal.config.ConfigHelpers
-
- configTestLog4j(String) - Static method in class org.apache.spark.util.Utils
-
config a log4j properties used for testsuite
- configuration() - Method in class org.apache.spark.scheduler.InputFormatInfo
-
- CONFIGURATION_INSTANTIATION_LOCK() - Static method in class org.apache.spark.rdd.HadoopRDD
-
Configuration's constructor is not threadsafe (see SPARK-1097 and HADOOP-10456).
- CONFIGURATION_INSTANTIATION_LOCK() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
Configuration's constructor is not threadsafe (see SPARK-1097 and HADOOP-10456).
- configureJobPropertiesForStorageHandler(TableDesc, JobConf, boolean) - Static method in class org.apache.spark.sql.hive.HiveTableUtil
-
- confusionMatrix() - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
-
Returns confusion matrix:
predicted classes are in columns,
they are ordered by class label ascending,
as in "labels"
- connect(String, int) - Method in class org.apache.spark.streaming.kafka.KafkaCluster
-
- connectedComponents() - Method in class org.apache.spark.graphx.GraphOps
-
Compute the connected component membership of each vertex and return a graph with the vertex
value containing the lowest vertex id in the connected component containing that vertex.
- connectedComponents(int) - Method in class org.apache.spark.graphx.GraphOps
-
Compute the connected component membership of each vertex and return a graph with the vertex
value containing the lowest vertex id in the connected component containing that vertex.
- ConnectedComponents - Class in org.apache.spark.graphx.lib
-
Connected components algorithm.
- ConnectedComponents() - Constructor for class org.apache.spark.graphx.lib.ConnectedComponents
-
- connectLeader(String, int) - Method in class org.apache.spark.streaming.kafka.KafkaCluster
-
- consequent() - Method in class org.apache.spark.mllib.fpm.AssociationRules.Rule
-
- ConstantInputDStream<T> - Class in org.apache.spark.streaming.dstream
-
An input stream that always returns the same RDD on each time step.
- ConstantInputDStream(StreamingContext, RDD<T>, ClassTag<T>) - Constructor for class org.apache.spark.streaming.dstream.ConstantInputDStream
-
- constraints() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- constraints() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- constraints() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- constructTree(org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0.NodeData[]) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$
-
Given a list of nodes from a tree, construct the tree.
- constructTrees(RDD<org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0.NodeData>) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$
-
- constructURIForAuthentication(URI, org.apache.spark.SecurityManager) - Static method in class org.apache.spark.util.Utils
-
Construct a URI container information used for authentication.
- contains(Param<?>) - Method in class org.apache.spark.ml.param.ParamMap
-
Checks whether a parameter is explicitly specified.
- contains(String) - Method in class org.apache.spark.SparkConf
-
Does the configuration contain a given parameter?
- contains(Object) - Method in class org.apache.spark.sql.Column
-
Contains the other element.
- contains(String) - Method in class org.apache.spark.sql.types.Metadata
-
Tests whether this Metadata contains a binding for a key.
- contains(A1) - Static method in class org.apache.spark.sql.types.StructType
-
- containsBlock(BlockId) - Method in class org.apache.spark.storage.StorageStatus
-
Return whether the given block is stored in this block manager in O(1) time.
- containsCachedMetadata(String) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- containsChild() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- containsChild() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- containsChild() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- containsNull() - Method in class org.apache.spark.sql.types.ArrayType
-
- containsSlice(GenSeq<B>) - Static method in class org.apache.spark.sql.types.StructType
-
- contentType() - Method in class org.apache.spark.ui.JettyUtils.ServletParams
-
- context() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- context() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- context() - Static method in class org.apache.spark.api.java.JavaRDD
-
- context() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
- context() - Static method in class org.apache.spark.api.r.RRDD
-
- context() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- context() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- context() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- context() - Static method in class org.apache.spark.graphx.VertexRDD
-
- context() - Method in class org.apache.spark.InterruptibleIterator
-
- context(SQLContext) - Static method in class org.apache.spark.ml.r.RWrappers
-
- context(SQLContext) - Method in class org.apache.spark.ml.util.MLReader
-
- context(SQLContext) - Method in class org.apache.spark.ml.util.MLWriter
-
- context() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- context() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- context() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- context() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- context() - Method in class org.apache.spark.rdd.RDD
-
- context() - Static method in class org.apache.spark.rdd.UnionRDD
-
- context() - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- context() - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
- context() - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- context() - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- context() - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- context() - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- context() - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- context() - Method in class org.apache.spark.streaming.dstream.DStream
-
Return the StreamingContext associated with this DStream
- Continuous() - Static method in class org.apache.spark.mllib.tree.configuration.FeatureType
-
- ContinuousSplit - Class in org.apache.spark.ml.tree
-
Split which tests a continuous feature.
- conv(Column, int, int) - Static method in class org.apache.spark.sql.functions
-
Convert a number in a string column from one base to another.
- CONVERT_METASTORE_ORC() - Static method in class org.apache.spark.sql.hive.HiveUtils
-
- CONVERT_METASTORE_PARQUET() - Static method in class org.apache.spark.sql.hive.HiveUtils
-
- CONVERT_METASTORE_PARQUET_WITH_SCHEMA_MERGING() - Static method in class org.apache.spark.sql.hive.HiveUtils
-
- convertMatrixColumnsFromML(Dataset<?>, String...) - Static method in class org.apache.spark.mllib.util.MLUtils
-
Converts matrix columns in an input Dataset to the
Matrix
type from the new
Matrix type under the
spark.ml package.
- convertMatrixColumnsFromML(Dataset<?>, Seq<String>) - Static method in class org.apache.spark.mllib.util.MLUtils
-
Converts matrix columns in an input Dataset to the
Matrix
type from the new
Matrix type under the
spark.ml package.
- convertMatrixColumnsToML(Dataset<?>, String...) - Static method in class org.apache.spark.mllib.util.MLUtils
-
Converts Matrix columns in an input Dataset from the
Matrix
type to the new
Matrix type under the
spark.ml package.
- convertMatrixColumnsToML(Dataset<?>, Seq<String>) - Static method in class org.apache.spark.mllib.util.MLUtils
-
Converts Matrix columns in an input Dataset from the
Matrix
type to the new
Matrix type under the
spark.ml package.
- convertToCanonicalEdges(Function2<ED, ED, ED>) - Method in class org.apache.spark.graphx.GraphOps
-
Convert bi-directional edges into uni-directional ones.
- convertToTimeUnit(long, TimeUnit) - Static method in class org.apache.spark.streaming.ui.UIUtils
-
Convert milliseconds to the specified unit.
- convertVectorColumnsFromML(Dataset<?>, String...) - Static method in class org.apache.spark.mllib.util.MLUtils
-
Converts vector columns in an input Dataset to the
Vector
type from the new
Vector type under the
spark.ml package.
- convertVectorColumnsFromML(Dataset<?>, Seq<String>) - Static method in class org.apache.spark.mllib.util.MLUtils
-
Converts vector columns in an input Dataset to the
Vector
type from the new
Vector type under the
spark.ml package.
- convertVectorColumnsToML(Dataset<?>, String...) - Static method in class org.apache.spark.mllib.util.MLUtils
-
Converts vector columns in an input Dataset from the
Vector
type to the new
Vector type under the
spark.ml package.
- convertVectorColumnsToML(Dataset<?>, Seq<String>) - Static method in class org.apache.spark.mllib.util.MLUtils
-
Converts vector columns in an input Dataset from the
Vector
type to the new
Vector type under the
spark.ml package.
- CoordinateMatrix - Class in org.apache.spark.mllib.linalg.distributed
-
Represents a matrix in coordinate format.
- CoordinateMatrix(RDD<MatrixEntry>, long, long) - Constructor for class org.apache.spark.mllib.linalg.distributed.CoordinateMatrix
-
- CoordinateMatrix(RDD<MatrixEntry>) - Constructor for class org.apache.spark.mllib.linalg.distributed.CoordinateMatrix
-
Alternative constructor leaving matrix dimensions to be determined automatically.
- copy(ParamMap) - Method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- copy(ParamMap) - Method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.classification.GBTClassifier
-
- copy(ParamMap) - Method in class org.apache.spark.ml.classification.LogisticRegression
-
- copy(ParamMap) - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- copy(ParamMap) - Method in class org.apache.spark.ml.classification.NaiveBayes
-
- copy(ParamMap) - Method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.classification.OneVsRest
-
- copy(ParamMap) - Method in class org.apache.spark.ml.classification.OneVsRestModel
-
- copy(ParamMap) - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- copy(ParamMap) - Method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- copy(ParamMap) - Method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.clustering.GaussianMixture
-
- copy(ParamMap) - Method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.clustering.KMeans
-
- copy(ParamMap) - Method in class org.apache.spark.ml.clustering.KMeansModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.clustering.LDA
-
- copy(ParamMap) - Method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.Estimator
-
- copy(ParamMap) - Method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- copy(ParamMap) - Method in class org.apache.spark.ml.evaluation.Evaluator
-
- copy(ParamMap) - Method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
- copy(ParamMap) - Method in class org.apache.spark.ml.evaluation.RegressionEvaluator
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.Binarizer
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.Bucketizer
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.ChiSqSelector
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.ColumnPruner
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.CountVectorizer
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- copy(ParamMap) - Static method in class org.apache.spark.ml.feature.DCT
-
- copy(ParamMap) - Static method in class org.apache.spark.ml.feature.ElementwiseProduct
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.HashingTF
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.IDF
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.IDFModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.IndexToString
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.Interaction
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.MaxAbsScaler
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.MinMaxScaler
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- copy(ParamMap) - Static method in class org.apache.spark.ml.feature.NGram
-
- copy(ParamMap) - Static method in class org.apache.spark.ml.feature.Normalizer
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.OneHotEncoder
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.PCA
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.PCAModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.PolynomialExpansion
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.RegexTokenizer
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.RFormula
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.RFormulaModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.SQLTransformer
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.StandardScaler
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.StandardScalerModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.StopWordsRemover
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.StringIndexer
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.StringIndexerModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.Tokenizer
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.VectorAssembler
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.VectorAttributeRewriter
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.VectorIndexer
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.VectorSlicer
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.Word2Vec
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.Word2VecModel
-
- copy(Vector, Vector) - Static method in class org.apache.spark.ml.linalg.BLAS
-
y = x
- copy() - Method in class org.apache.spark.ml.linalg.DenseMatrix
-
- copy() - Method in class org.apache.spark.ml.linalg.DenseVector
-
- copy() - Method in interface org.apache.spark.ml.linalg.Matrix
-
Get a deep copy of the matrix.
- copy() - Method in class org.apache.spark.ml.linalg.SparseMatrix
-
- copy() - Method in class org.apache.spark.ml.linalg.SparseVector
-
- copy() - Method in interface org.apache.spark.ml.linalg.Vector
-
Makes a deep copy of this vector.
- copy(ParamMap) - Method in class org.apache.spark.ml.Model
-
- copy() - Method in class org.apache.spark.ml.param.ParamMap
-
Creates a copy of this param map.
- copy(ParamMap) - Method in interface org.apache.spark.ml.param.Params
-
Creates a copy of this instance with the same UID and some extra params.
- copy(ParamMap) - Method in class org.apache.spark.ml.Pipeline
-
- copy(ParamMap) - Method in class org.apache.spark.ml.PipelineModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.PipelineStage
-
- copy(ParamMap) - Method in class org.apache.spark.ml.Predictor
-
- copy(ParamMap) - Method in class org.apache.spark.ml.recommendation.ALS
-
- copy(ParamMap) - Method in class org.apache.spark.ml.recommendation.ALSModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- copy(ParamMap) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- copy(ParamMap) - Method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.regression.GBTRegressor
-
- copy(ParamMap) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- copy(ParamMap) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.regression.IsotonicRegression
-
- copy(ParamMap) - Method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.regression.LinearRegression
-
- copy(ParamMap) - Method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- copy(ParamMap) - Method in class org.apache.spark.ml.Transformer
-
- copy(ParamMap) - Method in class org.apache.spark.ml.tuning.CrossValidator
-
- copy(ParamMap) - Method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- copy(ParamMap) - Method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
-
- copy(ParamMap) - Method in class org.apache.spark.ml.UnaryTransformer
-
- copy(Vector, Vector) - Static method in class org.apache.spark.mllib.linalg.BLAS
-
y = x
- copy() - Method in class org.apache.spark.mllib.linalg.DenseMatrix
-
- copy() - Method in class org.apache.spark.mllib.linalg.DenseVector
-
- copy() - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Get a deep copy of the matrix.
- copy() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
-
- copy() - Method in class org.apache.spark.mllib.linalg.SparseVector
-
- copy() - Method in interface org.apache.spark.mllib.linalg.Vector
-
Makes a deep copy of this vector.
- copy() - Method in class org.apache.spark.mllib.random.ExponentialGenerator
-
- copy() - Method in class org.apache.spark.mllib.random.GammaGenerator
-
- copy() - Method in class org.apache.spark.mllib.random.LogNormalGenerator
-
- copy() - Method in class org.apache.spark.mllib.random.PoissonGenerator
-
- copy() - Method in interface org.apache.spark.mllib.random.RandomDataGenerator
-
Returns a copy of the RandomDataGenerator with a new instance of the rng object used in the
class when applicable for non-locking concurrent usage.
- copy() - Method in class org.apache.spark.mllib.random.StandardNormalGenerator
-
- copy() - Method in class org.apache.spark.mllib.random.UniformGenerator
-
- copy() - Method in class org.apache.spark.mllib.random.WeibullGenerator
-
- copy() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
Returns a shallow copy of this instance.
- copy(Kryo, T) - Static method in class org.apache.spark.serializer.JavaIterableWrapperSerializer
-
- copy() - Method in interface org.apache.spark.sql.Row
-
Make a copy of the current
Row object.
- copy() - Method in class org.apache.spark.util.AccumulatorV2
-
Creates a new copy of this accumulator.
- copy() - Method in class org.apache.spark.util.CollectionAccumulator
-
- copy() - Method in class org.apache.spark.util.DoubleAccumulator
-
- copy() - Method in class org.apache.spark.util.LegacyAccumulatorWrapper
-
- copy() - Method in class org.apache.spark.util.LongAccumulator
-
- copy() - Method in class org.apache.spark.util.StatCounter
-
Clone this StatCounter
- copyAndReset() - Method in class org.apache.spark.util.AccumulatorV2
-
Creates a new copy of this accumulator, which is zero value.
- copyAndReset() - Method in class org.apache.spark.util.CollectionAccumulator
-
- copyStream(InputStream, OutputStream, boolean, boolean) - Static method in class org.apache.spark.util.Utils
-
Copy all data from an InputStream to an OutputStream.
- copyToArray(Object, int) - Static method in class org.apache.spark.sql.types.StructType
-
- copyToArray(Object) - Static method in class org.apache.spark.sql.types.StructType
-
- copyToArray(Object, int, int) - Static method in class org.apache.spark.sql.types.StructType
-
- copyToBuffer(Buffer<B>) - Static method in class org.apache.spark.sql.types.StructType
-
- copyValues(T, ParamMap) - Method in interface org.apache.spark.ml.param.Params
-
Copies param values from this instance to another instance for params shared by them.
- cores() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutor
-
- coresGranted() - Method in class org.apache.spark.status.api.v1.ApplicationInfo
-
- coresPerExecutor() - Method in class org.apache.spark.status.api.v1.ApplicationInfo
-
- corr(RDD<Object>, RDD<Object>, String) - Static method in class org.apache.spark.mllib.stat.correlation.Correlations
-
- corr(RDD<Vector>) - Static method in class org.apache.spark.mllib.stat.Statistics
-
Compute the Pearson correlation matrix for the input RDD of Vectors.
- corr(RDD<Vector>, String) - Static method in class org.apache.spark.mllib.stat.Statistics
-
Compute the correlation matrix for the input RDD of Vectors using the specified method.
- corr(RDD<Object>, RDD<Object>) - Static method in class org.apache.spark.mllib.stat.Statistics
-
Compute the Pearson correlation for the input RDDs.
- corr(JavaRDD<Double>, JavaRDD<Double>) - Static method in class org.apache.spark.mllib.stat.Statistics
-
Java-friendly version of corr()
- corr(RDD<Object>, RDD<Object>, String) - Static method in class org.apache.spark.mllib.stat.Statistics
-
Compute the correlation for the input RDDs using the specified method.
- corr(JavaRDD<Double>, JavaRDD<Double>, String) - Static method in class org.apache.spark.mllib.stat.Statistics
-
Java-friendly version of corr()
- corr(String, String, String) - Method in class org.apache.spark.sql.DataFrameStatFunctions
-
Calculates the correlation of two columns of a DataFrame.
- corr(String, String) - Method in class org.apache.spark.sql.DataFrameStatFunctions
-
Calculates the Pearson Correlation Coefficient of two columns of a DataFrame.
- corr(Column, Column) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the Pearson Correlation Coefficient for two columns.
- corr(String, String) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the Pearson Correlation Coefficient for two columns.
- CorrelationNames - Class in org.apache.spark.mllib.stat.correlation
-
Maintains supported and default correlation names.
- CorrelationNames() - Constructor for class org.apache.spark.mllib.stat.correlation.CorrelationNames
-
- Correlations - Class in org.apache.spark.mllib.stat.correlation
-
Delegates computation to the specific correlation object based on the input method name.
- Correlations() - Constructor for class org.apache.spark.mllib.stat.correlation.Correlations
-
- corresponds(GenSeq<B>, Function2<A, B, Object>) - Static method in class org.apache.spark.sql.types.StructType
-
- corrMatrix(RDD<Vector>, String) - Static method in class org.apache.spark.mllib.stat.correlation.Correlations
-
- cos(Column) - Static method in class org.apache.spark.sql.functions
-
Computes the cosine of the given value.
- cos(String) - Static method in class org.apache.spark.sql.functions
-
Computes the cosine of the given column.
- cosh(Column) - Static method in class org.apache.spark.sql.functions
-
Computes the hyperbolic cosine of the given value.
- cosh(String) - Static method in class org.apache.spark.sql.functions
-
Computes the hyperbolic cosine of the given column.
- count() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- count() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- count() - Static method in class org.apache.spark.api.java.JavaRDD
-
- count() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return the number of elements in the RDD.
- count() - Static method in class org.apache.spark.api.r.RRDD
-
- count() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- count() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
The number of edges in the RDD.
- count() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
The number of vertices in the RDD.
- count() - Static method in class org.apache.spark.graphx.VertexRDD
-
- count() - Method in class org.apache.spark.ml.regression.AFTAggregator
-
- count() - Method in class org.apache.spark.ml.regression.LeastSquaresAggregator
-
- count() - Method in class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
-
Sample size.
- count() - Method in interface org.apache.spark.mllib.stat.MultivariateStatisticalSummary
-
Sample size.
- count() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- count() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- count() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- count() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- count() - Method in class org.apache.spark.rdd.RDD
-
Return the number of elements in the RDD.
- count() - Static method in class org.apache.spark.rdd.UnionRDD
-
- count() - Method in class org.apache.spark.sql.Dataset
-
Returns the number of rows in the Dataset.
- count(MapFunction<T, Object>) - Static method in class org.apache.spark.sql.expressions.javalang.typed
-
Count aggregate function.
- count(Function1<IN, Object>) - Static method in class org.apache.spark.sql.expressions.scalalang.typed
-
Count aggregate function.
- count(Column) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the number of items in a group.
- count(String) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the number of items in a group.
- count() - Method in class org.apache.spark.sql.KeyValueGroupedDataset
-
Returns a
Dataset that contains a tuple with each key and the number of items present
for that key.
- count() - Method in class org.apache.spark.sql.RelationalGroupedDataset
-
Count the number of rows for each group.
- count(Function1<A, Object>) - Static method in class org.apache.spark.sql.types.StructType
-
- count() - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- count() - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD has a single element generated by counting each RDD
of this DStream.
- count() - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- count() - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- count() - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- count() - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- count() - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- count() - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream in which each RDD has a single element generated by counting each RDD
of this DStream.
- count() - Method in class org.apache.spark.streaming.kafka.OffsetRange
-
Number of messages this OffsetRange refers to
- count() - Method in class org.apache.spark.util.DoubleAccumulator
-
Returns the number of elements added to the accumulator.
- count() - Method in class org.apache.spark.util.LongAccumulator
-
Returns the number of elements added to the accumulator.
- count() - Method in class org.apache.spark.util.StatCounter
-
- countApprox(long, double) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- countApprox(long) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- countApprox(long, double) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- countApprox(long) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- countApprox(long, double) - Static method in class org.apache.spark.api.java.JavaRDD
-
- countApprox(long) - Static method in class org.apache.spark.api.java.JavaRDD
-
- countApprox(long, double) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Approximate version of count() that returns a potentially incomplete result
within a timeout, even if not all tasks have finished.
- countApprox(long) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Approximate version of count() that returns a potentially incomplete result
within a timeout, even if not all tasks have finished.
- countApprox(long, double) - Static method in class org.apache.spark.api.r.RRDD
-
- countApprox(long, double) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- countApprox(long, double) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- countApprox(long, double) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- countApprox(long, double) - Static method in class org.apache.spark.graphx.VertexRDD
-
- countApprox(long, double) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- countApprox(long, double) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- countApprox(long, double) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- countApprox(long, double) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- countApprox(long, double) - Method in class org.apache.spark.rdd.RDD
-
Approximate version of count() that returns a potentially incomplete result
within a timeout, even if not all tasks have finished.
- countApprox(long, double) - Static method in class org.apache.spark.rdd.UnionRDD
-
- countApprox$default$2() - Static method in class org.apache.spark.api.r.RRDD
-
- countApprox$default$2() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- countApprox$default$2() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- countApprox$default$2() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- countApprox$default$2() - Static method in class org.apache.spark.graphx.VertexRDD
-
- countApprox$default$2() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- countApprox$default$2() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- countApprox$default$2() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- countApprox$default$2() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- countApprox$default$2() - Static method in class org.apache.spark.rdd.UnionRDD
-
- countApproxDistinct(double) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- countApproxDistinct(double) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- countApproxDistinct(double) - Static method in class org.apache.spark.api.java.JavaRDD
-
- countApproxDistinct(double) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return approximate number of distinct elements in the RDD.
- countApproxDistinct(int, int) - Static method in class org.apache.spark.api.r.RRDD
-
- countApproxDistinct(double) - Static method in class org.apache.spark.api.r.RRDD
-
- countApproxDistinct(int, int) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- countApproxDistinct(double) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- countApproxDistinct(int, int) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- countApproxDistinct(double) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- countApproxDistinct(int, int) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- countApproxDistinct(double) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- countApproxDistinct(int, int) - Static method in class org.apache.spark.graphx.VertexRDD
-
- countApproxDistinct(double) - Static method in class org.apache.spark.graphx.VertexRDD
-
- countApproxDistinct(int, int) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- countApproxDistinct(double) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- countApproxDistinct(int, int) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- countApproxDistinct(double) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- countApproxDistinct(int, int) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- countApproxDistinct(double) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- countApproxDistinct(int, int) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- countApproxDistinct(double) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- countApproxDistinct(int, int) - Method in class org.apache.spark.rdd.RDD
-
Return approximate number of distinct elements in the RDD.
- countApproxDistinct(double) - Method in class org.apache.spark.rdd.RDD
-
Return approximate number of distinct elements in the RDD.
- countApproxDistinct(int, int) - Static method in class org.apache.spark.rdd.UnionRDD
-
- countApproxDistinct(double) - Static method in class org.apache.spark.rdd.UnionRDD
-
- countApproxDistinct$default$1() - Static method in class org.apache.spark.api.r.RRDD
-
- countApproxDistinct$default$1() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- countApproxDistinct$default$1() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- countApproxDistinct$default$1() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- countApproxDistinct$default$1() - Static method in class org.apache.spark.graphx.VertexRDD
-
- countApproxDistinct$default$1() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- countApproxDistinct$default$1() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- countApproxDistinct$default$1() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- countApproxDistinct$default$1() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- countApproxDistinct$default$1() - Static method in class org.apache.spark.rdd.UnionRDD
-
- countApproxDistinctByKey(double, Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return approximate number of distinct values for each key in this RDD.
- countApproxDistinctByKey(double, int) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return approximate number of distinct values for each key in this RDD.
- countApproxDistinctByKey(double) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return approximate number of distinct values for each key in this RDD.
- countApproxDistinctByKey(int, int, Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Return approximate number of distinct values for each key in this RDD.
- countApproxDistinctByKey(double, Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Return approximate number of distinct values for each key in this RDD.
- countApproxDistinctByKey(double, int) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Return approximate number of distinct values for each key in this RDD.
- countApproxDistinctByKey(double) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Return approximate number of distinct values for each key in this RDD.
- countAsync() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- countAsync() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- countAsync() - Static method in class org.apache.spark.api.java.JavaRDD
-
- countAsync() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
The asynchronous version of count, which returns a
future for counting the number of elements in this RDD.
- countAsync() - Method in class org.apache.spark.rdd.AsyncRDDActions
-
Returns a future for counting the number of elements in the RDD.
- countByKey() - Method in class org.apache.spark.api.java.JavaPairRDD
-
Count the number of elements for each key, and return the result to the master as a Map.
- countByKey() - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Count the number of elements for each key, collecting the results to a local Map.
- countByKeyApprox(long) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Approximate version of countByKey that can return a partial result if it does
not finish within a timeout.
- countByKeyApprox(long, double) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Approximate version of countByKey that can return a partial result if it does
not finish within a timeout.
- countByKeyApprox(long, double) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Approximate version of countByKey that can return a partial result if it does
not finish within a timeout.
- countByValue() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- countByValue() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- countByValue() - Static method in class org.apache.spark.api.java.JavaRDD
-
- countByValue() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return the count of each unique value in this RDD as a map of (value, count) pairs.
- countByValue(Ordering<T>) - Static method in class org.apache.spark.api.r.RRDD
-
- countByValue(Ordering<T>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- countByValue(Ordering<T>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- countByValue(Ordering<T>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- countByValue(Ordering<T>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- countByValue(Ordering<T>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- countByValue(Ordering<T>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- countByValue(Ordering<T>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- countByValue(Ordering<T>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- countByValue(Ordering<T>) - Method in class org.apache.spark.rdd.RDD
-
Return the count of each unique value in this RDD as a local map of (value, count) pairs.
- countByValue(Ordering<T>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- countByValue() - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- countByValue(int) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- countByValue() - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD contains the counts of each distinct value in
each RDD of this DStream.
- countByValue(int) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD contains the counts of each distinct value in
each RDD of this DStream.
- countByValue() - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- countByValue(int) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- countByValue() - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- countByValue(int) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- countByValue() - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- countByValue(int) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- countByValue() - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- countByValue(int) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- countByValue() - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- countByValue(int) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- countByValue(int, Ordering<T>) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream in which each RDD contains the counts of each distinct value in
each RDD of this DStream.
- countByValue$default$1() - Static method in class org.apache.spark.api.r.RRDD
-
- countByValue$default$1() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- countByValue$default$1() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- countByValue$default$1() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- countByValue$default$1() - Static method in class org.apache.spark.graphx.VertexRDD
-
- countByValue$default$1() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- countByValue$default$1() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- countByValue$default$1() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- countByValue$default$1() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- countByValue$default$1() - Static method in class org.apache.spark.rdd.UnionRDD
-
- countByValueAndWindow(Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- countByValueAndWindow(Duration, Duration, int) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- countByValueAndWindow(Duration, Duration) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD contains the count of distinct elements in
RDDs in a sliding window over this DStream.
- countByValueAndWindow(Duration, Duration, int) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD contains the count of distinct elements in
RDDs in a sliding window over this DStream.
- countByValueAndWindow(Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- countByValueAndWindow(Duration, Duration, int) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- countByValueAndWindow(Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- countByValueAndWindow(Duration, Duration, int) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- countByValueAndWindow(Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- countByValueAndWindow(Duration, Duration, int) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- countByValueAndWindow(Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- countByValueAndWindow(Duration, Duration, int) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- countByValueAndWindow(Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- countByValueAndWindow(Duration, Duration, int) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- countByValueAndWindow(Duration, Duration, int, Ordering<T>) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream in which each RDD contains the count of distinct elements in
RDDs in a sliding window over this DStream.
- countByValueApprox(long, double) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- countByValueApprox(long) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- countByValueApprox(long, double) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- countByValueApprox(long) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- countByValueApprox(long, double) - Static method in class org.apache.spark.api.java.JavaRDD
-
- countByValueApprox(long) - Static method in class org.apache.spark.api.java.JavaRDD
-
- countByValueApprox(long, double) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Approximate version of countByValue().
- countByValueApprox(long) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Approximate version of countByValue().
- countByValueApprox(long, double, Ordering<T>) - Static method in class org.apache.spark.api.r.RRDD
-
- countByValueApprox(long, double, Ordering<T>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- countByValueApprox(long, double, Ordering<T>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- countByValueApprox(long, double, Ordering<T>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- countByValueApprox(long, double, Ordering<T>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- countByValueApprox(long, double, Ordering<T>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- countByValueApprox(long, double, Ordering<T>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- countByValueApprox(long, double, Ordering<T>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- countByValueApprox(long, double, Ordering<T>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- countByValueApprox(long, double, Ordering<T>) - Method in class org.apache.spark.rdd.RDD
-
Approximate version of countByValue().
- countByValueApprox(long, double, Ordering<T>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- countByValueApprox$default$2() - Static method in class org.apache.spark.api.r.RRDD
-
- countByValueApprox$default$2() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- countByValueApprox$default$2() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- countByValueApprox$default$2() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- countByValueApprox$default$2() - Static method in class org.apache.spark.graphx.VertexRDD
-
- countByValueApprox$default$2() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- countByValueApprox$default$2() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- countByValueApprox$default$2() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- countByValueApprox$default$2() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- countByValueApprox$default$2() - Static method in class org.apache.spark.rdd.UnionRDD
-
- countByValueApprox$default$3(long, double) - Static method in class org.apache.spark.api.r.RRDD
-
- countByValueApprox$default$3(long, double) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- countByValueApprox$default$3(long, double) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- countByValueApprox$default$3(long, double) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- countByValueApprox$default$3(long, double) - Static method in class org.apache.spark.graphx.VertexRDD
-
- countByValueApprox$default$3(long, double) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- countByValueApprox$default$3(long, double) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- countByValueApprox$default$3(long, double) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- countByValueApprox$default$3(long, double) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- countByValueApprox$default$3(long, double) - Static method in class org.apache.spark.rdd.UnionRDD
-
- countByWindow(Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- countByWindow(Duration, Duration) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD has a single element generated by counting the number
of elements in a window over this DStream.
- countByWindow(Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- countByWindow(Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- countByWindow(Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- countByWindow(Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- countByWindow(Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- countByWindow(Duration, Duration) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream in which each RDD has a single element generated by counting the number
of elements in a sliding window over this DStream.
- countDistinct(Column, Column...) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the number of distinct items in a group.
- countDistinct(String, String...) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the number of distinct items in a group.
- countDistinct(Column, Seq<Column>) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the number of distinct items in a group.
- countDistinct(String, Seq<String>) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the number of distinct items in a group.
- countMinSketch(String, int, int, int) - Method in class org.apache.spark.sql.DataFrameStatFunctions
-
Builds a Count-min Sketch over a specified column.
- countMinSketch(String, double, double, int) - Method in class org.apache.spark.sql.DataFrameStatFunctions
-
Builds a Count-min Sketch over a specified column.
- countMinSketch(Column, int, int, int) - Method in class org.apache.spark.sql.DataFrameStatFunctions
-
Builds a Count-min Sketch over a specified column.
- countMinSketch(Column, double, double, int) - Method in class org.apache.spark.sql.DataFrameStatFunctions
-
Builds a Count-min Sketch over a specified column.
- CountMinSketch - Class in org.apache.spark.util.sketch
-
A Count-min sketch is a probabilistic data structure used for summarizing streams of data in
sub-linear space.
- CountMinSketch() - Constructor for class org.apache.spark.util.sketch.CountMinSketch
-
- CountMinSketch.Version - Enum in org.apache.spark.util.sketch
-
- countTowardsTaskFailures() - Static method in class org.apache.spark.ExceptionFailure
-
- countTowardsTaskFailures() - Method in class org.apache.spark.ExecutorLostFailure
-
- countTowardsTaskFailures() - Static method in class org.apache.spark.FetchFailed
-
- countTowardsTaskFailures() - Static method in class org.apache.spark.Resubmitted
-
- countTowardsTaskFailures() - Method in class org.apache.spark.TaskCommitDenied
-
If a task failed because its attempt to commit was denied, do not count this failure
towards failing the stage.
- countTowardsTaskFailures() - Method in interface org.apache.spark.TaskFailedReason
-
Whether this task failure should be counted towards the maximum number of times the task is
allowed to fail before the stage is aborted.
- countTowardsTaskFailures() - Static method in class org.apache.spark.TaskKilled
-
- countTowardsTaskFailures() - Static method in class org.apache.spark.TaskResultLost
-
- countTowardsTaskFailures() - Static method in class org.apache.spark.UnknownReason
-
- CountVectorizer - Class in org.apache.spark.ml.feature
-
- CountVectorizer(String) - Constructor for class org.apache.spark.ml.feature.CountVectorizer
-
- CountVectorizer() - Constructor for class org.apache.spark.ml.feature.CountVectorizer
-
- CountVectorizerModel - Class in org.apache.spark.ml.feature
-
Converts a text document to a sparse vector of token counts.
- CountVectorizerModel(String, String[]) - Constructor for class org.apache.spark.ml.feature.CountVectorizerModel
-
- CountVectorizerModel(String[]) - Constructor for class org.apache.spark.ml.feature.CountVectorizerModel
-
- cov() - Method in class org.apache.spark.ml.stat.distribution.MultivariateGaussian
-
- cov(String, String) - Method in class org.apache.spark.sql.DataFrameStatFunctions
-
Calculate the sample covariance of two numerical columns of a DataFrame.
- covar_pop(Column, Column) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the population covariance for two columns.
- covar_pop(String, String) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the population covariance for two columns.
- covar_samp(Column, Column) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the sample covariance for two columns.
- covar_samp(String, String) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the sample covariance for two columns.
- crc32(Column) - Static method in class org.apache.spark.sql.functions
-
Calculates the cyclic redundancy check value (CRC32) of a binary column and
returns the value as a bigint.
- CreatableRelationProvider - Interface in org.apache.spark.sql.sources
-
- create(boolean, boolean, boolean, boolean, int) - Static method in class org.apache.spark.api.java.StorageLevels
-
Create a new StorageLevel object.
- create(JavaSparkContext, JdbcRDD.ConnectionFactory, String, long, long, int, Function<ResultSet, T>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
Create an RDD that executes a SQL query on a JDBC connection and reads results.
- create(JavaSparkContext, JdbcRDD.ConnectionFactory, String, long, long, int) - Static method in class org.apache.spark.rdd.JdbcRDD
-
Create an RDD that executes a SQL query on a JDBC connection and reads results.
- create(RDD<T>, Function1<Object, Object>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
Create a PartitionPruningRDD.
- create(Object...) - Static method in class org.apache.spark.sql.RowFactory
-
Create a
Row from the given arguments.
- create(String) - Static method in class org.apache.spark.sql.streaming.ProcessingTime
-
- create(long, TimeUnit) - Static method in class org.apache.spark.sql.streaming.ProcessingTime
-
- create(String, int) - Static method in class org.apache.spark.streaming.kafka.Broker
-
- create(String, int, long, long) - Static method in class org.apache.spark.streaming.kafka.OffsetRange
-
- create(TopicAndPartition, long, long) - Static method in class org.apache.spark.streaming.kafka.OffsetRange
-
- create(long) - Static method in class org.apache.spark.util.sketch.BloomFilter
-
Creates a
BloomFilter with the expected number of insertions and a default expected
false positive probability of 3%.
- create(long, double) - Static method in class org.apache.spark.util.sketch.BloomFilter
-
Creates a
BloomFilter with the expected number of insertions and expected false
positive probability.
- create(long, long) - Static method in class org.apache.spark.util.sketch.BloomFilter
-
Creates a
BloomFilter with given
expectedNumItems and
numBits, it will
pick an optimal
numHashFunctions which can minimize
fpp for the bloom filter.
- create(int, int, int) - Static method in class org.apache.spark.util.sketch.CountMinSketch
-
- create(double, double, int) - Static method in class org.apache.spark.util.sketch.CountMinSketch
-
Creates a
CountMinSketch with given relative error (
eps),
confidence,
and random
seed.
- createArrayType(DataType) - Static method in class org.apache.spark.sql.types.DataTypes
-
Creates an ArrayType by specifying the data type of elements (elementType).
- createArrayType(DataType, boolean) - Static method in class org.apache.spark.sql.types.DataTypes
-
Creates an ArrayType by specifying the data type of elements (elementType) and
whether the array contains null values (containsNull).
- createCombiner() - Method in class org.apache.spark.Aggregator
-
- createCompiledClass(String, File, TestUtils.JavaSourceFromString, Seq<URL>) - Static method in class org.apache.spark.TestUtils
-
Creates a compiled class with the source file.
- createCompiledClass(String, File, String, String, Seq<URL>) - Static method in class org.apache.spark.TestUtils
-
Creates a compiled class with the given name.
- createDataFrame(RDD<A>, TypeTags.TypeTag<A>) - Method in class org.apache.spark.sql.SparkSession
-
:: Experimental ::
Creates a DataFrame from an RDD of Product (e.g.
- createDataFrame(Seq<A>, TypeTags.TypeTag<A>) - Method in class org.apache.spark.sql.SparkSession
-
:: Experimental ::
Creates a DataFrame from a local Seq of Product.
- createDataFrame(RDD<Row>, StructType) - Method in class org.apache.spark.sql.SparkSession
-
:: DeveloperApi ::
Creates a
DataFrame from an
RDD containing
Rows using the given schema.
- createDataFrame(JavaRDD<Row>, StructType) - Method in class org.apache.spark.sql.SparkSession
-
:: DeveloperApi ::
Creates a
DataFrame from a
JavaRDD containing
Rows using the given schema.
- createDataFrame(List<Row>, StructType) - Method in class org.apache.spark.sql.SparkSession
-
:: DeveloperApi ::
Creates a
DataFrame from a
List containing
Rows using the given schema.
- createDataFrame(RDD<?>, Class<?>) - Method in class org.apache.spark.sql.SparkSession
-
Applies a schema to an RDD of Java Beans.
- createDataFrame(JavaRDD<?>, Class<?>) - Method in class org.apache.spark.sql.SparkSession
-
Applies a schema to an RDD of Java Beans.
- createDataFrame(List<?>, Class<?>) - Method in class org.apache.spark.sql.SparkSession
-
Applies a schema to a List of Java Beans.
- createDataFrame(RDD<A>, TypeTags.TypeTag<A>) - Method in class org.apache.spark.sql.SQLContext
-
- createDataFrame(Seq<A>, TypeTags.TypeTag<A>) - Method in class org.apache.spark.sql.SQLContext
-
- createDataFrame(RDD<Row>, StructType) - Method in class org.apache.spark.sql.SQLContext
-
- createDataFrame(JavaRDD<Row>, StructType) - Method in class org.apache.spark.sql.SQLContext
-
- createDataFrame(List<Row>, StructType) - Method in class org.apache.spark.sql.SQLContext
-
- createDataFrame(RDD<?>, Class<?>) - Method in class org.apache.spark.sql.SQLContext
-
- createDataFrame(JavaRDD<?>, Class<?>) - Method in class org.apache.spark.sql.SQLContext
-
- createDataFrame(List<?>, Class<?>) - Method in class org.apache.spark.sql.SQLContext
-
- createDataset(Seq<T>, Encoder<T>) - Method in class org.apache.spark.sql.SparkSession
-
:: Experimental ::
Creates a
Dataset from a local Seq of data of a given type.
- createDataset(RDD<T>, Encoder<T>) - Method in class org.apache.spark.sql.SparkSession
-
:: Experimental ::
Creates a
Dataset from an RDD of a given type.
- createDataset(List<T>, Encoder<T>) - Method in class org.apache.spark.sql.SparkSession
-
:: Experimental ::
Creates a
Dataset from a
List of a given type.
- createDataset(Seq<T>, Encoder<T>) - Method in class org.apache.spark.sql.SQLContext
-
- createDataset(RDD<T>, Encoder<T>) - Method in class org.apache.spark.sql.SQLContext
-
- createDataset(List<T>, Encoder<T>) - Method in class org.apache.spark.sql.SQLContext
-
- createDecimalType(int, int) - Static method in class org.apache.spark.sql.types.DataTypes
-
Creates a DecimalType by specifying the precision and scale.
- createDecimalType() - Static method in class org.apache.spark.sql.types.DataTypes
-
Creates a DecimalType with default precision and scale, which are 10 and 0.
- createDF(RDD<byte[]>, StructType, SparkSession) - Static method in class org.apache.spark.sql.api.r.SQLUtils
-
- createDirectory(String, String) - Static method in class org.apache.spark.util.Utils
-
Create a directory inside the given parent directory.
- createDirectStream(StreamingContext, Map<String, String>, Map<TopicAndPartition, Object>, Function1<MessageAndMetadata<K, V>, R>, ClassTag<K>, ClassTag<V>, ClassTag<KD>, ClassTag<VD>, ClassTag<R>) - Static method in class org.apache.spark.streaming.kafka.KafkaUtils
-
Create an input stream that directly pulls messages from Kafka Brokers
without using any receiver.
- createDirectStream(StreamingContext, Map<String, String>, Set<String>, ClassTag<K>, ClassTag<V>, ClassTag<KD>, ClassTag<VD>) - Static method in class org.apache.spark.streaming.kafka.KafkaUtils
-
Create an input stream that directly pulls messages from Kafka Brokers
without using any receiver.
- createDirectStream(JavaStreamingContext, Class<K>, Class<V>, Class<KD>, Class<VD>, Class<R>, Map<String, String>, Map<TopicAndPartition, Long>, Function<MessageAndMetadata<K, V>, R>) - Static method in class org.apache.spark.streaming.kafka.KafkaUtils
-
Create an input stream that directly pulls messages from Kafka Brokers
without using any receiver.
- createDirectStream(JavaStreamingContext, Class<K>, Class<V>, Class<KD>, Class<VD>, Map<String, String>, Set<String>) - Static method in class org.apache.spark.streaming.kafka.KafkaUtils
-
Create an input stream that directly pulls messages from Kafka Brokers
without using any receiver.
- createExternalTable(String, String) - Method in class org.apache.spark.sql.catalog.Catalog
-
:: Experimental ::
Creates an external table from the given path and returns the corresponding DataFrame.
- createExternalTable(String, String, String) - Method in class org.apache.spark.sql.catalog.Catalog
-
:: Experimental ::
Creates an external table from the given path based on a data source
and returns the corresponding DataFrame.
- createExternalTable(String, String, Map<String, String>) - Method in class org.apache.spark.sql.catalog.Catalog
-
:: Experimental ::
Creates an external table from the given path based on a data source and a set of options.
- createExternalTable(String, String, Map<String, String>) - Method in class org.apache.spark.sql.catalog.Catalog
-
:: Experimental ::
(Scala-specific)
Creates an external table from the given path based on a data source and a set of options.
- createExternalTable(String, String, StructType, Map<String, String>) - Method in class org.apache.spark.sql.catalog.Catalog
-
:: Experimental ::
Create an external table from the given path based on a data source, a schema and
a set of options.
- createExternalTable(String, String, StructType, Map<String, String>) - Method in class org.apache.spark.sql.catalog.Catalog
-
:: Experimental ::
(Scala-specific)
Create an external table from the given path based on a data source, a schema and
a set of options.
- createExternalTable(String, String) - Method in class org.apache.spark.sql.internal.CatalogImpl
-
:: Experimental ::
Creates an external table from the given path and returns the corresponding DataFrame.
- createExternalTable(String, String, String) - Method in class org.apache.spark.sql.internal.CatalogImpl
-
:: Experimental ::
Creates an external table from the given path based on a data source
and returns the corresponding DataFrame.
- createExternalTable(String, String, Map<String, String>) - Method in class org.apache.spark.sql.internal.CatalogImpl
-
:: Experimental ::
Creates an external table from the given path based on a data source and a set of options.
- createExternalTable(String, String, Map<String, String>) - Method in class org.apache.spark.sql.internal.CatalogImpl
-
:: Experimental ::
(Scala-specific)
Creates an external table from the given path based on a data source and a set of options.
- createExternalTable(String, String, StructType, Map<String, String>) - Method in class org.apache.spark.sql.internal.CatalogImpl
-
:: Experimental ::
Create an external table from the given path based on a data source, a schema and
a set of options.
- createExternalTable(String, String, StructType, Map<String, String>) - Method in class org.apache.spark.sql.internal.CatalogImpl
-
:: Experimental ::
(Scala-specific)
Create an external table from the given path based on a data source, a schema and
a set of options.
- createExternalTable(String, String) - Method in class org.apache.spark.sql.SQLContext
-
- createExternalTable(String, String, String) - Method in class org.apache.spark.sql.SQLContext
-
- createExternalTable(String, String, Map<String, String>) - Method in class org.apache.spark.sql.SQLContext
-
- createExternalTable(String, String, Map<String, String>) - Method in class org.apache.spark.sql.SQLContext
-
- createExternalTable(String, String, StructType, Map<String, String>) - Method in class org.apache.spark.sql.SQLContext
-
- createExternalTable(String, String, StructType, Map<String, String>) - Method in class org.apache.spark.sql.SQLContext
-
- createFilter(StructType, Filter[]) - Static method in class org.apache.spark.sql.hive.orc.OrcFilters
-
- CreateHiveTableAsSelectCommand - Class in org.apache.spark.sql.hive.execution
-
Create table and insert the query result into it.
- CreateHiveTableAsSelectCommand(CatalogTable, LogicalPlan, boolean) - Constructor for class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- createJar(Seq<File>, File, Option<String>) - Static method in class org.apache.spark.TestUtils
-
Create a jar file that contains this set of files.
- createJarWithClasses(Seq<String>, String, Seq<Tuple2<String, String>>, Seq<URL>) - Static method in class org.apache.spark.TestUtils
-
Create a jar that defines classes with the given names.
- createJarWithFiles(Map<String, String>, File) - Static method in class org.apache.spark.TestUtils
-
Create a jar file containing multiple files.
- createLogForDriver(SparkConf, String, Configuration) - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
-
Create a WriteAheadLog for the driver.
- createLogForReceiver(SparkConf, String, Configuration) - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
-
Create a WriteAheadLog for the receiver.
- createMapType(DataType, DataType) - Static method in class org.apache.spark.sql.types.DataTypes
-
Creates a MapType by specifying the data type of keys (keyType) and values
(keyType).
- createMapType(DataType, DataType, boolean) - Static method in class org.apache.spark.sql.types.DataTypes
-
Creates a MapType by specifying the data type of keys (keyType), the data type of
values (keyType), and whether values contain any null value
(valueContainsNull).
- createOrReplaceTempView(String) - Method in class org.apache.spark.sql.Dataset
-
Creates a temporary view using the given name.
- createOutputOperationFailureForUI(String) - Static method in class org.apache.spark.streaming.ui.UIUtils
-
- createPMMLModelExport(Object) - Static method in class org.apache.spark.mllib.pmml.export.PMMLModelExportFactory
-
Factory object to help creating the necessary PMMLModelExport implementation
taking as input the machine learning model (for example KMeansModel).
- createPollingStream(StreamingContext, String, int, StorageLevel) - Static method in class org.apache.spark.streaming.flume.FlumeUtils
-
Creates an input stream that is to be used with the Spark Sink deployed on a Flume agent.
- createPollingStream(StreamingContext, Seq<InetSocketAddress>, StorageLevel) - Static method in class org.apache.spark.streaming.flume.FlumeUtils
-
Creates an input stream that is to be used with the Spark Sink deployed on a Flume agent.
- createPollingStream(StreamingContext, Seq<InetSocketAddress>, StorageLevel, int, int) - Static method in class org.apache.spark.streaming.flume.FlumeUtils
-
Creates an input stream that is to be used with the Spark Sink deployed on a Flume agent.
- createPollingStream(JavaStreamingContext, String, int) - Static method in class org.apache.spark.streaming.flume.FlumeUtils
-
Creates an input stream that is to be used with the Spark Sink deployed on a Flume agent.
- createPollingStream(JavaStreamingContext, String, int, StorageLevel) - Static method in class org.apache.spark.streaming.flume.FlumeUtils
-
Creates an input stream that is to be used with the Spark Sink deployed on a Flume agent.
- createPollingStream(JavaStreamingContext, InetSocketAddress[], StorageLevel) - Static method in class org.apache.spark.streaming.flume.FlumeUtils
-
Creates an input stream that is to be used with the Spark Sink deployed on a Flume agent.
- createPollingStream(JavaStreamingContext, InetSocketAddress[], StorageLevel, int, int) - Static method in class org.apache.spark.streaming.flume.FlumeUtils
-
Creates an input stream that is to be used with the Spark Sink deployed on a Flume agent.
- createRDD(SparkContext, Map<String, String>, OffsetRange[], ClassTag<K>, ClassTag<V>, ClassTag<KD>, ClassTag<VD>) - Static method in class org.apache.spark.streaming.kafka.KafkaUtils
-
Create a RDD from Kafka using offset ranges for each topic and partition.
- createRDD(SparkContext, Map<String, String>, OffsetRange[], Map<TopicAndPartition, Broker>, Function1<MessageAndMetadata<K, V>, R>, ClassTag<K>, ClassTag<V>, ClassTag<KD>, ClassTag<VD>, ClassTag<R>) - Static method in class org.apache.spark.streaming.kafka.KafkaUtils
-
Create a RDD from Kafka using offset ranges for each topic and partition.
- createRDD(JavaSparkContext, Class<K>, Class<V>, Class<KD>, Class<VD>, Map<String, String>, OffsetRange[]) - Static method in class org.apache.spark.streaming.kafka.KafkaUtils
-
Create a RDD from Kafka using offset ranges for each topic and partition.
- createRDD(JavaSparkContext, Class<K>, Class<V>, Class<KD>, Class<VD>, Class<R>, Map<String, String>, OffsetRange[], Map<TopicAndPartition, Broker>, Function<MessageAndMetadata<K, V>, R>) - Static method in class org.apache.spark.streaming.kafka.KafkaUtils
-
Create a RDD from Kafka using offset ranges for each topic and partition.
- createRDDFromArray(JavaSparkContext, byte[][]) - Static method in class org.apache.spark.api.r.RRDD
-
Create an RRDD given a sequence of byte arrays.
- createRedirectHandler(String, String, Function1<HttpServletRequest, BoxedUnit>, String, Set<String>) - Static method in class org.apache.spark.ui.JettyUtils
-
Create a handler that always redirects the user to the given path
- createRelation(SQLContext, SaveMode, Map<String, String>, Dataset<Row>) - Method in interface org.apache.spark.sql.sources.CreatableRelationProvider
-
Creates a relation with the given parameters based on the contents of the given
DataFrame.
- createRelation(SQLContext, Map<String, String>) - Method in interface org.apache.spark.sql.sources.RelationProvider
-
Returns a new base relation with the given parameters.
- createRelation(SQLContext, Map<String, String>, StructType) - Method in interface org.apache.spark.sql.sources.SchemaRelationProvider
-
Returns a new base relation with the given parameters and user defined schema.
- createServlet(JettyUtils.ServletParams<T>, org.apache.spark.SecurityManager, SparkConf, Function1<T, Object>) - Static method in class org.apache.spark.ui.JettyUtils
-
- createServletHandler(String, JettyUtils.ServletParams<T>, org.apache.spark.SecurityManager, SparkConf, String, Function1<T, Object>) - Static method in class org.apache.spark.ui.JettyUtils
-
Create a context handler that responds to a request with the given path prefix
- createServletHandler(String, HttpServlet, String) - Static method in class org.apache.spark.ui.JettyUtils
-
Create a context handler that responds to a request with the given path prefix
- createSink(SQLContext, Map<String, String>, Seq<String>, OutputMode) - Method in interface org.apache.spark.sql.sources.StreamSinkProvider
-
- createSource(SQLContext, String, Option<StructType>, String, Map<String, String>) - Method in interface org.apache.spark.sql.sources.StreamSourceProvider
-
- createSparkContext(String, String, String, String[], Map<Object, Object>, Map<Object, Object>) - Static method in class org.apache.spark.api.r.RRDD
-
- createStaticHandler(String, String) - Static method in class org.apache.spark.ui.JettyUtils
-
Create a handler for serving files from a static directory
- createStream(StreamingContext, String, int, StorageLevel) - Static method in class org.apache.spark.streaming.flume.FlumeUtils
-
Create a input stream from a Flume source.
- createStream(StreamingContext, String, int, StorageLevel, boolean) - Static method in class org.apache.spark.streaming.flume.FlumeUtils
-
Create a input stream from a Flume source.
- createStream(JavaStreamingContext, String, int) - Static method in class org.apache.spark.streaming.flume.FlumeUtils
-
Creates a input stream from a Flume source.
- createStream(JavaStreamingContext, String, int, StorageLevel) - Static method in class org.apache.spark.streaming.flume.FlumeUtils
-
Creates a input stream from a Flume source.
- createStream(JavaStreamingContext, String, int, StorageLevel, boolean) - Static method in class org.apache.spark.streaming.flume.FlumeUtils
-
Creates a input stream from a Flume source.
- createStream(StreamingContext, String, String, Map<String, Object>, StorageLevel) - Static method in class org.apache.spark.streaming.kafka.KafkaUtils
-
Create an input stream that pulls messages from Kafka Brokers.
- createStream(StreamingContext, Map<String, String>, Map<String, Object>, StorageLevel, ClassTag<K>, ClassTag<V>, ClassTag<U>, ClassTag<T>) - Static method in class org.apache.spark.streaming.kafka.KafkaUtils
-
Create an input stream that pulls messages from Kafka Brokers.
- createStream(JavaStreamingContext, String, String, Map<String, Integer>) - Static method in class org.apache.spark.streaming.kafka.KafkaUtils
-
Create an input stream that pulls messages from Kafka Brokers.
- createStream(JavaStreamingContext, String, String, Map<String, Integer>, StorageLevel) - Static method in class org.apache.spark.streaming.kafka.KafkaUtils
-
Create an input stream that pulls messages from Kafka Brokers.
- createStream(JavaStreamingContext, Class<K>, Class<V>, Class<U>, Class<T>, Map<String, String>, Map<String, Integer>, StorageLevel) - Static method in class org.apache.spark.streaming.kafka.KafkaUtils
-
Create an input stream that pulls messages from Kafka Brokers.
- createStream(StreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel, Function1<Record, T>, ClassTag<T>) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
-
Create an input stream that pulls messages from a Kinesis stream.
- createStream(StreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel, Function1<Record, T>, String, String, ClassTag<T>) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
-
Create an input stream that pulls messages from a Kinesis stream.
- createStream(StreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
-
Create an input stream that pulls messages from a Kinesis stream.
- createStream(StreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel, String, String) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
-
Create an input stream that pulls messages from a Kinesis stream.
- createStream(JavaStreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel, Function<Record, T>, Class<T>) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
-
Create an input stream that pulls messages from a Kinesis stream.
- createStream(JavaStreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel, Function<Record, T>, Class<T>, String, String) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
-
Create an input stream that pulls messages from a Kinesis stream.
- createStream(JavaStreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
-
Create an input stream that pulls messages from a Kinesis stream.
- createStream(JavaStreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel, String, String) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
-
Create an input stream that pulls messages from a Kinesis stream.
- createStream(JavaStreamingContext, String, String, String, String, int, Duration, StorageLevel, String, String) - Method in class org.apache.spark.streaming.kinesis.KinesisUtilsPythonHelper
-
- createStructField(String, String, boolean) - Static method in class org.apache.spark.sql.api.r.SQLUtils
-
- createStructField(String, DataType, boolean, Metadata) - Static method in class org.apache.spark.sql.types.DataTypes
-
Creates a StructField by specifying the name (name), data type (dataType) and
whether values of this field can be null values (nullable).
- createStructField(String, DataType, boolean) - Static method in class org.apache.spark.sql.types.DataTypes
-
Creates a StructField with empty metadata.
- createStructType(Seq<StructField>) - Static method in class org.apache.spark.sql.api.r.SQLUtils
-
- createStructType(List<StructField>) - Static method in class org.apache.spark.sql.types.DataTypes
-
Creates a StructType with the given list of StructFields (fields).
- createStructType(StructField[]) - Static method in class org.apache.spark.sql.types.DataTypes
-
Creates a StructType with the given StructField array (fields).
- createTempDir(String, String) - Static method in class org.apache.spark.util.Utils
-
Create a temporary directory inside the given parent directory.
- createTempView(String) - Method in class org.apache.spark.sql.Dataset
-
Creates a temporary view using the given name.
- createUnsafe(long, int, int) - Static method in class org.apache.spark.sql.types.Decimal
-
Creates a decimal from unscaled, precision and scale without checking the bounds.
- createWorkspace(int) - Static method in class org.apache.spark.mllib.optimization.NNLS
-
- crosstab(String, String) - Method in class org.apache.spark.sql.DataFrameStatFunctions
-
Computes a pair-wise frequency table of the given columns.
- CrossValidator - Class in org.apache.spark.ml.tuning
-
K-fold cross validation.
- CrossValidator(String) - Constructor for class org.apache.spark.ml.tuning.CrossValidator
-
- CrossValidator() - Constructor for class org.apache.spark.ml.tuning.CrossValidator
-
- CrossValidatorModel - Class in org.apache.spark.ml.tuning
-
Model from k-fold cross validation.
- csv(String...) - Method in class org.apache.spark.sql.DataFrameReader
-
Loads a CSV file and returns the result as a DataFrame.
- csv(String) - Method in class org.apache.spark.sql.DataFrameReader
-
Loads a CSV file and returns the result as a DataFrame.
- csv(Seq<String>) - Method in class org.apache.spark.sql.DataFrameReader
-
Loads a CSV file and returns the result as a DataFrame.
- csv(String) - Method in class org.apache.spark.sql.DataFrameWriter
-
Saves the content of the DataFrame in CSV format at the specified path.
- csv(String) - Method in class org.apache.spark.sql.streaming.DataStreamReader
-
:: Experimental ::
Loads a CSV file stream and returns the result as a DataFrame.
- cube(Column...) - Method in class org.apache.spark.sql.Dataset
-
Create a multi-dimensional cube for the current Dataset using the specified columns,
so we can run aggregation on them.
- cube(String, String...) - Method in class org.apache.spark.sql.Dataset
-
Create a multi-dimensional cube for the current Dataset using the specified columns,
so we can run aggregation on them.
- cube(Seq<Column>) - Method in class org.apache.spark.sql.Dataset
-
Create a multi-dimensional cube for the current Dataset using the specified columns,
so we can run aggregation on them.
- cube(String, Seq<String>) - Method in class org.apache.spark.sql.Dataset
-
Create a multi-dimensional cube for the current Dataset using the specified columns,
so we can run aggregation on them.
- cume_dist() - Static method in class org.apache.spark.sql.functions
-
Window function: returns the cumulative distribution of values within a window partition,
i.e.
- current_date() - Static method in class org.apache.spark.sql.functions
-
Returns the current date as a date column.
- current_timestamp() - Static method in class org.apache.spark.sql.functions
-
Returns the current timestamp as a timestamp column.
- currentAttemptId() - Method in interface org.apache.spark.SparkStageInfo
-
- currentAttemptId() - Method in class org.apache.spark.SparkStageInfoImpl
-
- currentDatabase() - Method in class org.apache.spark.sql.catalog.Catalog
-
Returns the current default database in this session.
- currentDatabase() - Method in class org.apache.spark.sql.internal.CatalogImpl
-
Returns the current default database in this session.
- currPrefLocs(Partition, RDD<?>) - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
-
- dapply(Dataset<Row>, byte[], byte[], Object[], StructType) - Static method in class org.apache.spark.sql.api.r.SQLUtils
-
The helper function for dapply() on R side.
- data() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.LaunchTask
-
- data() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StatusUpdate
-
- Database - Class in org.apache.spark.sql.catalog
-
A database in Spark, as returned by the
listDatabases method defined in
Catalog.
- Database(String, String, String) - Constructor for class org.apache.spark.sql.catalog.Database
-
- database() - Method in class org.apache.spark.sql.catalog.Function
-
- database() - Method in class org.apache.spark.sql.catalog.Table
-
- databaseTypeDefinition() - Method in class org.apache.spark.sql.jdbc.JdbcType
-
- dataDistribution() - Method in class org.apache.spark.status.api.v1.RDDStorageInfo
-
- DATAFRAME_DAPPLY() - Static method in class org.apache.spark.api.r.RRunnerModes
-
- DATAFRAME_GAPPLY() - Static method in class org.apache.spark.api.r.RRunnerModes
-
- DataFrameNaFunctions - Class in org.apache.spark.sql
-
:: Experimental ::
Functionality for working with missing data in DataFrames.
- DataFrameReader - Class in org.apache.spark.sql
-
Interface used to load a
Dataset from external storage systems (e.g.
- DataFrameStatFunctions - Class in org.apache.spark.sql
-
:: Experimental ::
Statistic functions for DataFrames.
- DataFrameWriter<T> - Class in org.apache.spark.sql
-
Interface used to write a
Dataset to external storage systems (e.g.
- Dataset<T> - Class in org.apache.spark.sql
-
A Dataset is a strongly typed collection of domain-specific objects that can be transformed
in parallel using functional or relational operations.
- Dataset(SparkSession, LogicalPlan, Encoder<T>) - Constructor for class org.apache.spark.sql.Dataset
-
- Dataset(SQLContext, LogicalPlan, Encoder<T>) - Constructor for class org.apache.spark.sql.Dataset
-
- DatasetHolder<T> - Class in org.apache.spark.sql
-
A container for a
Dataset, used for implicit conversions in Scala.
- DataSourceRegister - Interface in org.apache.spark.sql.sources
-
::DeveloperApi::
Data sources should implement this trait so that they can register an alias to their data source.
- DataStreamReader - Class in org.apache.spark.sql.streaming
-
Interface used to load a streaming Dataset from external storage systems (e.g.
- DataStreamWriter<T> - Class in org.apache.spark.sql.streaming
-
:: Experimental ::
Interface used to write a streaming Dataset to external storage systems (e.g.
- dataTablesHeaderNodes() - Static method in class org.apache.spark.ui.UIUtils
-
- dataType() - Method in class org.apache.spark.sql.catalog.Column
-
- dataType() - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
-
- dataType() - Method in class org.apache.spark.sql.expressions.UserDefinedFunction
-
- DataType - Class in org.apache.spark.sql.types
-
:: DeveloperApi ::
The base type of all Spark SQL data types.
- DataType() - Constructor for class org.apache.spark.sql.types.DataType
-
- dataType() - Method in class org.apache.spark.sql.types.StructField
-
- DataTypes - Class in org.apache.spark.sql.types
-
To get/create specific data type, users should use singleton objects and factory methods
provided by this class.
- DataTypes() - Constructor for class org.apache.spark.sql.types.DataTypes
-
- DataValidators - Class in org.apache.spark.mllib.util
-
:: DeveloperApi ::
A collection of methods used to validate data before applying ML algorithms.
- DataValidators() - Constructor for class org.apache.spark.mllib.util.DataValidators
-
- date() - Method in class org.apache.spark.sql.ColumnName
-
Creates a new StructField of type date.
- DATE() - Static method in class org.apache.spark.sql.Encoders
-
An encoder for nullable date type.
- date_add(Column, int) - Static method in class org.apache.spark.sql.functions
-
Returns the date that is days days after start
- date_format(Column, String) - Static method in class org.apache.spark.sql.functions
-
Converts a date/timestamp/string to a value of string in the format specified by the date
format given by the second argument.
- date_sub(Column, int) - Static method in class org.apache.spark.sql.functions
-
Returns the date that is days days before start
- datediff(Column, Column) - Static method in class org.apache.spark.sql.functions
-
Returns the number of days from start to end.
- DateType - Static variable in class org.apache.spark.sql.types.DataTypes
-
Gets the DateType object.
- DateType - Class in org.apache.spark.sql.types
-
:: DeveloperApi ::
A date type, supporting "0001-01-01" through "9999-12-31".
- dayofmonth(Column) - Static method in class org.apache.spark.sql.functions
-
Extracts the day of the month as an integer from a given date/timestamp/string.
- dayofyear(Column) - Static method in class org.apache.spark.sql.functions
-
Extracts the day of the year as an integer from a given date/timestamp/string.
- DB2Dialect - Class in org.apache.spark.sql.jdbc
-
- DB2Dialect() - Constructor for class org.apache.spark.sql.jdbc.DB2Dialect
-
- DCT - Class in org.apache.spark.ml.feature
-
A feature transformer that takes the 1D discrete cosine transform of a real vector.
- DCT(String) - Constructor for class org.apache.spark.ml.feature.DCT
-
- DCT() - Constructor for class org.apache.spark.ml.feature.DCT
-
- deadStorageStatusList() - Method in class org.apache.spark.storage.StorageStatusListener
-
- deadStorageStatusList() - Method in class org.apache.spark.ui.exec.ExecutorsListener
-
- decayFactor() - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
-
- decimal() - Method in class org.apache.spark.sql.ColumnName
-
Creates a new StructField of type decimal.
- decimal(int, int) - Method in class org.apache.spark.sql.ColumnName
-
Creates a new StructField of type decimal.
- DECIMAL() - Static method in class org.apache.spark.sql.Encoders
-
An encoder for nullable decimal type.
- Decimal - Class in org.apache.spark.sql.types
-
A mutable implementation of BigDecimal that can hold a Long if values are small enough.
- Decimal() - Constructor for class org.apache.spark.sql.types.Decimal
-
- Decimal.DecimalAsIfIntegral$ - Class in org.apache.spark.sql.types
-
A Integral evidence parameter for Decimals.
- Decimal.DecimalAsIfIntegral$() - Constructor for class org.apache.spark.sql.types.Decimal.DecimalAsIfIntegral$
-
- Decimal.DecimalIsFractional$ - Class in org.apache.spark.sql.types
-
A Fractional evidence parameter for Decimals.
- Decimal.DecimalIsFractional$() - Constructor for class org.apache.spark.sql.types.Decimal.DecimalIsFractional$
-
- DecimalType - Class in org.apache.spark.sql.types
-
:: DeveloperApi ::
The data type representing java.math.BigDecimal values.
- DecimalType(int, int) - Constructor for class org.apache.spark.sql.types.DecimalType
-
- DecimalType(int) - Constructor for class org.apache.spark.sql.types.DecimalType
-
- DecimalType() - Constructor for class org.apache.spark.sql.types.DecimalType
-
- DecimalType.Expression$ - Class in org.apache.spark.sql.types
-
- DecimalType.Expression$() - Constructor for class org.apache.spark.sql.types.DecimalType.Expression$
-
- DecimalType.Fixed$ - Class in org.apache.spark.sql.types
-
- DecimalType.Fixed$() - Constructor for class org.apache.spark.sql.types.DecimalType.Fixed$
-
- DecisionTree - Class in org.apache.spark.mllib.tree
-
A class which implements a decision tree learning algorithm for classification and regression.
- DecisionTree(Strategy) - Constructor for class org.apache.spark.mllib.tree.DecisionTree
-
- DecisionTreeClassificationModel - Class in org.apache.spark.ml.classification
-
Decision tree model (http://en.wikipedia.org/wiki/Decision_tree_learning) for classification.
- DecisionTreeClassifier - Class in org.apache.spark.ml.classification
-
Decision tree learning algorithm (http://en.wikipedia.org/wiki/Decision_tree_learning)
for classification.
- DecisionTreeClassifier(String) - Constructor for class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- DecisionTreeClassifier() - Constructor for class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- DecisionTreeModel - Class in org.apache.spark.mllib.tree.model
-
Decision tree model for classification or regression.
- DecisionTreeModel(Node, Enumeration.Value) - Constructor for class org.apache.spark.mllib.tree.model.DecisionTreeModel
-
- DecisionTreeModel.SaveLoadV1_0$ - Class in org.apache.spark.mllib.tree.model
-
- DecisionTreeModel.SaveLoadV1_0$() - Constructor for class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$
-
- DecisionTreeModel.SaveLoadV1_0$.NodeData - Class in org.apache.spark.mllib.tree.model
-
Model data for model import/export
- DecisionTreeModel.SaveLoadV1_0$.NodeData(int, int, org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0.PredictData, double, boolean, Option<org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0.SplitData>, Option<Object>, Option<Object>, Option<Object>) - Constructor for class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData
-
- DecisionTreeModel.SaveLoadV1_0$.PredictData - Class in org.apache.spark.mllib.tree.model
-
- DecisionTreeModel.SaveLoadV1_0$.PredictData(double, double) - Constructor for class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.PredictData
-
- DecisionTreeModel.SaveLoadV1_0$.SplitData - Class in org.apache.spark.mllib.tree.model
-
- DecisionTreeModel.SaveLoadV1_0$.SplitData(int, double, int, Seq<Object>) - Constructor for class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.SplitData
-
- DecisionTreeModelReadWrite - Class in org.apache.spark.ml.tree
-
Helper classes for tree model persistence
- DecisionTreeModelReadWrite() - Constructor for class org.apache.spark.ml.tree.DecisionTreeModelReadWrite
-
- DecisionTreeModelReadWrite.NodeData - Class in org.apache.spark.ml.tree
-
- DecisionTreeModelReadWrite.NodeData(int, double, double, double[], double, int, int, DecisionTreeModelReadWrite.SplitData) - Constructor for class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData
-
- DecisionTreeModelReadWrite.NodeData$ - Class in org.apache.spark.ml.tree
-
- DecisionTreeModelReadWrite.NodeData$() - Constructor for class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData$
-
- DecisionTreeModelReadWrite.SplitData - Class in org.apache.spark.ml.tree
-
- DecisionTreeModelReadWrite.SplitData(int, double[], int) - Constructor for class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.SplitData
-
- DecisionTreeModelReadWrite.SplitData$ - Class in org.apache.spark.ml.tree
-
- DecisionTreeModelReadWrite.SplitData$() - Constructor for class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.SplitData$
-
- DecisionTreeRegressionModel - Class in org.apache.spark.ml.regression
-
Decision tree model for regression.
- DecisionTreeRegressor - Class in org.apache.spark.ml.regression
-
Decision tree learning algorithm
for regression.
- DecisionTreeRegressor(String) - Constructor for class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- DecisionTreeRegressor() - Constructor for class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- decode(Column, String) - Static method in class org.apache.spark.sql.functions
-
Computes the first argument into a string from a binary using the provided character set
(one of 'US-ASCII', 'ISO-8859-1', 'UTF-8', 'UTF-16BE', 'UTF-16LE', 'UTF-16').
- decodeFileNameInURI(URI) - Static method in class org.apache.spark.util.Utils
-
Get the file name from uri's raw path and decode it.
- decodeLabel(Vector) - Static method in class org.apache.spark.ml.classification.LabelConverter
-
Converts a vector to a label.
- decodeURLParameter(String) - Static method in class org.apache.spark.ui.UIUtils
-
Decode URLParameter if URL is encoded by YARN-WebAppProxyServlet.
- DEFAULT_DRIVER_MEM_MB() - Static method in class org.apache.spark.util.Utils
-
Define a default value for driver memory here since this value is referenced across the code
base and nearly all files already use Utils.scala
- DEFAULT_MAX_FAILURES() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
-
- DEFAULT_MAX_TO_STRING_FIELDS() - Static method in class org.apache.spark.util.Utils
-
The performance overhead of creating and logging strings for wide schemas can be large.
- DEFAULT_ROLLING_INTERVAL_SECS() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
-
- DEFAULT_SHUTDOWN_PRIORITY() - Static method in class org.apache.spark.util.ShutdownHookManager
-
- defaultAttr() - Static method in class org.apache.spark.ml.attribute.BinaryAttribute
-
The default binary attribute.
- defaultAttr() - Static method in class org.apache.spark.ml.attribute.NominalAttribute
-
The default nominal attribute.
- defaultAttr() - Static method in class org.apache.spark.ml.attribute.NumericAttribute
-
The default numeric attribute.
- defaultCopy(ParamMap) - Method in interface org.apache.spark.ml.param.Params
-
Default implementation of copy with extra params.
- defaultCorrName() - Static method in class org.apache.spark.mllib.stat.correlation.CorrelationNames
-
- defaultLink() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Binomial$
-
- defaultLink() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gamma$
-
- defaultLink() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gaussian$
-
- defaultLink() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Poisson$
-
- defaultMinPartitions() - Method in class org.apache.spark.api.java.JavaSparkContext
-
Default min number of partitions for Hadoop RDDs when not given by user
- defaultMinPartitions() - Method in class org.apache.spark.SparkContext
-
Default min number of partitions for Hadoop RDDs when not given by user
Notice that we use math.min so the "defaultMinPartitions" cannot be higher than 2.
- defaultParallelism() - Method in class org.apache.spark.api.java.JavaSparkContext
-
Default level of parallelism to use when not given by user (e.g.
- defaultParallelism() - Method in class org.apache.spark.SparkContext
-
Default level of parallelism to use when not given by user (e.g.
- defaultParamMap() - Method in interface org.apache.spark.ml.param.Params
-
Internal param map for default values.
- defaultParams(String) - Static method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
Returns default configuration for the boosting algorithm
- defaultParams(Enumeration.Value) - Static method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
Returns default configuration for the boosting algorithm
- DefaultParamsReadable<T> - Interface in org.apache.spark.ml.util
-
:: DeveloperApi ::
- DefaultParamsWritable - Interface in org.apache.spark.ml.util
-
:: DeveloperApi ::
- DefaultPartitionCoalescer - Class in org.apache.spark.rdd
-
Coalesce the partitions of a parent RDD (prev) into fewer partitions, so that each partition of
this RDD computes one or more of the parent ones.
- DefaultPartitionCoalescer(double) - Constructor for class org.apache.spark.rdd.DefaultPartitionCoalescer
-
- DefaultPartitionCoalescer.PartitionLocations - Class in org.apache.spark.rdd
-
- DefaultPartitionCoalescer.PartitionLocations(RDD<?>) - Constructor for class org.apache.spark.rdd.DefaultPartitionCoalescer.PartitionLocations
-
- defaultPartitioner(RDD<?>, Seq<RDD<?>>) - Static method in class org.apache.spark.Partitioner
-
Choose a partitioner to use for a cogroup-like operation between a number of RDDs.
- defaultSize() - Method in class org.apache.spark.sql.types.ArrayType
-
The default size of a value of the ArrayType is 100 * the default size of the element type.
- defaultSize() - Method in class org.apache.spark.sql.types.BinaryType
-
The default size of a value of the BinaryType is 100 bytes.
- defaultSize() - Method in class org.apache.spark.sql.types.BooleanType
-
The default size of a value of the BooleanType is 1 byte.
- defaultSize() - Method in class org.apache.spark.sql.types.ByteType
-
The default size of a value of the ByteType is 1 byte.
- defaultSize() - Method in class org.apache.spark.sql.types.CalendarIntervalType
-
- defaultSize() - Method in class org.apache.spark.sql.types.DataType
-
The default size of a value of this data type, used internally for size estimation.
- defaultSize() - Method in class org.apache.spark.sql.types.DateType
-
The default size of a value of the DateType is 4 bytes.
- defaultSize() - Method in class org.apache.spark.sql.types.DecimalType
-
The default size of a value of the DecimalType is 8 bytes (precision <= 18) or 16 bytes.
- defaultSize() - Method in class org.apache.spark.sql.types.DoubleType
-
The default size of a value of the DoubleType is 8 bytes.
- defaultSize() - Method in class org.apache.spark.sql.types.FloatType
-
The default size of a value of the FloatType is 4 bytes.
- defaultSize() - Method in class org.apache.spark.sql.types.IntegerType
-
The default size of a value of the IntegerType is 4 bytes.
- defaultSize() - Method in class org.apache.spark.sql.types.LongType
-
The default size of a value of the LongType is 8 bytes.
- defaultSize() - Method in class org.apache.spark.sql.types.MapType
-
The default size of a value of the MapType is
100 * (the default size of the key type + the default size of the value type).
- defaultSize() - Method in class org.apache.spark.sql.types.NullType
-
- defaultSize() - Static method in class org.apache.spark.sql.types.NumericType
-
- defaultSize() - Method in class org.apache.spark.sql.types.ShortType
-
The default size of a value of the ShortType is 2 bytes.
- defaultSize() - Method in class org.apache.spark.sql.types.StringType
-
The default size of a value of the StringType is 20 bytes.
- defaultSize() - Method in class org.apache.spark.sql.types.StructType
-
The default size of a value of the StructType is the total default sizes of all field types.
- defaultSize() - Method in class org.apache.spark.sql.types.TimestampType
-
The default size of a value of the TimestampType is 8 bytes.
- defaultStrategy(String) - Static method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- defaultStrategy(Enumeration.Value) - Static method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- defaultValue() - Method in class org.apache.spark.internal.config.ConfigEntryWithDefault
-
- defaultValueString() - Method in class org.apache.spark.internal.config.ConfigEntryWithDefault
-
- defaultValueString() - Method in class org.apache.spark.internal.config.FallbackConfigEntry
-
- degree() - Method in class org.apache.spark.ml.feature.PolynomialExpansion
-
The polynomial degree to expand, which should be >= 1.
- degrees() - Method in class org.apache.spark.graphx.GraphOps
-
The degree of each vertex in the graph.
- degreesOfFreedom() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
-
Degrees of freedom.
- degreesOfFreedom() - Method in class org.apache.spark.mllib.stat.test.ChiSqTestResult
-
- degreesOfFreedom() - Method in class org.apache.spark.mllib.stat.test.KolmogorovSmirnovTestResult
-
- degreesOfFreedom() - Method in interface org.apache.spark.mllib.stat.test.TestResult
-
Returns the degree(s) of freedom of the hypothesis test.
- delegate() - Method in class org.apache.spark.InterruptibleIterator
-
- deleteCheckpointFiles() - Method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
:: DeveloperApi ::
- deleteRecursively(File) - Static method in class org.apache.spark.util.Utils
-
Delete a file or directory and its contents recursively.
- dense(int, int, double[]) - Static method in class org.apache.spark.ml.linalg.Matrices
-
Creates a column-major dense matrix.
- dense(double, double...) - Static method in class org.apache.spark.ml.linalg.Vectors
-
Creates a dense vector from its values.
- dense(double, Seq<Object>) - Static method in class org.apache.spark.ml.linalg.Vectors
-
Creates a dense vector from its values.
- dense(double[]) - Static method in class org.apache.spark.ml.linalg.Vectors
-
Creates a dense vector from a double array.
- dense(int, int, double[]) - Static method in class org.apache.spark.mllib.linalg.Matrices
-
Creates a column-major dense matrix.
- dense(double, double...) - Static method in class org.apache.spark.mllib.linalg.Vectors
-
Creates a dense vector from its values.
- dense(double, Seq<Object>) - Static method in class org.apache.spark.mllib.linalg.Vectors
-
Creates a dense vector from its values.
- dense(double[]) - Static method in class org.apache.spark.mllib.linalg.Vectors
-
Creates a dense vector from a double array.
- dense_rank() - Static method in class org.apache.spark.sql.functions
-
Window function: returns the rank of rows within a window partition, without any gaps.
- DenseMatrix - Class in org.apache.spark.ml.linalg
-
Column-major dense matrix.
- DenseMatrix(int, int, double[], boolean) - Constructor for class org.apache.spark.ml.linalg.DenseMatrix
-
- DenseMatrix(int, int, double[]) - Constructor for class org.apache.spark.ml.linalg.DenseMatrix
-
Column-major dense matrix.
- DenseMatrix - Class in org.apache.spark.mllib.linalg
-
Column-major dense matrix.
- DenseMatrix(int, int, double[], boolean) - Constructor for class org.apache.spark.mllib.linalg.DenseMatrix
-
- DenseMatrix(int, int, double[]) - Constructor for class org.apache.spark.mllib.linalg.DenseMatrix
-
Column-major dense matrix.
- DenseVector - Class in org.apache.spark.ml.linalg
-
A dense vector represented by a value array.
- DenseVector(double[]) - Constructor for class org.apache.spark.ml.linalg.DenseVector
-
- DenseVector - Class in org.apache.spark.mllib.linalg
-
A dense vector represented by a value array.
- DenseVector(double[]) - Constructor for class org.apache.spark.mllib.linalg.DenseVector
-
- dependencies() - Static method in class org.apache.spark.api.r.RRDD
-
- dependencies() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- dependencies() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- dependencies() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- dependencies() - Static method in class org.apache.spark.graphx.VertexRDD
-
- dependencies() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- dependencies() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- dependencies() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- dependencies() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- dependencies() - Method in class org.apache.spark.rdd.RDD
-
Get the list of dependencies of this RDD, taking into account whether the
RDD is checkpointed or not.
- dependencies() - Static method in class org.apache.spark.rdd.UnionRDD
-
- dependencies() - Method in class org.apache.spark.streaming.dstream.DStream
-
List of parent DStreams on which this DStream depends on
- dependencies() - Method in class org.apache.spark.streaming.dstream.InputDStream
-
- Dependency<T> - Class in org.apache.spark
-
:: DeveloperApi ::
Base class for dependencies.
- Dependency() - Constructor for class org.apache.spark.Dependency
-
- DEPLOY_MODE - Static variable in class org.apache.spark.launcher.SparkLauncher
-
The Spark deploy mode.
- deployMode() - Method in class org.apache.spark.SparkContext
-
- depth() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- depth() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- depth() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
-
Get depth of tree.
- depth() - Method in class org.apache.spark.util.sketch.CountMinSketch
-
- DerbyDialect - Class in org.apache.spark.sql.jdbc
-
- DerbyDialect() - Constructor for class org.apache.spark.sql.jdbc.DerbyDialect
-
- deriv(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.CLogLog$
-
- deriv(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Identity$
-
- deriv(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Inverse$
-
- deriv(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Log$
-
- deriv(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Logit$
-
- deriv(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Probit$
-
- deriv(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Sqrt$
-
- desc() - Method in class org.apache.spark.serializer.SerializationDebugger.ObjectStreamClassMethods
-
- desc() - Method in class org.apache.spark.sql.Column
-
Returns an ordering used in sorting.
- desc(String) - Static method in class org.apache.spark.sql.functions
-
Returns a sort expression based on the descending order of the column.
- desc() - Method in class org.apache.spark.util.MethodIdentifier
-
- describe(String...) - Method in class org.apache.spark.sql.Dataset
-
Computes statistics for numeric columns, including count, mean, stddev, min, and max.
- describe(Seq<String>) - Method in class org.apache.spark.sql.Dataset
-
Computes statistics for numeric columns, including count, mean, stddev, min, and max.
- describeTopics(int) - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- describeTopics() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- describeTopics(int) - Method in class org.apache.spark.ml.clustering.LDAModel
-
Return the topics described by their top-weighted terms.
- describeTopics() - Method in class org.apache.spark.ml.clustering.LDAModel
-
- describeTopics(int) - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- describeTopics() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- describeTopics(int) - Method in class org.apache.spark.mllib.clustering.DistributedLDAModel
-
- describeTopics(int) - Method in class org.apache.spark.mllib.clustering.LDAModel
-
Return the topics described by weighted terms.
- describeTopics() - Method in class org.apache.spark.mllib.clustering.LDAModel
-
Return the topics described by weighted terms.
- describeTopics(int) - Method in class org.apache.spark.mllib.clustering.LocalLDAModel
-
- description() - Method in class org.apache.spark.ExceptionFailure
-
- description() - Method in class org.apache.spark.sql.catalog.Column
-
- description() - Method in class org.apache.spark.sql.catalog.Database
-
- description() - Method in class org.apache.spark.sql.catalog.Function
-
- description() - Method in class org.apache.spark.sql.catalog.Table
-
- description() - Method in class org.apache.spark.sql.streaming.SinkStatus
-
- description() - Method in class org.apache.spark.sql.streaming.SourceStatus
-
- description() - Method in class org.apache.spark.status.api.v1.JobData
-
- description() - Method in class org.apache.spark.storage.StorageLevel
-
- description() - Method in class org.apache.spark.streaming.scheduler.OutputOperationInfo
-
- description() - Method in class org.apache.spark.ui.jobs.UIData.StageUIData
-
- DeserializationStream - Class in org.apache.spark.serializer
-
:: DeveloperApi ::
A stream for reading serialized objects.
- DeserializationStream() - Constructor for class org.apache.spark.serializer.DeserializationStream
-
- deserialize(Object) - Method in class org.apache.spark.mllib.linalg.VectorUDT
-
- deserialize(ByteBuffer, ClassLoader, ClassTag<T>) - Method in class org.apache.spark.serializer.DummySerializerInstance
-
- deserialize(ByteBuffer, ClassTag<T>) - Method in class org.apache.spark.serializer.DummySerializerInstance
-
- deserialize(ByteBuffer, ClassTag<T>) - Method in class org.apache.spark.serializer.SerializerInstance
-
- deserialize(ByteBuffer, ClassLoader, ClassTag<T>) - Method in class org.apache.spark.serializer.SerializerInstance
-
- deserialize(byte[]) - Static method in class org.apache.spark.util.Utils
-
Deserialize an object using Java serialization
- deserialize(byte[], ClassLoader) - Static method in class org.apache.spark.util.Utils
-
Deserialize an object using Java serialization and the given ClassLoader
- deserialized() - Method in class org.apache.spark.storage.StorageLevel
-
- DeserializedMemoryEntry<T> - Class in org.apache.spark.storage.memory
-
- DeserializedMemoryEntry(Object, long, ClassTag<T>) - Constructor for class org.apache.spark.storage.memory.DeserializedMemoryEntry
-
- deserializeLongValue(byte[]) - Static method in class org.apache.spark.util.Utils
-
Deserialize a Long value (used for PythonPartitioner)
- deserializeStream(InputStream) - Method in class org.apache.spark.serializer.DummySerializerInstance
-
- deserializeStream(InputStream) - Method in class org.apache.spark.serializer.SerializerInstance
-
- deserializeViaNestedStream(InputStream, SerializerInstance, Function1<DeserializationStream, BoxedUnit>) - Static method in class org.apache.spark.util.Utils
-
Deserialize via nested stream using specific serializer
- destroy() - Method in class org.apache.spark.broadcast.Broadcast
-
Destroy all data and metadata related to this broadcast variable.
- details() - Method in class org.apache.spark.scheduler.StageInfo
-
- details() - Method in class org.apache.spark.status.api.v1.StageData
-
- determineBounds(ArrayBuffer<Tuple2<K, Object>>, int, Ordering<K>, ClassTag<K>) - Static method in class org.apache.spark.RangePartitioner
-
Determines the bounds for range partitioning from candidates with weights indicating how many
items each represents.
- deterministic() - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
-
Returns true iff this function is deterministic, i.e.
- deviance(double, double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Binomial$
-
- deviance(double, double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gamma$
-
- deviance(double, double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gaussian$
-
- deviance(double, double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Poisson$
-
- deviance() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
-
The deviance for the fitted model.
- devianceResiduals() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
-
The weighted residuals, the usual residuals rescaled by
the square root of the instance weights.
- dfToCols(Dataset<Row>) - Static method in class org.apache.spark.sql.api.r.SQLUtils
-
- dfToRowRDD(Dataset<Row>) - Static method in class org.apache.spark.sql.api.r.SQLUtils
-
- dgemm(double, DenseMatrix<Object>, DenseMatrix<Object>, double, DenseMatrix<Object>) - Static method in class org.apache.spark.ml.ann.BreezeUtil
-
DGEMM: C := alpha * A * B + beta * C
- dgemv(double, DenseMatrix<Object>, DenseVector<Object>, double, DenseVector<Object>) - Static method in class org.apache.spark.ml.ann.BreezeUtil
-
DGEMV: y := alpha * A * x + beta * y
- diag(Vector) - Static method in class org.apache.spark.ml.linalg.DenseMatrix
-
Generate a diagonal matrix in DenseMatrix format from the supplied values.
- diag(Vector) - Static method in class org.apache.spark.ml.linalg.Matrices
-
Generate a diagonal matrix in Matrix format from the supplied values.
- diag(Vector) - Static method in class org.apache.spark.mllib.linalg.DenseMatrix
-
Generate a diagonal matrix in DenseMatrix format from the supplied values.
- diag(Vector) - Static method in class org.apache.spark.mllib.linalg.Matrices
-
Generate a diagonal matrix in Matrix format from the supplied values.
- diff(RDD<Tuple2<Object, VD>>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- diff(VertexRDD<VD>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- diff(RDD<Tuple2<Object, VD>>) - Method in class org.apache.spark.graphx.VertexRDD
-
For each vertex present in both this and other, diff returns only those vertices with
differing values; for values that are different, keeps the values from other.
- diff(VertexRDD<VD>) - Method in class org.apache.spark.graphx.VertexRDD
-
For each vertex present in both this and other, diff returns only those vertices with
differing values; for values that are different, keeps the values from other.
- diff(GenSeq<B>) - Static method in class org.apache.spark.sql.types.StructType
-
- dir() - Method in class org.apache.spark.mllib.optimization.NNLS.Workspace
-
- disableOutputSpecValidation() - Static method in class org.apache.spark.rdd.PairRDDFunctions
-
Allows for the spark.hadoop.validateOutputSpecs checks to be disabled on a case-by-case
basis; see SPARK-4835 for more details.
- disconnect() - Method in interface org.apache.spark.launcher.SparkAppHandle
-
Disconnects the handle from the application, without stopping it.
- DISK_BYTES_SPILLED() - Static method in class org.apache.spark.InternalAccumulator
-
- DISK_ONLY - Static variable in class org.apache.spark.api.java.StorageLevels
-
- DISK_ONLY() - Static method in class org.apache.spark.storage.StorageLevel
-
- DISK_ONLY_2 - Static variable in class org.apache.spark.api.java.StorageLevels
-
- DISK_ONLY_2() - Static method in class org.apache.spark.storage.StorageLevel
-
- diskBytesSpilled() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
-
- diskBytesSpilled() - Method in class org.apache.spark.status.api.v1.StageData
-
- diskBytesSpilled() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
-
- diskBytesSpilled() - Method in class org.apache.spark.status.api.v1.TaskMetrics
-
- diskBytesSpilled() - Method in class org.apache.spark.ui.jobs.UIData.ExecutorSummary
-
- diskBytesSpilled() - Method in class org.apache.spark.ui.jobs.UIData.StageUIData
-
- diskBytesSpilled() - Method in class org.apache.spark.ui.jobs.UIData.TaskMetricsUIData
-
- diskSize() - Method in class org.apache.spark.storage.BlockManagerMessages.UpdateBlockInfo
-
- diskSize() - Method in class org.apache.spark.storage.BlockStatus
-
- diskSize() - Method in class org.apache.spark.storage.BlockUpdatedInfo
-
- diskSize() - Method in class org.apache.spark.storage.RDDInfo
-
- diskUsed() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
-
- diskUsed() - Method in class org.apache.spark.status.api.v1.RDDDataDistribution
-
- diskUsed() - Method in class org.apache.spark.status.api.v1.RDDPartitionInfo
-
- diskUsed() - Method in class org.apache.spark.status.api.v1.RDDStorageInfo
-
- diskUsed() - Method in class org.apache.spark.storage.StorageStatus
-
Return the disk space used by this block manager.
- diskUsedByRdd(int) - Method in class org.apache.spark.storage.StorageStatus
-
Return the disk space used by the given RDD in this block manager in O(1) time.
- dispersion() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
-
The dispersion of the fitted model.
- dispose(ByteBuffer) - Static method in class org.apache.spark.storage.StorageUtils
-
Attempt to clean up a ByteBuffer if it is memory-mapped.
- distinct() - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Return a new RDD containing the distinct elements in this RDD.
- distinct(int) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Return a new RDD containing the distinct elements in this RDD.
- distinct() - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return a new RDD containing the distinct elements in this RDD.
- distinct(int) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return a new RDD containing the distinct elements in this RDD.
- distinct() - Method in class org.apache.spark.api.java.JavaRDD
-
Return a new RDD containing the distinct elements in this RDD.
- distinct(int) - Method in class org.apache.spark.api.java.JavaRDD
-
Return a new RDD containing the distinct elements in this RDD.
- distinct(int, Ordering<T>) - Static method in class org.apache.spark.api.r.RRDD
-
- distinct() - Static method in class org.apache.spark.api.r.RRDD
-
- distinct(int, Ordering<T>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- distinct() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- distinct(int, Ordering<T>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- distinct() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- distinct(int, Ordering<T>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- distinct() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- distinct(int, Ordering<T>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- distinct() - Static method in class org.apache.spark.graphx.VertexRDD
-
- distinct(int, Ordering<T>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- distinct() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- distinct(int, Ordering<T>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- distinct() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- distinct(int, Ordering<T>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- distinct() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- distinct(int, Ordering<T>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- distinct() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- distinct(int, Ordering<T>) - Method in class org.apache.spark.rdd.RDD
-
Return a new RDD containing the distinct elements in this RDD.
- distinct() - Method in class org.apache.spark.rdd.RDD
-
Return a new RDD containing the distinct elements in this RDD.
- distinct(int, Ordering<T>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- distinct() - Static method in class org.apache.spark.rdd.UnionRDD
-
- distinct() - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset that contains only the unique rows from this Dataset.
- distinct(Column...) - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
-
Creates a Column for this UDAF using the distinct values of the given
Columns as input arguments.
- distinct(Seq<Column>) - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
-
Creates a Column for this UDAF using the distinct values of the given
Columns as input arguments.
- distinct() - Static method in class org.apache.spark.sql.types.StructType
-
- distinct$default$2(int) - Static method in class org.apache.spark.api.r.RRDD
-
- distinct$default$2(int) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- distinct$default$2(int) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- distinct$default$2(int) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- distinct$default$2(int) - Static method in class org.apache.spark.graphx.VertexRDD
-
- distinct$default$2(int) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- distinct$default$2(int) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- distinct$default$2(int) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- distinct$default$2(int) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- distinct$default$2(int) - Static method in class org.apache.spark.rdd.UnionRDD
-
- DistributedLDAModel - Class in org.apache.spark.ml.clustering
-
:: Experimental ::
- DistributedLDAModel - Class in org.apache.spark.mllib.clustering
-
Distributed LDA model.
- DistributedMatrix - Interface in org.apache.spark.mllib.linalg.distributed
-
Represents a distributively stored matrix backed by one or more RDDs.
- div(Decimal, Decimal) - Method in class org.apache.spark.sql.types.Decimal.DecimalIsFractional$
-
- div(Duration) - Method in class org.apache.spark.streaming.Duration
-
- divide(Object) - Method in class org.apache.spark.sql.Column
-
Division this expression by another expression.
- doc() - Static method in class org.apache.spark.ml.param.DoubleParam
-
- doc() - Static method in class org.apache.spark.ml.param.FloatParam
-
- doc() - Method in class org.apache.spark.ml.param.Param
-
- docConcentration() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- docConcentration() - Static method in class org.apache.spark.ml.clustering.LDA
-
- docConcentration() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- docConcentration() - Method in class org.apache.spark.mllib.clustering.DistributedLDAModel
-
- docConcentration() - Method in class org.apache.spark.mllib.clustering.LDAModel
-
Concentration parameter (commonly named "alpha") for the prior placed on documents'
distributions over topics ("theta").
- docConcentration() - Method in class org.apache.spark.mllib.clustering.LocalLDAModel
-
- doesDirectoryContainAnyNewFiles(File, long) - Static method in class org.apache.spark.util.Utils
-
Determines if a directory contains any files newer than cutoff seconds.
- Dot - Class in org.apache.spark.ml.feature
-
- Dot() - Constructor for class org.apache.spark.ml.feature.Dot
-
- dot(Vector, Vector) - Static method in class org.apache.spark.ml.linalg.BLAS
-
dot(x, y)
- dot(Vector, Vector) - Static method in class org.apache.spark.mllib.linalg.BLAS
-
dot(x, y)
- doTest(DStream<Tuple2<StatCounter, StatCounter>>) - Static method in class org.apache.spark.mllib.stat.test.StudentTTest
-
- doTest(DStream<Tuple2<StatCounter, StatCounter>>) - Static method in class org.apache.spark.mllib.stat.test.WelchTTest
-
- DOUBLE() - Static method in class org.apache.spark.sql.Encoders
-
An encoder for nullable double type.
- doubleAccumulator(double) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Deprecated.
use sc().doubleAccumulator(). Since 2.0.0.
- doubleAccumulator(double, String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Deprecated.
use sc().doubleAccumulator(String). Since 2.0.0.
- doubleAccumulator() - Method in class org.apache.spark.SparkContext
-
Create and register a double accumulator, which starts with 0 and accumulates inputs by add.
- doubleAccumulator(String) - Method in class org.apache.spark.SparkContext
-
Create and register a double accumulator, which starts with 0 and accumulates inputs by add.
- DoubleAccumulator - Class in org.apache.spark.util
-
An
accumulator for computing sum, count, and averages for double precision
floating numbers.
- DoubleAccumulator() - Constructor for class org.apache.spark.util.DoubleAccumulator
-
- DoubleArrayParam - Class in org.apache.spark.ml.param
-
:: DeveloperApi ::
Specialized version of Param[Array[Double} for Java.
- DoubleArrayParam(Params, String, String, Function1<double[], Object>) - Constructor for class org.apache.spark.ml.param.DoubleArrayParam
-
- DoubleArrayParam(Params, String, String) - Constructor for class org.apache.spark.ml.param.DoubleArrayParam
-
- DoubleFlatMapFunction<T> - Interface in org.apache.spark.api.java.function
-
A function that returns zero or more records of type Double from each input record.
- DoubleFunction<T> - Interface in org.apache.spark.api.java.function
-
A function that returns Doubles, and can be used to construct DoubleRDDs.
- DoubleParam - Class in org.apache.spark.ml.param
-
:: DeveloperApi ::
Specialized version of Param[Double] for Java.
- DoubleParam(String, String, String, Function1<Object, Object>) - Constructor for class org.apache.spark.ml.param.DoubleParam
-
- DoubleParam(String, String, String) - Constructor for class org.apache.spark.ml.param.DoubleParam
-
- DoubleParam(Identifiable, String, String, Function1<Object, Object>) - Constructor for class org.apache.spark.ml.param.DoubleParam
-
- DoubleParam(Identifiable, String, String) - Constructor for class org.apache.spark.ml.param.DoubleParam
-
- DoubleRDDFunctions - Class in org.apache.spark.rdd
-
Extra functions available on RDDs of Doubles through an implicit conversion.
- DoubleRDDFunctions(RDD<Object>) - Constructor for class org.apache.spark.rdd.DoubleRDDFunctions
-
- doubleRDDToDoubleRDDFunctions(RDD<Object>) - Static method in class org.apache.spark.rdd.RDD
-
- DoubleType - Static variable in class org.apache.spark.sql.types.DataTypes
-
Gets the DoubleType object.
- DoubleType - Class in org.apache.spark.sql.types
-
:: DeveloperApi ::
The data type representing Double values.
- driver() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.SetupDriver
-
- DRIVER_EXTRA_CLASSPATH - Static variable in class org.apache.spark.launcher.SparkLauncher
-
Configuration key for the driver class path.
- DRIVER_EXTRA_JAVA_OPTIONS - Static variable in class org.apache.spark.launcher.SparkLauncher
-
Configuration key for the driver VM options.
- DRIVER_EXTRA_LIBRARY_PATH - Static variable in class org.apache.spark.launcher.SparkLauncher
-
Configuration key for the driver native library path.
- DRIVER_MEMORY - Static variable in class org.apache.spark.launcher.SparkLauncher
-
Configuration key for the driver memory.
- DRIVER_WAL_BATCHING_CONF_KEY() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
-
- DRIVER_WAL_BATCHING_TIMEOUT_CONF_KEY() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
-
- DRIVER_WAL_CLASS_CONF_KEY() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
-
- DRIVER_WAL_CLOSE_AFTER_WRITE_CONF_KEY() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
-
- DRIVER_WAL_MAX_FAILURES_CONF_KEY() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
-
- DRIVER_WAL_ROLLING_INTERVAL_CONF_KEY() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
-
- driverLogs() - Method in class org.apache.spark.scheduler.SparkListenerApplicationStart
-
- drop() - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
Returns a new DataFrame that drops rows containing any null or NaN values.
- drop(String) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
Returns a new DataFrame that drops rows containing null or NaN values.
- drop(String[]) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
Returns a new DataFrame that drops rows containing any null or NaN values
in the specified columns.
- drop(Seq<String>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
(Scala-specific) Returns a new DataFrame that drops rows containing any null or NaN values
in the specified columns.
- drop(String, String[]) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
Returns a new DataFrame that drops rows containing null or NaN values
in the specified columns.
- drop(String, Seq<String>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
(Scala-specific) Returns a new DataFrame that drops rows containing null or NaN values
in the specified columns.
- drop(int) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
Returns a new DataFrame that drops rows containing
less than minNonNulls non-null and non-NaN values.
- drop(int, String[]) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
Returns a new DataFrame that drops rows containing
less than minNonNulls non-null and non-NaN values in the specified columns.
- drop(int, Seq<String>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
(Scala-specific) Returns a new DataFrame that drops rows containing less than
minNonNulls non-null and non-NaN values in the specified columns.
- drop(String...) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset with columns dropped.
- drop(String) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset with a column dropped.
- drop(Seq<String>) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset with columns dropped.
- drop(Column) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset with a column dropped.
- drop(int) - Static method in class org.apache.spark.sql.types.StructType
-
- dropDuplicates(String, String...) - Method in class org.apache.spark.sql.Dataset
-
Returns a new
Dataset with duplicate rows removed, considering only
the subset of columns.
- dropDuplicates() - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset that contains only the unique rows from this Dataset.
- dropDuplicates(Seq<String>) - Method in class org.apache.spark.sql.Dataset
-
(Scala-specific) Returns a new Dataset with duplicate rows removed, considering only
the subset of columns.
- dropDuplicates(String[]) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset with duplicate rows removed, considering only
the subset of columns.
- dropDuplicates(String, Seq<String>) - Method in class org.apache.spark.sql.Dataset
-
Returns a new
Dataset with duplicate rows removed, considering only
the subset of columns.
- dropLast() - Method in class org.apache.spark.ml.feature.OneHotEncoder
-
Whether to drop the last category in the encoded vector (default: true)
- dropRight(int) - Static method in class org.apache.spark.sql.types.StructType
-
- dropTempTable(String) - Method in class org.apache.spark.sql.SQLContext
-
- dropTempView(String) - Method in class org.apache.spark.sql.catalog.Catalog
-
Drops the temporary view with the given view name in the catalog.
- dropTempView(String) - Method in class org.apache.spark.sql.internal.CatalogImpl
-
Drops the temporary view with the given view name in the catalog.
- dropWhile(Function1<A, Object>) - Static method in class org.apache.spark.sql.types.StructType
-
- Dst - Static variable in class org.apache.spark.graphx.TripletFields
-
Expose the destination and edge fields but not the source field.
- dstAttr() - Method in class org.apache.spark.graphx.EdgeContext
-
The vertex attribute of the edge's destination vertex.
- dstAttr() - Method in class org.apache.spark.graphx.EdgeTriplet
-
The destination vertex attribute
- dstAttr() - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
-
- dstId() - Method in class org.apache.spark.graphx.Edge
-
- dstId() - Method in class org.apache.spark.graphx.EdgeContext
-
The vertex id of the edge's destination vertex.
- dstId() - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
-
- dstream() - Method in class org.apache.spark.streaming.api.java.JavaDStream
-
- dstream() - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
- dstream() - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- dstream() - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- dstream() - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- dstream() - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- dstream() - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- DStream<T> - Class in org.apache.spark.streaming.dstream
-
A Discretized Stream (DStream), the basic abstraction in Spark Streaming, is a continuous
sequence of RDDs (of the same type) representing a continuous stream of data (see
org.apache.spark.rdd.RDD in the Spark core documentation for more details on RDDs).
- DStream(StreamingContext, ClassTag<T>) - Constructor for class org.apache.spark.streaming.dstream.DStream
-
- dtypes() - Method in class org.apache.spark.sql.Dataset
-
Returns all column names and their data types as an array.
- DummySerializerInstance - Class in org.apache.spark.serializer
-
Unfortunately, we need a serializer instance in order to construct a DiskBlockObjectWriter.
- duration() - Method in class org.apache.spark.scheduler.TaskInfo
-
- duration() - Method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
-
- Duration - Class in org.apache.spark.streaming
-
- Duration(long) - Constructor for class org.apache.spark.streaming.Duration
-
- duration() - Method in class org.apache.spark.streaming.scheduler.OutputOperationInfo
-
Return the duration of this output operation.
- Durations - Class in org.apache.spark.streaming
-
- Durations() - Constructor for class org.apache.spark.streaming.Durations
-
- f() - Method in class org.apache.spark.sql.expressions.UserDefinedFunction
-
- f1Measure() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
-
Returns document-based f1-measure averaged by the number of documents
- f1Measure(double) - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
-
Returns f1-measure for a given label (category)
- factorial(Column) - Static method in class org.apache.spark.sql.functions
-
Computes the factorial of the given value.
- failed() - Method in class org.apache.spark.scheduler.TaskInfo
-
- FAILED() - Static method in class org.apache.spark.TaskState
-
- failedJobs() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- failedStages() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- failedTasks() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
-
- failedTasks() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
-
- failedTasks() - Method in class org.apache.spark.ui.jobs.UIData.ExecutorSummary
-
- failure(String) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- failureReason() - Method in class org.apache.spark.scheduler.StageInfo
-
If the stage failed, the reason why.
- failureReason() - Method in class org.apache.spark.streaming.scheduler.OutputOperationInfo
-
- failureReasonCell(String, int, boolean) - Static method in class org.apache.spark.streaming.ui.UIUtils
-
- FAIR() - Static method in class org.apache.spark.scheduler.SchedulingMode
-
- FallbackConfigEntry<T> - Class in org.apache.spark.internal.config
-
A config entry whose default value is defined by another config entry.
- FallbackConfigEntry(String, String, boolean, ConfigEntry<T>) - Constructor for class org.apache.spark.internal.config.FallbackConfigEntry
-
- FalsePositiveRate - Class in org.apache.spark.mllib.evaluation.binary
-
False positive rate.
- FalsePositiveRate() - Constructor for class org.apache.spark.mllib.evaluation.binary.FalsePositiveRate
-
- falsePositiveRate(double) - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
-
Returns false positive rate for a given label (category)
- family() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- family() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- fastEquals(TreeNode<?>) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- fastEquals(TreeNode<?>) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- fastEquals(TreeNode<?>) - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- feature() - Method in class org.apache.spark.mllib.feature.ChiSqSelectorModel.SaveLoadV1_0$.Data
-
- feature() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.SplitData
-
- feature() - Method in class org.apache.spark.mllib.tree.model.Split
-
- featureImportances() - Method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
Estimate of the importance of each feature.
- featureImportances() - Method in class org.apache.spark.ml.classification.GBTClassificationModel
-
Estimate of the importance of each feature.
- featureImportances() - Method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
Estimate of the importance of each feature.
- featureImportances() - Method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
Estimate of the importance of each feature.
- featureImportances() - Method in class org.apache.spark.ml.regression.GBTRegressionModel
-
Estimate of the importance of each feature.
- featureImportances() - Method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
Estimate of the importance of each feature.
- featureIndex() - Static method in class org.apache.spark.ml.regression.IsotonicRegression
-
- featureIndex() - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- featureIndex() - Method in class org.apache.spark.ml.tree.CategoricalSplit
-
- featureIndex() - Method in class org.apache.spark.ml.tree.ContinuousSplit
-
- featureIndex() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.SplitData
-
- featureIndex() - Method in interface org.apache.spark.ml.tree.Split
-
Index of feature which this split tests
- features() - Method in class org.apache.spark.ml.feature.LabeledPoint
-
- features() - Method in class org.apache.spark.mllib.regression.LabeledPoint
-
- featuresCol() - Method in class org.apache.spark.ml.classification.BinaryLogisticRegressionSummary
-
- featuresCol() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- featuresCol() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- featuresCol() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- featuresCol() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- featuresCol() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- featuresCol() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- featuresCol() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
-
Field in "predictions" which gives the features of each instance as a vector.
- featuresCol() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- featuresCol() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- featuresCol() - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- featuresCol() - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- featuresCol() - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- featuresCol() - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- featuresCol() - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- featuresCol() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- featuresCol() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- featuresCol() - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- featuresCol() - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- featuresCol() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- featuresCol() - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- featuresCol() - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- featuresCol() - Method in class org.apache.spark.ml.clustering.GaussianMixtureSummary
-
- featuresCol() - Static method in class org.apache.spark.ml.clustering.KMeans
-
- featuresCol() - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- featuresCol() - Method in class org.apache.spark.ml.clustering.KMeansSummary
-
- featuresCol() - Static method in class org.apache.spark.ml.clustering.LDA
-
- featuresCol() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- featuresCol() - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- featuresCol() - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- featuresCol() - Static method in class org.apache.spark.ml.feature.RFormula
-
- featuresCol() - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- featuresCol() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- featuresCol() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- featuresCol() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- featuresCol() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- featuresCol() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- featuresCol() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- featuresCol() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- featuresCol() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- featuresCol() - Static method in class org.apache.spark.ml.regression.IsotonicRegression
-
- featuresCol() - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- featuresCol() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- featuresCol() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- featuresCol() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
-
- featuresCol() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- featuresCol() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- featureSubsetStrategy() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- featureSubsetStrategy() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- featureSubsetStrategy() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- featureSubsetStrategy() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- FeatureType - Class in org.apache.spark.mllib.tree.configuration
-
Enum to describe whether a feature is "continuous" or "categorical"
- FeatureType() - Constructor for class org.apache.spark.mllib.tree.configuration.FeatureType
-
- featureType() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.SplitData
-
- featureType() - Method in class org.apache.spark.mllib.tree.model.Split
-
- FETCH_WAIT_TIME() - Method in class org.apache.spark.InternalAccumulator.shuffleRead$
-
- FetchFailed - Class in org.apache.spark
-
:: DeveloperApi ::
Task failed to fetch shuffle data from a remote node.
- FetchFailed(BlockManagerId, int, int, int, String) - Constructor for class org.apache.spark.FetchFailed
-
- fetchFile(String, File, SparkConf, org.apache.spark.SecurityManager, Configuration, long, boolean) - Static method in class org.apache.spark.util.Utils
-
Download a file or directory to target directory.
- fetchPct() - Method in class org.apache.spark.scheduler.RuntimePercentage
-
- fetchWaitTime() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetricDistributions
-
- fetchWaitTime() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetrics
-
- fetchWaitTime() - Method in class org.apache.spark.ui.jobs.UIData.ShuffleReadMetricsUIData
-
- field() - Method in class org.apache.spark.storage.BroadcastBlockId
-
- fieldIndex(String) - Method in interface org.apache.spark.sql.Row
-
Returns the index of a given field name.
- fieldIndex(String) - Method in class org.apache.spark.sql.types.StructType
-
Returns the index of a given field.
- fieldNames() - Method in class org.apache.spark.sql.types.StructType
-
Returns all field names in an array.
- fields() - Method in class org.apache.spark.sql.types.StructType
-
- FIFO() - Static method in class org.apache.spark.scheduler.SchedulingMode
-
- files() - Method in class org.apache.spark.SparkContext
-
- fileStream(String, Class<K>, Class<V>, Class<F>) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Create an input stream that monitors a Hadoop-compatible filesystem
for new files and reads them using the given key-value types and input format.
- fileStream(String, Class<K>, Class<V>, Class<F>, Function<Path, Boolean>, boolean) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Create an input stream that monitors a Hadoop-compatible filesystem
for new files and reads them using the given key-value types and input format.
- fileStream(String, Class<K>, Class<V>, Class<F>, Function<Path, Boolean>, boolean, Configuration) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Create an input stream that monitors a Hadoop-compatible filesystem
for new files and reads them using the given key-value types and input format.
- fileStream(String, ClassTag<K>, ClassTag<V>, ClassTag<F>) - Method in class org.apache.spark.streaming.StreamingContext
-
Create an input stream that monitors a Hadoop-compatible filesystem
for new files and reads them using the given key-value types and input format.
- fileStream(String, Function1<Path, Object>, boolean, ClassTag<K>, ClassTag<V>, ClassTag<F>) - Method in class org.apache.spark.streaming.StreamingContext
-
Create an input stream that monitors a Hadoop-compatible filesystem
for new files and reads them using the given key-value types and input format.
- fileStream(String, Function1<Path, Object>, boolean, Configuration, ClassTag<K>, ClassTag<V>, ClassTag<F>) - Method in class org.apache.spark.streaming.StreamingContext
-
Create an input stream that monitors a Hadoop-compatible filesystem
for new files and reads them using the given key-value types and input format.
- fill(double) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
Returns a new DataFrame that replaces null or NaN values in numeric columns with value.
- fill(String) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
Returns a new DataFrame that replaces null values in string columns with value.
- fill(double, String[]) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
Returns a new DataFrame that replaces null or NaN values in specified numeric columns.
- fill(double, Seq<String>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
(Scala-specific) Returns a new DataFrame that replaces null or NaN values in specified
numeric columns.
- fill(String, String[]) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
Returns a new DataFrame that replaces null values in specified string columns.
- fill(String, Seq<String>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
(Scala-specific) Returns a new DataFrame that replaces null values in
specified string columns.
- fill(Map<String, Object>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
Returns a new DataFrame that replaces null values.
- fill(Map<String, Object>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
(Scala-specific) Returns a new DataFrame that replaces null values.
- fillInStackTrace() - Static method in exception org.apache.spark.sql.AnalysisException
-
- fillInStackTrace() - Static method in exception org.apache.spark.sql.streaming.StreamingQueryException
-
- filter(Function<Double, Boolean>) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Return a new RDD containing only the elements that satisfy a predicate.
- filter(Function<Tuple2<K, V>, Boolean>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return a new RDD containing only the elements that satisfy a predicate.
- filter(Function<T, Boolean>) - Method in class org.apache.spark.api.java.JavaRDD
-
Return a new RDD containing only the elements that satisfy a predicate.
- filter(Function1<T, Object>) - Static method in class org.apache.spark.api.r.RRDD
-
- filter(Function1<T, Object>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- filter(Function1<Graph<VD, ED>, Graph<VD2, ED2>>, Function1<EdgeTriplet<VD2, ED2>, Object>, Function2<Object, VD2, Object>, ClassTag<VD2>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.GraphOps
-
Filter the graph by computing some values to filter on, and applying the predicates.
- filter(Function1<EdgeTriplet<VD, ED>, Object>, Function2<Object, VD, Object>) - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- filter(Function1<Tuple2<Object, VD>, Object>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- filter(Function1<Tuple2<Object, VD>, Object>) - Method in class org.apache.spark.graphx.VertexRDD
-
Restricts the vertex set to the set of vertices satisfying the given predicate.
- filter(Params) - Method in class org.apache.spark.ml.param.ParamMap
-
Filters this param map for the given parent.
- filter(Function1<T, Object>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- filter(Function1<T, Object>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- filter(Function1<T, Object>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- filter(Function1<T, Object>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- filter(Function1<T, Object>) - Method in class org.apache.spark.rdd.RDD
-
Return a new RDD containing only the elements that satisfy a predicate.
- filter(Function1<T, Object>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- filter(Column) - Method in class org.apache.spark.sql.Dataset
-
Filters rows using the given condition.
- filter(String) - Method in class org.apache.spark.sql.Dataset
-
Filters rows using the given SQL expression.
- filter(Function1<T, Object>) - Method in class org.apache.spark.sql.Dataset
-
:: Experimental ::
(Scala-specific)
Returns a new Dataset that only contains elements where func returns true.
- filter(FilterFunction<T>) - Method in class org.apache.spark.sql.Dataset
-
:: Experimental ::
(Java-specific)
Returns a new Dataset that only contains elements where func returns true.
- Filter - Class in org.apache.spark.sql.sources
-
A filter predicate for data sources.
- Filter() - Constructor for class org.apache.spark.sql.sources.Filter
-
- filter(Function1<A, Object>) - Static method in class org.apache.spark.sql.types.StructType
-
- filter() - Method in class org.apache.spark.storage.BlockManagerMessages.GetMatchingBlockIds
-
- filter(Function<T, Boolean>) - Method in class org.apache.spark.streaming.api.java.JavaDStream
-
Return a new DStream containing only the elements that satisfy a predicate.
- filter(Function<T, Boolean>) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- filter(Function<Tuple2<K, V>, Boolean>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream containing only the elements that satisfy a predicate.
- filter(Function<Tuple2<K, V>, Boolean>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- filter(Function<Tuple2<K, V>, Boolean>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- filter(Function<T, Boolean>) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- filter(Function1<T, Object>) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream containing only the elements that satisfy a predicate.
- filterByRange(K, K) - Method in class org.apache.spark.rdd.OrderedRDDFunctions
-
Returns an RDD containing only the elements in the inclusive range lower to upper.
- FilterFunction<T> - Interface in org.apache.spark.api.java.function
-
Base interface for a function used in Dataset's filter function.
- filterName() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.AddWebUIFilter
-
- filterNot(Function1<A, Object>) - Static method in class org.apache.spark.sql.types.StructType
-
- filterParams() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.AddWebUIFilter
-
- finalStorageLevel() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- find(Function1<BaseType, Object>) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- find(Function1<BaseType, Object>) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- find(Function1<BaseType, Object>) - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- find(Function1<A, Object>) - Static method in class org.apache.spark.sql.types.StructType
-
- findLeader(String, int) - Method in class org.apache.spark.streaming.kafka.KafkaCluster
-
- findLeaders(Set<TopicAndPartition>) - Method in class org.apache.spark.streaming.kafka.KafkaCluster
-
- findSynonyms(String, int) - Method in class org.apache.spark.ml.feature.Word2VecModel
-
Find "num" number of words closest in similarity to the given word, not
including the word itself.
- findSynonyms(Vector, int) - Method in class org.apache.spark.ml.feature.Word2VecModel
-
Find "num" number of words whose vector representation most similar to the supplied vector.
- findSynonyms(String, int) - Method in class org.apache.spark.mllib.feature.Word2VecModel
-
Find synonyms of a word; do not include the word itself in results.
- findSynonyms(Vector, int) - Method in class org.apache.spark.mllib.feature.Word2VecModel
-
Find synonyms of the vector representation of a word, possibly
including any words in the model vocabulary whose vector respresentation
is the supplied vector.
- finish(BUF) - Method in class org.apache.spark.sql.expressions.Aggregator
-
Transform the output of the reduction.
- finished() - Method in class org.apache.spark.scheduler.TaskInfo
-
- FINISHED() - Static method in class org.apache.spark.TaskState
-
- FINISHED_STATES() - Static method in class org.apache.spark.TaskState
-
- finishReason() - Method in class org.apache.spark.ui.jobs.UIData.ExecutorUIData
-
- finishTime() - Method in class org.apache.spark.scheduler.TaskInfo
-
The time when the task has completed successfully (including the time to remotely fetch
results, if necessary).
- finishTime() - Method in class org.apache.spark.ui.jobs.UIData.ExecutorUIData
-
- first() - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
- first() - Method in class org.apache.spark.api.java.JavaPairRDD
-
- first() - Static method in class org.apache.spark.api.java.JavaRDD
-
- first() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return the first element in this RDD.
- first() - Static method in class org.apache.spark.api.r.RRDD
-
- first() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- first() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- first() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- first() - Static method in class org.apache.spark.graphx.VertexRDD
-
- first() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- first() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- first() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- first() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- first() - Method in class org.apache.spark.rdd.RDD
-
Return the first element in this RDD.
- first() - Static method in class org.apache.spark.rdd.UnionRDD
-
- first() - Method in class org.apache.spark.sql.Dataset
-
Returns the first row.
- first(Column, boolean) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the first value in a group.
- first(String, boolean) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the first value of a column in a group.
- first(Column) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the first value in a group.
- first(String) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the first value of a column in a group.
- firstTaskLaunchedTime() - Method in class org.apache.spark.status.api.v1.StageData
-
- fit(Dataset<?>, ParamPair<?>, Seq<ParamPair<?>>) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- fit(Dataset<?>, ParamMap) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- fit(Dataset<?>, ParamMap[]) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- fit(Dataset<?>, ParamPair<?>, ParamPair<?>...) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- fit(Dataset<?>) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- fit(Dataset<?>, ParamPair<?>, Seq<ParamPair<?>>) - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- fit(Dataset<?>, ParamMap) - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- fit(Dataset<?>, ParamMap[]) - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- fit(Dataset<?>, ParamPair<?>, ParamPair<?>...) - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- fit(Dataset<?>) - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- fit(Dataset<?>, ParamPair<?>, Seq<ParamPair<?>>) - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- fit(Dataset<?>, ParamMap) - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- fit(Dataset<?>, ParamMap[]) - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- fit(Dataset<?>, ParamPair<?>, ParamPair<?>...) - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- fit(Dataset<?>) - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- fit(Dataset<?>, ParamPair<?>, Seq<ParamPair<?>>) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- fit(Dataset<?>, ParamMap) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- fit(Dataset<?>, ParamMap[]) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- fit(Dataset<?>, ParamPair<?>, ParamPair<?>...) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- fit(Dataset<?>) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- fit(Dataset<?>, ParamPair<?>, Seq<ParamPair<?>>) - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- fit(Dataset<?>, ParamMap) - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- fit(Dataset<?>, ParamMap[]) - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- fit(Dataset<?>, ParamPair<?>, ParamPair<?>...) - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- fit(Dataset<?>) - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- fit(Dataset<?>) - Method in class org.apache.spark.ml.classification.OneVsRest
-
- fit(Dataset<?>, ParamPair<?>, Seq<ParamPair<?>>) - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- fit(Dataset<?>, ParamMap) - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- fit(Dataset<?>, ParamMap[]) - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- fit(Dataset<?>, ParamPair<?>, ParamPair<?>...) - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- fit(Dataset<?>) - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- fit(Dataset<?>) - Method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- fit(Dataset<?>) - Method in class org.apache.spark.ml.clustering.GaussianMixture
-
- fit(Dataset<?>) - Method in class org.apache.spark.ml.clustering.KMeans
-
- fit(Dataset<?>) - Method in class org.apache.spark.ml.clustering.LDA
-
- fit(Dataset<?>, ParamPair<?>, ParamPair<?>...) - Method in class org.apache.spark.ml.Estimator
-
Fits a single model to the input data with optional parameters.
- fit(Dataset<?>, ParamPair<?>, Seq<ParamPair<?>>) - Method in class org.apache.spark.ml.Estimator
-
Fits a single model to the input data with optional parameters.
- fit(Dataset<?>, ParamMap) - Method in class org.apache.spark.ml.Estimator
-
Fits a single model to the input data with provided parameter map.
- fit(Dataset<?>) - Method in class org.apache.spark.ml.Estimator
-
Fits a model to the input data.
- fit(Dataset<?>, ParamMap[]) - Method in class org.apache.spark.ml.Estimator
-
Fits multiple models to the input data with multiple sets of parameters.
- fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.ChiSqSelector
-
- fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.CountVectorizer
-
- fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.IDF
-
- fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.MaxAbsScaler
-
- fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.MinMaxScaler
-
- fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.PCA
-
Computes a
PCAModel that contains the principal components of the input vectors.
- fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.RFormula
-
- fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.StandardScaler
-
- fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.StringIndexer
-
- fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.VectorIndexer
-
- fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.Word2Vec
-
- fit(Dataset<?>) - Method in class org.apache.spark.ml.Pipeline
-
Fits the pipeline to the input dataset with additional parameters.
- fit(Dataset<?>) - Method in class org.apache.spark.ml.Predictor
-
- fit(Dataset<?>) - Method in class org.apache.spark.ml.recommendation.ALS
-
- fit(Dataset<?>) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- fit(Dataset<?>, ParamPair<?>, Seq<ParamPair<?>>) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- fit(Dataset<?>, ParamMap) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- fit(Dataset<?>, ParamMap[]) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- fit(Dataset<?>, ParamPair<?>, ParamPair<?>...) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- fit(Dataset<?>) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- fit(Dataset<?>, ParamPair<?>, Seq<ParamPair<?>>) - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- fit(Dataset<?>, ParamMap) - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- fit(Dataset<?>, ParamMap[]) - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- fit(Dataset<?>, ParamPair<?>, ParamPair<?>...) - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- fit(Dataset<?>) - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- fit(Dataset<?>, ParamPair<?>, Seq<ParamPair<?>>) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- fit(Dataset<?>, ParamMap) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- fit(Dataset<?>, ParamMap[]) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- fit(Dataset<?>, ParamPair<?>, ParamPair<?>...) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- fit(Dataset<?>) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- fit(Dataset<?>) - Method in class org.apache.spark.ml.regression.IsotonicRegression
-
- fit(Dataset<?>, ParamPair<?>, Seq<ParamPair<?>>) - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- fit(Dataset<?>, ParamMap) - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- fit(Dataset<?>, ParamMap[]) - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- fit(Dataset<?>, ParamPair<?>, ParamPair<?>...) - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- fit(Dataset<?>) - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- fit(Dataset<?>, ParamPair<?>, Seq<ParamPair<?>>) - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- fit(Dataset<?>, ParamMap) - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- fit(Dataset<?>, ParamMap[]) - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- fit(Dataset<?>, ParamPair<?>, ParamPair<?>...) - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- fit(Dataset<?>) - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- fit(Dataset<?>) - Method in class org.apache.spark.ml.tuning.CrossValidator
-
- fit(Dataset<?>) - Method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- fit(RDD<LabeledPoint>) - Method in class org.apache.spark.mllib.feature.ChiSqSelector
-
Returns a ChiSquared feature selector.
- fit(RDD<Vector>) - Method in class org.apache.spark.mllib.feature.IDF
-
Computes the inverse document frequency.
- fit(JavaRDD<Vector>) - Method in class org.apache.spark.mllib.feature.IDF
-
Computes the inverse document frequency.
- fit(RDD<Vector>) - Method in class org.apache.spark.mllib.feature.PCA
-
Computes a
PCAModel that contains the principal components of the input vectors.
- fit(JavaRDD<Vector>) - Method in class org.apache.spark.mllib.feature.PCA
-
Java-friendly version of fit().
- fit(RDD<Vector>) - Method in class org.apache.spark.mllib.feature.StandardScaler
-
Computes the mean and variance and stores as a model to be used for later scaling.
- fit(RDD<S>) - Method in class org.apache.spark.mllib.feature.Word2Vec
-
Computes the vector representation of each word in vocabulary.
- fit(JavaRDD<S>) - Method in class org.apache.spark.mllib.feature.Word2Vec
-
Computes the vector representation of each word in vocabulary (Java version).
- fitIntercept() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- fitIntercept() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- fitIntercept() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- fitIntercept() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- fitIntercept() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- fitIntercept() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- fitIntercept() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- fitIntercept() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- flatMap(FlatMapFunction<T, U>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- flatMap(FlatMapFunction<T, U>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- flatMap(FlatMapFunction<T, U>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- flatMap(FlatMapFunction<T, U>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by first applying a function to all elements of this
RDD, and then flattening the results.
- flatMap(Function1<T, TraversableOnce<U>>, ClassTag<U>) - Static method in class org.apache.spark.api.r.RRDD
-
- flatMap(Function1<T, TraversableOnce<U>>, ClassTag<U>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- flatMap(Function1<T, TraversableOnce<U>>, ClassTag<U>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- flatMap(Function1<T, TraversableOnce<U>>, ClassTag<U>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- flatMap(Function1<T, TraversableOnce<U>>, ClassTag<U>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- flatMap(Function1<T, TraversableOnce<U>>, ClassTag<U>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- flatMap(Function1<T, TraversableOnce<U>>, ClassTag<U>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- flatMap(Function1<T, TraversableOnce<U>>, ClassTag<U>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- flatMap(Function1<T, TraversableOnce<U>>, ClassTag<U>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- flatMap(Function1<T, TraversableOnce<U>>, ClassTag<U>) - Method in class org.apache.spark.rdd.RDD
-
Return a new RDD by first applying a function to all elements of this
RDD, and then flattening the results.
- flatMap(Function1<T, TraversableOnce<U>>, ClassTag<U>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- flatMap(Function1<T, TraversableOnce<U>>, Encoder<U>) - Method in class org.apache.spark.sql.Dataset
-
:: Experimental ::
(Scala-specific)
Returns a new Dataset by first applying a function to all elements of this Dataset,
and then flattening the results.
- flatMap(FlatMapFunction<T, U>, Encoder<U>) - Method in class org.apache.spark.sql.Dataset
-
:: Experimental ::
(Java-specific)
Returns a new Dataset by first applying a function to all elements of this Dataset,
and then flattening the results.
- flatMap(Function1<BaseType, TraversableOnce<A>>) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- flatMap(Function1<BaseType, TraversableOnce<A>>) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- flatMap(Function1<BaseType, TraversableOnce<A>>) - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- flatMap(Function1<A, GenTraversableOnce<B>>, CanBuildFrom<Repr, B, That>) - Static method in class org.apache.spark.sql.types.StructType
-
- flatMap(FlatMapFunction<T, U>) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- flatMap(FlatMapFunction<T, U>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream by applying a function to all elements of this DStream,
and then flattening the results
- flatMap(FlatMapFunction<T, U>) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- flatMap(FlatMapFunction<T, U>) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- flatMap(FlatMapFunction<T, U>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- flatMap(FlatMapFunction<T, U>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- flatMap(FlatMapFunction<T, U>) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- flatMap(Function1<T, TraversableOnce<U>>, ClassTag<U>) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream by applying a function to all elements of this DStream,
and then flattening the results
- FlatMapFunction<T,R> - Interface in org.apache.spark.api.java.function
-
A function that returns zero or more output records from each input record.
- FlatMapFunction2<T1,T2,R> - Interface in org.apache.spark.api.java.function
-
A function that takes two inputs and returns zero or more output records.
- flatMapGroups(Function2<K, Iterator<V>, TraversableOnce<U>>, Encoder<U>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
-
Applies the given function to each group of data.
- flatMapGroups(FlatMapGroupsFunction<K, V, U>, Encoder<U>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
-
Applies the given function to each group of data.
- FlatMapGroupsFunction<K,V,R> - Interface in org.apache.spark.api.java.function
-
A function that returns zero or more output records from each grouping key and its values.
- flatMapToDouble(DoubleFlatMapFunction<T>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- flatMapToDouble(DoubleFlatMapFunction<T>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- flatMapToDouble(DoubleFlatMapFunction<T>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- flatMapToDouble(DoubleFlatMapFunction<T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by first applying a function to all elements of this
RDD, and then flattening the results.
- flatMapToPair(PairFlatMapFunction<T, K2, V2>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- flatMapToPair(PairFlatMapFunction<T, K2, V2>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- flatMapToPair(PairFlatMapFunction<T, K2, V2>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- flatMapToPair(PairFlatMapFunction<T, K2, V2>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by first applying a function to all elements of this
RDD, and then flattening the results.
- flatMapToPair(PairFlatMapFunction<T, K2, V2>) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- flatMapToPair(PairFlatMapFunction<T, K2, V2>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream by applying a function to all elements of this DStream,
and then flattening the results
- flatMapToPair(PairFlatMapFunction<T, K2, V2>) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- flatMapToPair(PairFlatMapFunction<T, K2, V2>) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- flatMapToPair(PairFlatMapFunction<T, K2, V2>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- flatMapToPair(PairFlatMapFunction<T, K2, V2>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- flatMapToPair(PairFlatMapFunction<T, K2, V2>) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- flatMapValues(Function<V, Iterable<U>>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Pass each value in the key-value pair RDD through a flatMap function without changing the
keys; this also retains the original RDD's partitioning.
- flatMapValues(Function1<V, TraversableOnce<U>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Pass each value in the key-value pair RDD through a flatMap function without changing the
keys; this also retains the original RDD's partitioning.
- flatMapValues(Function<V, Iterable<U>>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying a flatmap function to the value of each key-value pairs in
'this' DStream without changing the key.
- flatMapValues(Function<V, Iterable<U>>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- flatMapValues(Function<V, Iterable<U>>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- flatMapValues(Function1<V, TraversableOnce<U>>, ClassTag<U>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying a flatmap function to the value of each key-value pairs in
'this' DStream without changing the key.
- flatten(Function1<A, GenTraversableOnce<B>>) - Static method in class org.apache.spark.sql.types.StructType
-
- FLOAT() - Static method in class org.apache.spark.sql.Encoders
-
An encoder for nullable float type.
- FloatParam - Class in org.apache.spark.ml.param
-
:: DeveloperApi ::
Specialized version of Param[Float] for Java.
- FloatParam(String, String, String, Function1<Object, Object>) - Constructor for class org.apache.spark.ml.param.FloatParam
-
- FloatParam(String, String, String) - Constructor for class org.apache.spark.ml.param.FloatParam
-
- FloatParam(Identifiable, String, String, Function1<Object, Object>) - Constructor for class org.apache.spark.ml.param.FloatParam
-
- FloatParam(Identifiable, String, String) - Constructor for class org.apache.spark.ml.param.FloatParam
-
- FloatType - Static variable in class org.apache.spark.sql.types.DataTypes
-
Gets the FloatType object.
- FloatType - Class in org.apache.spark.sql.types
-
:: DeveloperApi ::
The data type representing Float values.
- floor(Column) - Static method in class org.apache.spark.sql.functions
-
Computes the floor of the given value.
- floor(String) - Static method in class org.apache.spark.sql.functions
-
Computes the floor of the given column.
- floor() - Method in class org.apache.spark.sql.types.Decimal
-
- floor(Duration) - Method in class org.apache.spark.streaming.Time
-
- floor(Duration, Time) - Method in class org.apache.spark.streaming.Time
-
- FlumeUtils - Class in org.apache.spark.streaming.flume
-
- FlumeUtils() - Constructor for class org.apache.spark.streaming.flume.FlumeUtils
-
- flush() - Method in class org.apache.spark.io.SnappyOutputStreamWrapper
-
- flush() - Method in class org.apache.spark.serializer.SerializationStream
-
- flush() - Method in class org.apache.spark.storage.TimeTrackingOutputStream
-
- fMeasure(double, double) - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
-
Returns f-measure for a given label (category)
- fMeasure(double) - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
-
Returns f1-measure for a given label (category)
- fMeasure() - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
-
Deprecated.
Use accuracy. Since 2.0.0.
- fMeasureByThreshold() - Method in class org.apache.spark.ml.classification.BinaryLogisticRegressionSummary
-
Returns a dataframe with two fields (threshold, F-Measure) curve with beta = 1.0.
- fMeasureByThreshold(double) - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
-
Returns the (threshold, F-Measure) curve.
- fMeasureByThreshold() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
-
Returns the (threshold, F-Measure) curve with beta = 1.0.
- fold(T, Function2<T, T, T>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- fold(T, Function2<T, T, T>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- fold(T, Function2<T, T, T>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- fold(T, Function2<T, T, T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Aggregate the elements of each partition, and then the results for all the partitions, using a
given associative function and a neutral "zero value".
- fold(T, Function2<T, T, T>) - Static method in class org.apache.spark.api.r.RRDD
-
- fold(T, Function2<T, T, T>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- fold(T, Function2<T, T, T>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- fold(T, Function2<T, T, T>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- fold(T, Function2<T, T, T>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- fold(T, Function2<T, T, T>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- fold(T, Function2<T, T, T>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- fold(T, Function2<T, T, T>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- fold(T, Function2<T, T, T>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- fold(T, Function2<T, T, T>) - Method in class org.apache.spark.rdd.RDD
-
Aggregate the elements of each partition, and then the results for all the partitions, using a
given associative function and a neutral "zero value".
- fold(T, Function2<T, T, T>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- fold(A1, Function2<A1, A1, A1>) - Static method in class org.apache.spark.sql.types.StructType
-
- foldByKey(V, Partitioner, Function2<V, V, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Merge the values for each key using an associative function and a neutral "zero value" which
may be added to the result an arbitrary number of times, and must not change the result
(e.g ., Nil for list concatenation, 0 for addition, or 1 for multiplication.).
- foldByKey(V, int, Function2<V, V, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Merge the values for each key using an associative function and a neutral "zero value" which
may be added to the result an arbitrary number of times, and must not change the result
(e.g ., Nil for list concatenation, 0 for addition, or 1 for multiplication.).
- foldByKey(V, Function2<V, V, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Merge the values for each key using an associative function and a neutral "zero value"
which may be added to the result an arbitrary number of times, and must not change the result
(e.g., Nil for list concatenation, 0 for addition, or 1 for multiplication.).
- foldByKey(V, Partitioner, Function2<V, V, V>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Merge the values for each key using an associative function and a neutral "zero value" which
may be added to the result an arbitrary number of times, and must not change the result
(e.g., Nil for list concatenation, 0 for addition, or 1 for multiplication.).
- foldByKey(V, int, Function2<V, V, V>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Merge the values for each key using an associative function and a neutral "zero value" which
may be added to the result an arbitrary number of times, and must not change the result
(e.g., Nil for list concatenation, 0 for addition, or 1 for multiplication.).
- foldByKey(V, Function2<V, V, V>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Merge the values for each key using an associative function and a neutral "zero value" which
may be added to the result an arbitrary number of times, and must not change the result
(e.g., Nil for list concatenation, 0 for addition, or 1 for multiplication.).
- foldLeft(B, Function2<B, A, B>) - Static method in class org.apache.spark.sql.types.StructType
-
- foldRight(B, Function2<A, B, B>) - Static method in class org.apache.spark.sql.types.StructType
-
- forall(Function1<A, Object>) - Static method in class org.apache.spark.sql.types.StructType
-
- foreach(VoidFunction<T>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- foreach(VoidFunction<T>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- foreach(VoidFunction<T>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- foreach(VoidFunction<T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Applies a function f to all elements of this RDD.
- foreach(Function1<T, BoxedUnit>) - Static method in class org.apache.spark.api.r.RRDD
-
- foreach(Function1<T, BoxedUnit>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- foreach(Function1<T, BoxedUnit>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- foreach(Function1<T, BoxedUnit>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- foreach(Function1<T, BoxedUnit>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- foreach(Function1<T, BoxedUnit>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- foreach(Function1<T, BoxedUnit>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- foreach(Function1<T, BoxedUnit>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- foreach(Function1<T, BoxedUnit>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- foreach(Function1<T, BoxedUnit>) - Method in class org.apache.spark.rdd.RDD
-
Applies a function f to all elements of this RDD.
- foreach(Function1<T, BoxedUnit>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- foreach(Function1<T, BoxedUnit>) - Method in class org.apache.spark.sql.Dataset
-
Applies a function f to all rows.
- foreach(ForeachFunction<T>) - Method in class org.apache.spark.sql.Dataset
-
(Java-specific)
Runs func on each element of this Dataset.
- foreach(Function1<BaseType, BoxedUnit>) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- foreach(Function1<BaseType, BoxedUnit>) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- foreach(Function1<BaseType, BoxedUnit>) - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- foreach(ForeachWriter<T>) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
-
:: Experimental ::
Starts the execution of the streaming query, which will continually send results to the given
ForeachWriter as as new data arrives.
- foreach(Function1<A, U>) - Static method in class org.apache.spark.sql.types.StructType
-
- foreach(Function1<A, U>) - Static method in class org.apache.spark.sql.types.StructType
-
- foreachActive(Function2<Object, Object, BoxedUnit>) - Method in class org.apache.spark.ml.linalg.DenseVector
-
- foreachActive(Function3<Object, Object, Object, BoxedUnit>) - Method in interface org.apache.spark.ml.linalg.Matrix
-
Applies a function f to all the active elements of dense and sparse matrix.
- foreachActive(Function2<Object, Object, BoxedUnit>) - Method in class org.apache.spark.ml.linalg.SparseVector
-
- foreachActive(Function2<Object, Object, BoxedUnit>) - Method in interface org.apache.spark.ml.linalg.Vector
-
Applies a function f to all the active elements of dense and sparse vector.
- foreachActive(Function2<Object, Object, BoxedUnit>) - Method in class org.apache.spark.mllib.linalg.DenseVector
-
- foreachActive(Function3<Object, Object, Object, BoxedUnit>) - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Applies a function f to all the active elements of dense and sparse matrix.
- foreachActive(Function2<Object, Object, BoxedUnit>) - Method in class org.apache.spark.mllib.linalg.SparseVector
-
- foreachActive(Function2<Object, Object, BoxedUnit>) - Method in interface org.apache.spark.mllib.linalg.Vector
-
Applies a function f to all the active elements of dense and sparse vector.
- foreachAsync(VoidFunction<T>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- foreachAsync(VoidFunction<T>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- foreachAsync(VoidFunction<T>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- foreachAsync(VoidFunction<T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
The asynchronous version of the foreach action, which
applies a function f to all the elements of this RDD.
- foreachAsync(Function1<T, BoxedUnit>) - Method in class org.apache.spark.rdd.AsyncRDDActions
-
Applies a function f to all elements of this RDD.
- ForeachFunction<T> - Interface in org.apache.spark.api.java.function
-
Base interface for a function used in Dataset's foreach function.
- foreachPartition(VoidFunction<Iterator<T>>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- foreachPartition(VoidFunction<Iterator<T>>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- foreachPartition(VoidFunction<Iterator<T>>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- foreachPartition(VoidFunction<Iterator<T>>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Applies a function f to each partition of this RDD.
- foreachPartition(Function1<Iterator<T>, BoxedUnit>) - Static method in class org.apache.spark.api.r.RRDD
-
- foreachPartition(Function1<Iterator<T>, BoxedUnit>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- foreachPartition(Function1<Iterator<T>, BoxedUnit>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- foreachPartition(Function1<Iterator<T>, BoxedUnit>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- foreachPartition(Function1<Iterator<T>, BoxedUnit>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- foreachPartition(Function1<Iterator<T>, BoxedUnit>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- foreachPartition(Function1<Iterator<T>, BoxedUnit>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- foreachPartition(Function1<Iterator<T>, BoxedUnit>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- foreachPartition(Function1<Iterator<T>, BoxedUnit>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- foreachPartition(Function1<Iterator<T>, BoxedUnit>) - Method in class org.apache.spark.rdd.RDD
-
Applies a function f to each partition of this RDD.
- foreachPartition(Function1<Iterator<T>, BoxedUnit>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- foreachPartition(Function1<Iterator<T>, BoxedUnit>) - Method in class org.apache.spark.sql.Dataset
-
Applies a function f to each partition of this Dataset.
- foreachPartition(ForeachPartitionFunction<T>) - Method in class org.apache.spark.sql.Dataset
-
(Java-specific)
Runs func on each partition of this Dataset.
- foreachPartitionAsync(VoidFunction<Iterator<T>>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- foreachPartitionAsync(VoidFunction<Iterator<T>>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- foreachPartitionAsync(VoidFunction<Iterator<T>>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- foreachPartitionAsync(VoidFunction<Iterator<T>>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
The asynchronous version of the foreachPartition action, which
applies a function f to each partition of this RDD.
- foreachPartitionAsync(Function1<Iterator<T>, BoxedUnit>) - Method in class org.apache.spark.rdd.AsyncRDDActions
-
Applies a function f to each partition of this RDD.
- ForeachPartitionFunction<T> - Interface in org.apache.spark.api.java.function
-
Base interface for a function used in Dataset's foreachPartition function.
- foreachRDD(VoidFunction<R>) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- foreachRDD(VoidFunction2<R, Time>) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- foreachRDD(VoidFunction<R>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Apply a function to each RDD in this DStream.
- foreachRDD(VoidFunction2<R, Time>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Apply a function to each RDD in this DStream.
- foreachRDD(VoidFunction<R>) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- foreachRDD(VoidFunction2<R, Time>) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- foreachRDD(VoidFunction<R>) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- foreachRDD(VoidFunction2<R, Time>) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- foreachRDD(VoidFunction<R>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- foreachRDD(VoidFunction2<R, Time>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- foreachRDD(VoidFunction<R>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- foreachRDD(VoidFunction2<R, Time>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- foreachRDD(VoidFunction<R>) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- foreachRDD(VoidFunction2<R, Time>) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- foreachRDD(Function1<RDD<T>, BoxedUnit>) - Method in class org.apache.spark.streaming.dstream.DStream
-
Apply a function to each RDD in this DStream.
- foreachRDD(Function2<RDD<T>, Time, BoxedUnit>) - Method in class org.apache.spark.streaming.dstream.DStream
-
Apply a function to each RDD in this DStream.
- foreachUp(Function1<BaseType, BoxedUnit>) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- foreachUp(Function1<BaseType, BoxedUnit>) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- foreachUp(Function1<BaseType, BoxedUnit>) - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- ForeachWriter<T> - Class in org.apache.spark.sql
-
:: Experimental ::
A class to consume data generated by a StreamingQuery.
- ForeachWriter() - Constructor for class org.apache.spark.sql.ForeachWriter
-
- format(String) - Method in class org.apache.spark.sql.DataFrameReader
-
Specifies the input data source format.
- format(String) - Method in class org.apache.spark.sql.DataFrameWriter
-
Specifies the underlying output data source.
- format(String) - Method in class org.apache.spark.sql.streaming.DataStreamReader
-
:: Experimental ::
Specifies the input data source format.
- format(String) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
-
:: Experimental ::
Specifies the underlying output data source.
- format_number(Column, int) - Static method in class org.apache.spark.sql.functions
-
Formats numeric column x to a format like '#,###,###.##', rounded to d decimal places,
and returns the result as a string column.
- format_string(String, Column...) - Static method in class org.apache.spark.sql.functions
-
Formats the arguments in printf-style and returns the result as a string column.
- format_string(String, Seq<Column>) - Static method in class org.apache.spark.sql.functions
-
Formats the arguments in printf-style and returns the result as a string column.
- formatBatchTime(long, long, boolean, TimeZone) - Static method in class org.apache.spark.streaming.ui.UIUtils
-
If batchInterval is less than 1 second, format batchTime with milliseconds.
- formatDate(Date) - Static method in class org.apache.spark.ui.UIUtils
-
- formatDate(long) - Static method in class org.apache.spark.ui.UIUtils
-
- formatDuration(long) - Static method in class org.apache.spark.ui.UIUtils
-
- formatDurationVerbose(long) - Static method in class org.apache.spark.ui.UIUtils
-
Generate a verbose human-readable string representing a duration such as "5 second 35 ms"
- formatNumber(double) - Static method in class org.apache.spark.ui.UIUtils
-
Generate a human-readable string representing a number (e.g.
- formatVersion() - Method in interface org.apache.spark.mllib.util.Saveable
-
Current version of model save/load format.
- formula() - Method in class org.apache.spark.ml.feature.RFormula
-
R formula parameter.
- FPGrowth - Class in org.apache.spark.mllib.fpm
-
A parallel FP-growth algorithm to mine frequent itemsets.
- FPGrowth() - Constructor for class org.apache.spark.mllib.fpm.FPGrowth
-
Constructs a default instance with default parameters {minSupport: 0.3, numPartitions: same
as the input data}.
- FPGrowth.FreqItemset<Item> - Class in org.apache.spark.mllib.fpm
-
Frequent itemset.
- FPGrowth.FreqItemset(Object, long) - Constructor for class org.apache.spark.mllib.fpm.FPGrowth.FreqItemset
-
- FPGrowthModel<Item> - Class in org.apache.spark.mllib.fpm
-
Model trained by
FPGrowth, which holds frequent itemsets.
- FPGrowthModel(RDD<FPGrowth.FreqItemset<Item>>, ClassTag<Item>) - Constructor for class org.apache.spark.mllib.fpm.FPGrowthModel
-
- FPGrowthModel.SaveLoadV1_0$ - Class in org.apache.spark.mllib.fpm
-
- FPGrowthModel.SaveLoadV1_0$() - Constructor for class org.apache.spark.mllib.fpm.FPGrowthModel.SaveLoadV1_0$
-
- freq() - Method in class org.apache.spark.mllib.fpm.FPGrowth.FreqItemset
-
- freq() - Method in class org.apache.spark.mllib.fpm.PrefixSpan.FreqSequence
-
- freqItems(String[], double) - Method in class org.apache.spark.sql.DataFrameStatFunctions
-
Finding frequent items for columns, possibly with false positives.
- freqItems(String[]) - Method in class org.apache.spark.sql.DataFrameStatFunctions
-
Finding frequent items for columns, possibly with false positives.
- freqItems(Seq<String>, double) - Method in class org.apache.spark.sql.DataFrameStatFunctions
-
(Scala-specific) Finding frequent items for columns, possibly with false positives.
- freqItems(Seq<String>) - Method in class org.apache.spark.sql.DataFrameStatFunctions
-
(Scala-specific) Finding frequent items for columns, possibly with false positives.
- freqItemsets() - Method in class org.apache.spark.mllib.fpm.FPGrowthModel
-
- freqSequences() - Method in class org.apache.spark.mllib.fpm.PrefixSpanModel
-
- from_unixtime(Column) - Static method in class org.apache.spark.sql.functions
-
Converts the number of seconds from unix epoch (1970-01-01 00:00:00 UTC) to a string
representing the timestamp of that moment in the current system time zone in the given
format.
- from_unixtime(Column, String) - Static method in class org.apache.spark.sql.functions
-
Converts the number of seconds from unix epoch (1970-01-01 00:00:00 UTC) to a string
representing the timestamp of that moment in the current system time zone in the given
format.
- from_utc_timestamp(Column, String) - Static method in class org.apache.spark.sql.functions
-
Assumes given timestamp is UTC and converts to given timezone.
- fromAvroFlumeEvent(AvroFlumeEvent) - Static method in class org.apache.spark.streaming.flume.SparkFlumeEvent
-
- fromCOO(int, int, Iterable<Tuple3<Object, Object, Object>>) - Static method in class org.apache.spark.ml.linalg.SparseMatrix
-
Generate a SparseMatrix from Coordinate List (COO) format.
- fromCOO(int, int, Iterable<Tuple3<Object, Object, Object>>) - Static method in class org.apache.spark.mllib.linalg.SparseMatrix
-
Generate a SparseMatrix from Coordinate List (COO) format.
- fromDecimal(Object) - Static method in class org.apache.spark.sql.types.Decimal
-
- fromDStream(DStream<T>, ClassTag<T>) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- fromEdgePartitions(RDD<Tuple2<Object, EdgePartition<ED, VD>>>, VD, StorageLevel, StorageLevel, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.impl.GraphImpl
-
Create a graph from EdgePartitions, setting referenced vertices to `defaultVertexAttr`.
- fromEdges(RDD<Edge<ED>>, ClassTag<ED>, ClassTag<VD>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
Creates an EdgeRDD from a set of edges.
- fromEdges(RDD<Edge<ED>>, VD, StorageLevel, StorageLevel, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.Graph
-
Construct a graph from a collection of edges.
- fromEdges(EdgeRDD<?>, int, VD, ClassTag<VD>) - Static method in class org.apache.spark.graphx.VertexRDD
-
Constructs a VertexRDD containing all vertices referred to in edges.
- fromEdgeTuples(RDD<Tuple2<Object, Object>>, VD, Option<PartitionStrategy>, StorageLevel, StorageLevel, ClassTag<VD>) - Static method in class org.apache.spark.graphx.Graph
-
Construct a graph from a collection of edges encoded as vertex id pairs.
- fromExistingRDDs(VertexRDD<VD>, EdgeRDD<ED>, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.impl.GraphImpl
-
Create a graph from a VertexRDD and an EdgeRDD with the same replicated vertex type as the
vertices.
- fromInputDStream(InputDStream<T>, ClassTag<T>) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- fromInputDStream(InputDStream<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- fromJavaDStream(JavaDStream<Tuple2<K, V>>) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- fromJavaRDD(JavaRDD<Tuple2<K, V>>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
Convert a JavaRDD of key-value pairs to JavaPairRDD.
- fromJson(String) - Static method in class org.apache.spark.ml.linalg.JsonVectorConverter
-
Parses the JSON representation of a vector into a
Vector.
- fromJson(String) - Static method in class org.apache.spark.mllib.linalg.Vectors
-
Parses the JSON representation of a vector into a
Vector.
- fromJson(String) - Static method in class org.apache.spark.sql.types.DataType
-
- fromJson(String) - Static method in class org.apache.spark.sql.types.Metadata
-
Creates a Metadata instance from JSON.
- fromMesos(Protos.TaskState) - Static method in class org.apache.spark.TaskState
-
- fromML(DenseMatrix) - Static method in class org.apache.spark.mllib.linalg.DenseMatrix
-
Convert new linalg type to spark.mllib type.
- fromML(DenseVector) - Static method in class org.apache.spark.mllib.linalg.DenseVector
-
Convert new linalg type to spark.mllib type.
- fromML(Matrix) - Static method in class org.apache.spark.mllib.linalg.Matrices
-
Convert new linalg type to spark.mllib type.
- fromML(SparseMatrix) - Static method in class org.apache.spark.mllib.linalg.SparseMatrix
-
Convert new linalg type to spark.mllib type.
- fromML(SparseVector) - Static method in class org.apache.spark.mllib.linalg.SparseVector
-
Convert new linalg type to spark.mllib type.
- fromML(Vector) - Static method in class org.apache.spark.mllib.linalg.Vectors
-
Convert new linalg type to spark.mllib type.
- fromName(String) - Static method in class org.apache.spark.ml.attribute.AttributeType
-
- fromName(String) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Family$
-
Gets the Family object from its name.
- fromName(String) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Link$
-
Gets the Link object from its name.
- fromNullable(T) - Static method in class org.apache.spark.api.java.Optional
-
- fromOffset() - Method in class org.apache.spark.streaming.kafka.OffsetRange
-
- fromOld(Node, Map<Object, Object>) - Static method in class org.apache.spark.ml.tree.Node
-
Create a new Node from the old Node format, recursively creating child nodes as needed.
- fromPairDStream(DStream<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- fromPairRDD(RDD<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>) - Static method in class org.apache.spark.mllib.rdd.MLPairRDDFunctions
-
Implicit conversion from a pair RDD to MLPairRDDFunctions.
- fromRDD(RDD<Object>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- fromRDD(RDD<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- fromRDD(RDD<T>, ClassTag<T>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- fromRDD(RDD<T>, ClassTag<T>) - Static method in class org.apache.spark.mllib.rdd.RDDFunctions
-
Implicit conversion from an RDD to RDDFunctions.
- fromRdd(RDD<?>) - Static method in class org.apache.spark.storage.RDDInfo
-
- fromReceiverInputDStream(ReceiverInputDStream<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- fromReceiverInputDStream(ReceiverInputDStream<T>, ClassTag<T>) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- fromSparkContext(SparkContext) - Static method in class org.apache.spark.api.java.JavaSparkContext
-
- fromStage(Stage, int, Option<Object>, TaskMetrics, Seq<Seq<TaskLocation>>) - Static method in class org.apache.spark.scheduler.StageInfo
-
Construct a StageInfo from a Stage.
- fromString(String) - Static method in enum org.apache.spark.JobExecutionStatus
-
- fromString(String) - Static method in class org.apache.spark.mllib.tree.impurity.Impurities
-
- fromString(String) - Static method in class org.apache.spark.mllib.tree.loss.Losses
-
- fromString(String) - Static method in enum org.apache.spark.status.api.v1.ApplicationStatus
-
- fromString(String) - Static method in enum org.apache.spark.status.api.v1.StageStatus
-
- fromString(String) - Static method in enum org.apache.spark.status.api.v1.TaskSorting
-
- fromString(String) - Static method in class org.apache.spark.storage.StorageLevel
-
:: DeveloperApi ::
Return the StorageLevel object with the specified name.
- fromStructField(StructField) - Static method in class org.apache.spark.ml.attribute.AttributeGroup
-
Creates an attribute group from a StructField instance.
- fullOuterJoin(JavaPairRDD<K, W>, Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Perform a full outer join of this and other.
- fullOuterJoin(JavaPairRDD<K, W>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Perform a full outer join of this and other.
- fullOuterJoin(JavaPairRDD<K, W>, int) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Perform a full outer join of this and other.
- fullOuterJoin(RDD<Tuple2<K, W>>, Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Perform a full outer join of this and other.
- fullOuterJoin(RDD<Tuple2<K, W>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Perform a full outer join of this and other.
- fullOuterJoin(RDD<Tuple2<K, W>>, int) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Perform a full outer join of this and other.
- fullOuterJoin(JavaPairDStream<K, W>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying 'full outer join' between RDDs of this DStream and
other DStream.
- fullOuterJoin(JavaPairDStream<K, W>, int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying 'full outer join' between RDDs of this DStream and
other DStream.
- fullOuterJoin(JavaPairDStream<K, W>, Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying 'full outer join' between RDDs of this DStream and
other DStream.
- fullOuterJoin(JavaPairDStream<K, W>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- fullOuterJoin(JavaPairDStream<K, W>, int) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- fullOuterJoin(JavaPairDStream<K, W>, Partitioner) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- fullOuterJoin(JavaPairDStream<K, W>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- fullOuterJoin(JavaPairDStream<K, W>, int) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- fullOuterJoin(JavaPairDStream<K, W>, Partitioner) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- fullOuterJoin(DStream<Tuple2<K, W>>, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying 'full outer join' between RDDs of this DStream and
other DStream.
- fullOuterJoin(DStream<Tuple2<K, W>>, int, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying 'full outer join' between RDDs of this DStream and
other DStream.
- fullOuterJoin(DStream<Tuple2<K, W>>, Partitioner, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying 'full outer join' between RDDs of this DStream and
other DStream.
- fullStackTrace() - Method in class org.apache.spark.ExceptionFailure
-
- Function<T1,R> - Interface in org.apache.spark.api.java.function
-
Base interface for functions whose return types do not create special RDDs.
- Function - Class in org.apache.spark.sql.catalog
-
A user-defined function in Spark, as returned by
listFunctions method in
Catalog.
- Function(String, String, String, String, boolean) - Constructor for class org.apache.spark.sql.catalog.Function
-
- function(Function4<Time, KeyType, Option<ValueType>, State<StateType>, Option<MappedType>>) - Static method in class org.apache.spark.streaming.StateSpec
-
- function(Function3<KeyType, Option<ValueType>, State<StateType>, MappedType>) - Static method in class org.apache.spark.streaming.StateSpec
-
- function(Function4<Time, KeyType, Optional<ValueType>, State<StateType>, Optional<MappedType>>) - Static method in class org.apache.spark.streaming.StateSpec
-
- function(Function3<KeyType, Optional<ValueType>, State<StateType>, MappedType>) - Static method in class org.apache.spark.streaming.StateSpec
-
- Function0<R> - Interface in org.apache.spark.api.java.function
-
A zero-argument function that returns an R.
- Function2<T1,T2,R> - Interface in org.apache.spark.api.java.function
-
A two-argument function that takes arguments of type T1 and T2 and returns an R.
- Function3<T1,T2,T3,R> - Interface in org.apache.spark.api.java.function
-
A three-argument function that takes arguments of type T1, T2 and T3 and returns an R.
- Function4<T1,T2,T3,T4,R> - Interface in org.apache.spark.api.java.function
-
A four-argument function that takes arguments of type T1, T2, T3 and T4 and returns an R.
- functions - Class in org.apache.spark.sql
-
:: Experimental ::
Functions available for DataFrame.
- functions() - Constructor for class org.apache.spark.sql.functions
-
- FutureAction<T> - Interface in org.apache.spark
-
A future for the result of an action to support cancellation.
- futureExecutionContext() - Static method in class org.apache.spark.rdd.AsyncRDDActions
-
- gain() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData
-
- gain() - Method in class org.apache.spark.ml.tree.InternalNode
-
- gain() - Method in class org.apache.spark.mllib.tree.model.InformationGainStats
-
- gamma1() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
-
- gamma2() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
-
- gamma6() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
-
- gamma7() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
-
- GammaGenerator - Class in org.apache.spark.mllib.random
-
:: DeveloperApi ::
Generates i.i.d.
- GammaGenerator(double, double) - Constructor for class org.apache.spark.mllib.random.GammaGenerator
-
- gammaJavaRDD(JavaSparkContext, double, double, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- gammaJavaRDD(JavaSparkContext, double, double, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- gammaJavaRDD(JavaSparkContext, double, double, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- gammaJavaVectorRDD(JavaSparkContext, double, double, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- gammaJavaVectorRDD(JavaSparkContext, double, double, long, int, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- gammaJavaVectorRDD(JavaSparkContext, double, double, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- gammaRDD(SparkContext, double, double, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
Generates an RDD comprised of i.i.d. samples from the gamma distribution with the input
shape and scale.
- gammaVectorRDD(SparkContext, double, double, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
Generates an RDD[Vector] with vectors containing i.i.d. samples drawn from the
gamma distribution with the input shape and scale.
- gapply(RelationalGroupedDataset, byte[], byte[], Object[], StructType) - Static method in class org.apache.spark.sql.api.r.SQLUtils
-
The helper function for gapply() on R side.
- gaps() - Method in class org.apache.spark.ml.feature.RegexTokenizer
-
Indicates whether regex splits on gaps (true) or matches tokens (false).
- GaussianMixture - Class in org.apache.spark.ml.clustering
-
:: Experimental ::
Gaussian Mixture clustering.
- GaussianMixture(String) - Constructor for class org.apache.spark.ml.clustering.GaussianMixture
-
- GaussianMixture() - Constructor for class org.apache.spark.ml.clustering.GaussianMixture
-
- GaussianMixture - Class in org.apache.spark.mllib.clustering
-
This class performs expectation maximization for multivariate Gaussian
Mixture Models (GMMs).
- GaussianMixture() - Constructor for class org.apache.spark.mllib.clustering.GaussianMixture
-
Constructs a default instance.
- GaussianMixtureModel - Class in org.apache.spark.ml.clustering
-
:: Experimental ::
- GaussianMixtureModel - Class in org.apache.spark.mllib.clustering
-
Multivariate Gaussian Mixture Model (GMM) consisting of k Gaussians, where points
are drawn from each Gaussian i=1..k with probability w(i); mu(i) and sigma(i) are
the respective mean and covariance for each Gaussian distribution i=1..k.
- GaussianMixtureModel(double[], MultivariateGaussian[]) - Constructor for class org.apache.spark.mllib.clustering.GaussianMixtureModel
-
- GaussianMixtureSummary - Class in org.apache.spark.ml.clustering
-
:: Experimental ::
Summary of GaussianMixture.
- gaussians() - Method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- gaussians() - Method in class org.apache.spark.mllib.clustering.GaussianMixtureModel
-
- gaussiansDF() - Method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
Retrieve Gaussian distributions as a DataFrame.
- GBTClassificationModel - Class in org.apache.spark.ml.classification
-
Gradient-Boosted Trees (GBTs) (http://en.wikipedia.org/wiki/Gradient_boosting)
model for classification.
- GBTClassificationModel(String, DecisionTreeRegressionModel[], double[]) - Constructor for class org.apache.spark.ml.classification.GBTClassificationModel
-
Construct a GBTClassificationModel
- GBTClassifier - Class in org.apache.spark.ml.classification
-
Gradient-Boosted Trees (GBTs) (http://en.wikipedia.org/wiki/Gradient_boosting)
learning algorithm for classification.
- GBTClassifier(String) - Constructor for class org.apache.spark.ml.classification.GBTClassifier
-
- GBTClassifier() - Constructor for class org.apache.spark.ml.classification.GBTClassifier
-
- GBTRegressionModel - Class in org.apache.spark.ml.regression
-
Gradient-Boosted Trees (GBTs)
model for regression.
- GBTRegressionModel(String, DecisionTreeRegressionModel[], double[]) - Constructor for class org.apache.spark.ml.regression.GBTRegressionModel
-
Construct a GBTRegressionModel
- GBTRegressor - Class in org.apache.spark.ml.regression
-
Gradient-Boosted Trees (GBTs)
learning algorithm for regression.
- GBTRegressor(String) - Constructor for class org.apache.spark.ml.regression.GBTRegressor
-
- GBTRegressor() - Constructor for class org.apache.spark.ml.regression.GBTRegressor
-
- GC_TIME() - Static method in class org.apache.spark.ui.ToolTips
-
- gemm(double, Matrix, DenseMatrix, double, DenseMatrix) - Static method in class org.apache.spark.ml.linalg.BLAS
-
C := alpha * A * B + beta * C
- gemm(double, Matrix, DenseMatrix, double, DenseMatrix) - Static method in class org.apache.spark.mllib.linalg.BLAS
-
C := alpha * A * B + beta * C
- gemv(double, Matrix, Vector, double, DenseVector) - Static method in class org.apache.spark.ml.linalg.BLAS
-
y := alpha * A * x + beta * y
- gemv(double, Matrix, Vector, double, DenseVector) - Static method in class org.apache.spark.mllib.linalg.BLAS
-
y := alpha * A * x + beta * y
- GeneralizedLinearAlgorithm<M extends GeneralizedLinearModel> - Class in org.apache.spark.mllib.regression
-
:: DeveloperApi ::
GeneralizedLinearAlgorithm implements methods to train a Generalized Linear Model (GLM).
- GeneralizedLinearAlgorithm() - Constructor for class org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm
-
- GeneralizedLinearModel - Class in org.apache.spark.mllib.regression
-
:: DeveloperApi ::
GeneralizedLinearModel (GLM) represents a model trained using
GeneralizedLinearAlgorithm.
- GeneralizedLinearModel(Vector, double) - Constructor for class org.apache.spark.mllib.regression.GeneralizedLinearModel
-
- GeneralizedLinearRegression - Class in org.apache.spark.ml.regression
-
:: Experimental ::
- GeneralizedLinearRegression(String) - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- GeneralizedLinearRegression() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- GeneralizedLinearRegression.Binomial$ - Class in org.apache.spark.ml.regression
-
Binomial exponential family distribution.
- GeneralizedLinearRegression.Binomial$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Binomial$
-
- GeneralizedLinearRegression.CLogLog$ - Class in org.apache.spark.ml.regression
-
- GeneralizedLinearRegression.CLogLog$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.CLogLog$
-
- GeneralizedLinearRegression.Family$ - Class in org.apache.spark.ml.regression
-
- GeneralizedLinearRegression.Family$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Family$
-
- GeneralizedLinearRegression.Gamma$ - Class in org.apache.spark.ml.regression
-
Gamma exponential family distribution.
- GeneralizedLinearRegression.Gamma$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gamma$
-
- GeneralizedLinearRegression.Gaussian$ - Class in org.apache.spark.ml.regression
-
Gaussian exponential family distribution.
- GeneralizedLinearRegression.Gaussian$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gaussian$
-
- GeneralizedLinearRegression.Identity$ - Class in org.apache.spark.ml.regression
-
- GeneralizedLinearRegression.Identity$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Identity$
-
- GeneralizedLinearRegression.Inverse$ - Class in org.apache.spark.ml.regression
-
- GeneralizedLinearRegression.Inverse$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Inverse$
-
- GeneralizedLinearRegression.Link$ - Class in org.apache.spark.ml.regression
-
- GeneralizedLinearRegression.Link$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Link$
-
- GeneralizedLinearRegression.Log$ - Class in org.apache.spark.ml.regression
-
- GeneralizedLinearRegression.Log$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Log$
-
- GeneralizedLinearRegression.Logit$ - Class in org.apache.spark.ml.regression
-
- GeneralizedLinearRegression.Logit$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Logit$
-
- GeneralizedLinearRegression.Poisson$ - Class in org.apache.spark.ml.regression
-
Poisson exponential family distribution.
- GeneralizedLinearRegression.Poisson$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Poisson$
-
- GeneralizedLinearRegression.Probit$ - Class in org.apache.spark.ml.regression
-
- GeneralizedLinearRegression.Probit$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Probit$
-
- GeneralizedLinearRegression.Sqrt$ - Class in org.apache.spark.ml.regression
-
- GeneralizedLinearRegression.Sqrt$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Sqrt$
-
- GeneralizedLinearRegressionModel - Class in org.apache.spark.ml.regression
-
- GeneralizedLinearRegressionSummary - Class in org.apache.spark.ml.regression
-
- GeneralizedLinearRegressionTrainingSummary - Class in org.apache.spark.ml.regression
-
- generateAssociationRules(double) - Method in class org.apache.spark.mllib.fpm.FPGrowthModel
-
Generates association rules for the Items in freqItemsets.
- generateKMeansRDD(SparkContext, int, int, int, double, int) - Static method in class org.apache.spark.mllib.util.KMeansDataGenerator
-
Generate an RDD containing test data for KMeans.
- generateLinearInput(double, double[], int, int, double) - Static method in class org.apache.spark.mllib.util.LinearDataGenerator
-
For compatibility, the generated data without specifying the mean and variance
will have zero mean and variance of (1.0/3.0) since the original output range is
[-1, 1] with uniform distribution, and the variance of uniform distribution
is (b - a)^2^ / 12 which will be (1.0/3.0)
- generateLinearInput(double, double[], double[], double[], int, int, double) - Static method in class org.apache.spark.mllib.util.LinearDataGenerator
-
- generateLinearInput(double, double[], double[], double[], int, int, double, double) - Static method in class org.apache.spark.mllib.util.LinearDataGenerator
-
- generateLinearInputAsList(double, double[], int, int, double) - Static method in class org.apache.spark.mllib.util.LinearDataGenerator
-
Return a Java List of synthetic data randomly generated according to a multi
collinear model.
- generateLinearRDD(SparkContext, int, int, double, int, double) - Static method in class org.apache.spark.mllib.util.LinearDataGenerator
-
Generate an RDD containing sample data for Linear Regression models - including Ridge, Lasso,
and unregularized variants.
- generateLogisticRDD(SparkContext, int, int, double, int, double) - Static method in class org.apache.spark.mllib.util.LogisticRegressionDataGenerator
-
Generate an RDD containing test data for LogisticRegression.
- generateRandomEdges(int, int, int, long) - Static method in class org.apache.spark.graphx.util.GraphGenerators
-
- generateTreeString(int, Seq<Object>, StringBuilder, boolean, String) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- generateTreeString(int, Seq<Object>, StringBuilder, boolean, String) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- generateTreeString(int, Seq<Object>, StringBuilder, boolean, String) - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- generateTreeString$default$5() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- generateTreeString$default$5() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- generateTreeString$default$5() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- genericBuilder() - Static method in class org.apache.spark.sql.types.StructType
-
- geq(Object) - Method in class org.apache.spark.sql.Column
-
Greater than or equal to an expression.
- get(Object) - Method in class org.apache.spark.api.java.JavaUtils.SerializableMapWrapper
-
- get() - Method in class org.apache.spark.api.java.Optional
-
- get(String) - Static method in class org.apache.spark.api.r.JVMObjectTracker
-
- get() - Method in interface org.apache.spark.FutureAction
-
Blocks and returns the result of this job.
- get(Param<T>) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- get(Param<T>) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- get(Param<T>) - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- get(Param<T>) - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- get(Param<T>) - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- get(Param<T>) - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- get(Param<T>) - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- get(Param<T>) - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- get(Param<T>) - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- get(Param<T>) - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.clustering.KMeans
-
- get(Param<T>) - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.clustering.LDA
-
- get(Param<T>) - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- get(Param<T>) - Static method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
- get(Param<T>) - Static method in class org.apache.spark.ml.evaluation.RegressionEvaluator
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.Binarizer
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.Bucketizer
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.ColumnPruner
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.CountVectorizer
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.DCT
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.ElementwiseProduct
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.HashingTF
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.IDF
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.IDFModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.IndexToString
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.Interaction
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.MaxAbsScaler
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.MinMaxScaler
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.NGram
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.Normalizer
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.OneHotEncoder
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.PCA
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.PCAModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.PolynomialExpansion
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.RegexTokenizer
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.RFormula
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.SQLTransformer
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.StandardScaler
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.StandardScalerModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.StopWordsRemover
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.StringIndexer
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.StringIndexerModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.Tokenizer
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.VectorAssembler
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.VectorAttributeRewriter
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.VectorIndexer
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.VectorSlicer
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- get(Param<T>) - Method in class org.apache.spark.ml.param.ParamMap
-
Optionally returns the value associated with a param.
- get(Param<T>) - Method in interface org.apache.spark.ml.param.Params
-
Optionally returns the user-supplied value of a param.
- get(Param<T>) - Static method in class org.apache.spark.ml.Pipeline
-
- get(Param<T>) - Static method in class org.apache.spark.ml.PipelineModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.recommendation.ALS
-
- get(Param<T>) - Static method in class org.apache.spark.ml.recommendation.ALSModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- get(Param<T>) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- get(Param<T>) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- get(Param<T>) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- get(Param<T>) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.regression.IsotonicRegression
-
- get(Param<T>) - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- get(Param<T>) - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- get(Param<T>) - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- get(Param<T>) - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- get(Param<T>) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- get(Param<T>) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
-
- get(String) - Method in class org.apache.spark.SparkConf
-
Get a parameter; throws a NoSuchElementException if it's not set
- get(String, String) - Method in class org.apache.spark.SparkConf
-
Get a parameter, falling back to a default if not set
- get() - Static method in class org.apache.spark.SparkEnv
-
Returns the SparkEnv.
- get(String) - Static method in class org.apache.spark.SparkFiles
-
Get the absolute path of a file added through SparkContext.addFile().
- get(int) - Method in interface org.apache.spark.sql.Row
-
Returns the value at position i.
- get(String) - Method in class org.apache.spark.sql.RuntimeConfig
-
Returns the value of Spark runtime configuration property for the given key.
- get(String, String) - Method in class org.apache.spark.sql.RuntimeConfig
-
Returns the value of Spark runtime configuration property for the given key.
- get(long) - Method in class org.apache.spark.sql.streaming.StreamingQueryManager
-
Returns the query if there is an active query with the given id, or null.
- get() - Method in class org.apache.spark.streaming.State
-
Get the state if it exists, otherwise it will throw java.util.NoSuchElementException.
- get() - Static method in class org.apache.spark.TaskContext
-
Return the currently active TaskContext.
- get(long) - Static method in class org.apache.spark.util.AccumulatorContext
-
- get_json_object(Column, String) - Static method in class org.apache.spark.sql.functions
-
Extracts json object from a json string based on json path specified, and returns json string
of the extracted json object.
- getAcceptanceResults(RDD<Tuple2<K, V>>, boolean, Map<K, Object>, Option<Map<K, Object>>, long) - Static method in class org.apache.spark.util.random.StratifiedSamplingUtils
-
Count the number of items instantly accepted and generate the waitlist for each stratum.
- getAcceptsNull() - Static method in class org.apache.spark.serializer.JavaIterableWrapperSerializer
-
- getActive() - Static method in class org.apache.spark.streaming.StreamingContext
-
:: Experimental ::
- getActiveJobIds() - Method in class org.apache.spark.api.java.JavaSparkStatusTracker
-
Returns an array containing the ids of all active jobs.
- getActiveJobIds() - Method in class org.apache.spark.SparkStatusTracker
-
Returns an array containing the ids of all active jobs.
- getActiveOrCreate(Function0<StreamingContext>) - Static method in class org.apache.spark.streaming.StreamingContext
-
:: Experimental ::
- getActiveOrCreate(String, Function0<StreamingContext>, Configuration, boolean) - Static method in class org.apache.spark.streaming.StreamingContext
-
:: Experimental ::
- getActiveStageIds() - Method in class org.apache.spark.api.java.JavaSparkStatusTracker
-
Returns an array containing the ids of all active stages.
- getActiveStageIds() - Method in class org.apache.spark.SparkStatusTracker
-
Returns an array containing the ids of all active stages.
- getAlgo() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getAll() - Method in class org.apache.spark.SparkConf
-
Get all parameters as a list of pairs
- getAll() - Method in class org.apache.spark.sql.RuntimeConfig
-
Returns all properties set in this conf.
- getAllConfs() - Method in class org.apache.spark.sql.SQLContext
-
Return all the configuration properties that have been set (i.e.
- getAllPools() - Method in class org.apache.spark.SparkContext
-
:: DeveloperApi ::
Return pools for fair scheduler
- getAllPrefLocs(RDD<?>) - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer.PartitionLocations
-
- GetAllReceiverInfo - Class in org.apache.spark.streaming.scheduler
-
- GetAllReceiverInfo() - Constructor for class org.apache.spark.streaming.scheduler.GetAllReceiverInfo
-
- getAlpha() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- getAlpha() - Method in class org.apache.spark.mllib.clustering.LDA
-
Alias for getDocConcentration
- getAnyValAs(int) - Method in interface org.apache.spark.sql.Row
-
Returns the value of a given fieldName.
- getAppId() - Method in interface org.apache.spark.launcher.SparkAppHandle
-
Returns the application ID, or null if not yet known.
- getAppId() - Method in class org.apache.spark.SparkConf
-
Returns the Spark application id, valid in the Driver after TaskScheduler registration and
from the start in the Executor.
- getAs(int) - Method in interface org.apache.spark.sql.Row
-
Returns the value at position i.
- getAs(String) - Method in interface org.apache.spark.sql.Row
-
Returns the value of a given fieldName.
- getAsymmetricAlpha() - Method in class org.apache.spark.mllib.clustering.LDA
-
Alias for getAsymmetricDocConcentration
- getAsymmetricDocConcentration() - Method in class org.apache.spark.mllib.clustering.LDA
-
Concentration parameter (commonly named "alpha") for the prior placed on documents'
distributions over topics ("theta").
- getAttr(String) - Method in class org.apache.spark.ml.attribute.AttributeGroup
-
Gets an attribute by its name.
- getAttr(int) - Method in class org.apache.spark.ml.attribute.AttributeGroup
-
Gets an attribute by its index.
- getAvroSchema() - Method in class org.apache.spark.SparkConf
-
Gets all the avro schemas in the configuration used in the generic Avro record serializer
- getBatchingTimeout(SparkConf) - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
-
How long we will wait for the wrappedLog in the BatchedWriteAheadLog to write the records
before we fail the write attempt to unblock receivers.
- getBernoulliSamplingFunction(RDD<Tuple2<K, V>>, Map<K, Object>, boolean, long) - Static method in class org.apache.spark.util.random.StratifiedSamplingUtils
-
Return the per partition sampling function used for sampling without replacement.
- getBeta() - Method in class org.apache.spark.mllib.clustering.LDA
-
Alias for getTopicConcentration
- getBinary() - Static method in class org.apache.spark.ml.feature.CountVectorizer
-
- getBinary() - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- getBinary() - Method in class org.apache.spark.ml.feature.HashingTF
-
- getBlock(BlockId) - Method in class org.apache.spark.storage.StorageStatus
-
Return the given block stored in this block manager in O(1) time.
- getBlockSize() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- getBoolean(String, boolean) - Method in class org.apache.spark.SparkConf
-
Get a parameter as a boolean, falling back to a default if not set
- getBoolean(int) - Method in interface org.apache.spark.sql.Row
-
Returns the value at position i as a primitive boolean.
- getBoolean(String) - Method in class org.apache.spark.sql.types.Metadata
-
Gets a Boolean.
- getBooleanArray(String) - Method in class org.apache.spark.sql.types.Metadata
-
Gets a Boolean array.
- getByte(int) - Method in interface org.apache.spark.sql.Row
-
Returns the value at position i as a primitive byte.
- getCachedBlockManagerId(BlockManagerId) - Static method in class org.apache.spark.storage.BlockManagerId
-
- getCachedMetadata(String) - Static method in class org.apache.spark.rdd.HadoopRDD
-
The three methods below are helpers for accessing the local map, a property of the SparkEnv of
the local process.
- getCacheNodeIds() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- getCacheNodeIds() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- getCacheNodeIds() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- getCacheNodeIds() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- getCacheNodeIds() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- getCacheNodeIds() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- getCacheNodeIds() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- getCacheNodeIds() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- getCacheNodeIds() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- getCacheNodeIds() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- getCacheNodeIds() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- getCacheNodeIds() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- getCallSite(Function1<String, Object>) - Static method in class org.apache.spark.util.Utils
-
When called inside a class in the spark package, returns the name of the user code class
(outside the spark package) that called into Spark, as well as which Spark method they called.
- getCaseSensitive() - Method in class org.apache.spark.ml.feature.StopWordsRemover
-
- getCatalystType(int, String, int, MetadataBuilder) - Method in class org.apache.spark.sql.jdbc.AggregatedDialect
-
- getCatalystType(int, String, int, MetadataBuilder) - Static method in class org.apache.spark.sql.jdbc.DB2Dialect
-
- getCatalystType(int, String, int, MetadataBuilder) - Static method in class org.apache.spark.sql.jdbc.DerbyDialect
-
- getCatalystType(int, String, int, MetadataBuilder) - Method in class org.apache.spark.sql.jdbc.JdbcDialect
-
Get the custom datatype mapping for the given jdbc meta information.
- getCatalystType(int, String, int, MetadataBuilder) - Static method in class org.apache.spark.sql.jdbc.MsSqlServerDialect
-
- getCatalystType(int, String, int, MetadataBuilder) - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
-
- getCatalystType(int, String, int, MetadataBuilder) - Static method in class org.apache.spark.sql.jdbc.NoopDialect
-
- getCatalystType(int, String, int, MetadataBuilder) - Static method in class org.apache.spark.sql.jdbc.OracleDialect
-
- getCatalystType(int, String, int, MetadataBuilder) - Static method in class org.apache.spark.sql.jdbc.PostgresDialect
-
- getCategoricalFeatures(StructField) - Static method in class org.apache.spark.ml.util.MetadataUtils
-
Examine a schema to identify categorical (Binary and Nominal) features.
- getCategoricalFeaturesInfo() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getCause() - Static method in exception org.apache.spark.sql.AnalysisException
-
- getCause() - Static method in exception org.apache.spark.sql.streaming.StreamingQueryException
-
- getCensorCol() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- getCensorCol() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- getCheckpointDir() - Method in class org.apache.spark.api.java.JavaSparkContext
-
- getCheckpointDir() - Method in class org.apache.spark.SparkContext
-
- getCheckpointFile() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- getCheckpointFile() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- getCheckpointFile() - Static method in class org.apache.spark.api.java.JavaRDD
-
- getCheckpointFile() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Gets the name of the file to which this RDD was checkpointed
- getCheckpointFile() - Static method in class org.apache.spark.api.r.RRDD
-
- getCheckpointFile() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- getCheckpointFile() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- getCheckpointFile() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- getCheckpointFile() - Static method in class org.apache.spark.graphx.VertexRDD
-
- getCheckpointFile() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- getCheckpointFile() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- getCheckpointFile() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- getCheckpointFile() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- getCheckpointFile() - Method in class org.apache.spark.rdd.RDD
-
Gets the name of the directory to which this RDD was checkpointed.
- getCheckpointFile() - Static method in class org.apache.spark.rdd.UnionRDD
-
- getCheckpointFiles() - Method in class org.apache.spark.graphx.Graph
-
Gets the name of the files to which this Graph was checkpointed.
- getCheckpointFiles() - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- getCheckpointFiles() - Method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
:: DeveloperApi ::
- getCheckpointInterval() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- getCheckpointInterval() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- getCheckpointInterval() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- getCheckpointInterval() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- getCheckpointInterval() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- getCheckpointInterval() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- getCheckpointInterval() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- getCheckpointInterval() - Static method in class org.apache.spark.ml.clustering.LDA
-
- getCheckpointInterval() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- getCheckpointInterval() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- getCheckpointInterval() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- getCheckpointInterval() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- getCheckpointInterval() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- getCheckpointInterval() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- getCheckpointInterval() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- getCheckpointInterval() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- getCheckpointInterval() - Method in class org.apache.spark.mllib.clustering.LDA
-
Period (in iterations) between checkpoints.
- getCheckpointInterval() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getClassifier() - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- getClassifier() - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- getCombOp() - Static method in class org.apache.spark.util.random.StratifiedSamplingUtils
-
Returns the function used combine results returned by seqOp from different partitions.
- getConf() - Method in class org.apache.spark.api.java.JavaSparkContext
-
Return a copy of this JavaSparkContext's configuration.
- getConf() - Method in class org.apache.spark.rdd.HadoopRDD
-
- getConf() - Method in class org.apache.spark.rdd.NewHadoopRDD
-
- getConf() - Method in class org.apache.spark.SparkContext
-
Return a copy of this SparkContext's configuration.
- getConf(String) - Method in class org.apache.spark.sql.SQLContext
-
Return the value of Spark SQL configuration property for the given key.
- getConf(String, String) - Method in class org.apache.spark.sql.SQLContext
-
Return the value of Spark SQL configuration property for the given key.
- getConfiguredLocalDirs(SparkConf) - Static method in class org.apache.spark.util.Utils
-
Return the configured local directories where Spark can write files.
- getConnection() - Method in interface org.apache.spark.rdd.JdbcRDD.ConnectionFactory
-
- getConsumerOffsetMetadata(String, Set<TopicAndPartition>) - Method in class org.apache.spark.streaming.kafka.KafkaCluster
-
Requires Kafka >= 0.8.1.1.
- getConsumerOffsetMetadata(String, Set<TopicAndPartition>, short) - Method in class org.apache.spark.streaming.kafka.KafkaCluster
-
- getConsumerOffsets(String, Set<TopicAndPartition>) - Method in class org.apache.spark.streaming.kafka.KafkaCluster
-
Requires Kafka >= 0.8.1.1.
- getConsumerOffsets(String, Set<TopicAndPartition>, short) - Method in class org.apache.spark.streaming.kafka.KafkaCluster
-
- getContextOrSparkClassLoader() - Static method in class org.apache.spark.util.Utils
-
Get the Context ClassLoader on this thread or, if not present, the ClassLoader that
loaded Spark.
- getConvergenceTol() - Method in class org.apache.spark.mllib.clustering.GaussianMixture
-
Return the largest change in log-likelihood at which convergence is
considered to have occurred.
- getCorrelationFromName(String) - Static method in class org.apache.spark.mllib.stat.correlation.Correlations
-
- getCurrentUserGroups(SparkConf, String) - Static method in class org.apache.spark.util.Utils
-
- getCurrentUserName() - Static method in class org.apache.spark.util.Utils
-
Returns the current user name.
- getDate(int) - Method in interface org.apache.spark.sql.Row
-
Returns the value at position i of date type as java.sql.Date.
- getDecimal(int) - Method in interface org.apache.spark.sql.Row
-
Returns the value at position i of decimal type as java.math.BigDecimal.
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.clustering.KMeans
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.clustering.LDA
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.evaluation.RegressionEvaluator
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.Binarizer
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.Bucketizer
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.ColumnPruner
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.CountVectorizer
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.DCT
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.ElementwiseProduct
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.HashingTF
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.IDF
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.IDFModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.IndexToString
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.Interaction
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.MaxAbsScaler
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.MinMaxScaler
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.NGram
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.Normalizer
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.OneHotEncoder
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.PCA
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.PCAModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.PolynomialExpansion
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.RegexTokenizer
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.RFormula
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.SQLTransformer
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.StandardScaler
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.StandardScalerModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.StopWordsRemover
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.StringIndexer
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.StringIndexerModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.Tokenizer
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.VectorAssembler
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.VectorAttributeRewriter
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.VectorIndexer
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.VectorSlicer
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- getDefault(Param<T>) - Method in interface org.apache.spark.ml.param.Params
-
Gets the default value of a parameter.
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.Pipeline
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.PipelineModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.recommendation.ALS
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.recommendation.ALSModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.IsotonicRegression
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
-
- getDefaultPropertiesFile(Map<String, String>) - Static method in class org.apache.spark.util.Utils
-
Return the path of the default Spark properties file.
- getDegree() - Method in class org.apache.spark.ml.feature.PolynomialExpansion
-
- getDependencies() - Method in class org.apache.spark.rdd.CoGroupedRDD
-
- getDependencies() - Method in class org.apache.spark.rdd.ShuffledRDD
-
- getDependencies() - Method in class org.apache.spark.rdd.UnionRDD
-
- getDeprecatedConfig(String, SparkConf) - Static method in class org.apache.spark.SparkConf
-
Looks for available deprecated keys for the given config option, and return the first
value available.
- getDocConcentration() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- getDocConcentration() - Static method in class org.apache.spark.ml.clustering.LDA
-
- getDocConcentration() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- getDocConcentration() - Method in class org.apache.spark.mllib.clustering.LDA
-
Concentration parameter (commonly named "alpha") for the prior placed on documents'
distributions over topics ("theta").
- getDouble(String, double) - Method in class org.apache.spark.SparkConf
-
Get a parameter as a double, falling back to a default if not set
- getDouble(int) - Method in interface org.apache.spark.sql.Row
-
Returns the value at position i as a primitive double.
- getDouble(String) - Method in class org.apache.spark.sql.types.Metadata
-
Gets a Double.
- getDoubleArray(String) - Method in class org.apache.spark.sql.types.Metadata
-
Gets a Double array.
- getDropLast() - Method in class org.apache.spark.ml.feature.OneHotEncoder
-
- getDynamicAllocationInitialExecutors(SparkConf) - Static method in class org.apache.spark.util.Utils
-
Return the initial number of executors for dynamic allocation.
- getEarliestLeaderOffsets(Set<TopicAndPartition>) - Method in class org.apache.spark.streaming.kafka.KafkaCluster
-
- getElasticNetParam() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getElasticNetParam() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getElasticNetParam() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- getElasticNetParam() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- getEndTimeEpoch() - Method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
-
- getEpsilon() - Method in class org.apache.spark.mllib.clustering.KMeans
-
The distance threshold within which we've consider centers to have converged.
- getEstimator() - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- getEstimator() - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- getEstimator() - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- getEstimator() - Static method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
-
- getEstimatorParamMaps() - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- getEstimatorParamMaps() - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- getEstimatorParamMaps() - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- getEstimatorParamMaps() - Static method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
-
- getEvaluator() - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- getEvaluator() - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- getEvaluator() - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- getEvaluator() - Static method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
-
- getExecutorEnv() - Method in class org.apache.spark.SparkConf
-
Get all executor environment variables set on this SparkConf
- getExecutorInfos() - Method in class org.apache.spark.SparkStatusTracker
-
Returns information of all known executors, including host, port, cacheSize, numRunningTasks.
- getExecutorMemoryStatus() - Method in class org.apache.spark.SparkContext
-
Return a map from the slave to the max memory available for caching and the remaining
memory available for caching.
- getExecutorStorageStatus() - Method in class org.apache.spark.SparkContext
-
:: DeveloperApi ::
Return information about blocks stored in all of the slaves
- getExternalTmpPath(Path, Configuration) - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- getExtTmpPathRelTo(Path, Configuration) - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- getFamily() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- getFamily() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- getFeatureIndex() - Static method in class org.apache.spark.ml.regression.IsotonicRegression
-
- getFeatureIndex() - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- getFeatureIndicesFromNames(StructField, String[]) - Static method in class org.apache.spark.ml.util.MetadataUtils
-
Takes a Vector column and a list of feature names, and returns the corresponding list of
feature indices in the column, in order.
- getFeaturesCol() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.clustering.KMeans
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.clustering.LDA
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.feature.RFormula
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.regression.IsotonicRegression
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- getFeatureSubsetStrategy() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- getFeatureSubsetStrategy() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- getFeatureSubsetStrategy() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- getFeatureSubsetStrategy() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- getField(String) - Method in class org.apache.spark.sql.Column
-
An expression that gets a field by name in a StructType.
- getFilePath(File, String) - Static method in class org.apache.spark.util.Utils
-
Return the absolute path of a file in the given directory.
- getFileReader(String, Option<Configuration>) - Static method in class org.apache.spark.sql.hive.orc.OrcFileOperator
-
Retrieves an ORC file reader from a given path.
- getFileSegmentLocations(String, long, long, Configuration) - Static method in class org.apache.spark.streaming.util.HdfsUtils
-
Get the locations of the HDFS blocks containing the given file segment.
- getFileSystemForPath(Path, Configuration) - Static method in class org.apache.spark.streaming.util.HdfsUtils
-
- getFinalStorageLevel() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- getFinalValue() - Method in class org.apache.spark.partial.PartialResult
-
Blocking method to wait for and return the final value.
- getFitIntercept() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getFitIntercept() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getFitIntercept() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- getFitIntercept() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- getFitIntercept() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- getFitIntercept() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- getFitIntercept() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- getFitIntercept() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- getFloat(int) - Method in interface org.apache.spark.sql.Row
-
Returns the value at position i as a primitive float.
- getFormattedClassName(Object) - Static method in class org.apache.spark.util.Utils
-
Return the class name of the given object, removing all dollar signs
- getFormula() - Method in class org.apache.spark.ml.feature.RFormula
-
- getGaps() - Method in class org.apache.spark.ml.feature.RegexTokenizer
-
- getGroups(String) - Method in interface org.apache.spark.security.GroupMappingServiceProvider
-
Get the groups the user belongs to.
- getHadoopFileSystem(URI, Configuration) - Static method in class org.apache.spark.util.Utils
-
Return a Hadoop FileSystem with the scheme encoded in the given path.
- getHadoopFileSystem(String, Configuration) - Static method in class org.apache.spark.util.Utils
-
Return a Hadoop FileSystem with the scheme encoded in the given path.
- getHandleInvalid() - Static method in class org.apache.spark.ml.feature.StringIndexer
-
- getHandleInvalid() - Static method in class org.apache.spark.ml.feature.StringIndexerModel
-
- getImplicitPrefs() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- getImpurity() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- getImpurity() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- getImpurity() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- getImpurity() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- getImpurity() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- getImpurity() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- getImpurity() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- getImpurity() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- getImpurity() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- getImpurity() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- getImpurity() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- getImpurity() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- getImpurity() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getIndices() - Method in class org.apache.spark.ml.feature.VectorSlicer
-
- getInitializationMode() - Method in class org.apache.spark.mllib.clustering.KMeans
-
The initialization algorithm.
- getInitializationSteps() - Method in class org.apache.spark.mllib.clustering.KMeans
-
Number of steps for the k-means|| initialization mode
- getInitialModel() - Method in class org.apache.spark.mllib.clustering.GaussianMixture
-
Return the user supplied initial GMM, if supplied
- getInitialPositionInStream(int) - Method in class org.apache.spark.streaming.kinesis.KinesisUtilsPythonHelper
-
- getInitialWeights() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- getInitMode() - Static method in class org.apache.spark.ml.clustering.KMeans
-
- getInitMode() - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- getInitSteps() - Static method in class org.apache.spark.ml.clustering.KMeans
-
- getInitSteps() - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.Binarizer
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.Bucketizer
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.CountVectorizer
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.DCT
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.ElementwiseProduct
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.HashingTF
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.IDF
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.IDFModel
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.IndexToString
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.MaxAbsScaler
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.MinMaxScaler
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.NGram
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.Normalizer
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.OneHotEncoder
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.PCA
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.PCAModel
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.PolynomialExpansion
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.RegexTokenizer
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.StandardScaler
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.StandardScalerModel
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.StopWordsRemover
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.StringIndexer
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.StringIndexerModel
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.Tokenizer
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.VectorIndexer
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.VectorSlicer
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- getInputCols() - Static method in class org.apache.spark.ml.feature.Interaction
-
- getInputCols() - Static method in class org.apache.spark.ml.feature.VectorAssembler
-
- getInputFileName() - Static method in class org.apache.spark.rdd.InputFileNameHolder
-
The thread variable for the name of the current file being read.
- getInputStream(String, Configuration) - Static method in class org.apache.spark.streaming.util.HdfsUtils
-
- getInt(String, int) - Method in class org.apache.spark.SparkConf
-
Get a parameter as an integer, falling back to a default if not set
- getInt(int) - Method in interface org.apache.spark.sql.Row
-
Returns the value at position i as a primitive int.
- getIntermediateStorageLevel() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- getInverse() - Method in class org.apache.spark.ml.feature.DCT
-
- getIsotonic() - Static method in class org.apache.spark.ml.regression.IsotonicRegression
-
- getIsotonic() - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- getItem(Object) - Method in class org.apache.spark.sql.Column
-
An expression that gets an item at position ordinal out of an array,
or gets a value by key key in a MapType.
- getItemCol() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- getItemCol() - Static method in class org.apache.spark.ml.recommendation.ALSModel
-
- getIteratorSize(Iterator<T>) - Static method in class org.apache.spark.util.Utils
-
Counts the number of elements of an iterator using a while loop rather than calling
TraversableOnce.size() because it uses a for loop, which is slightly slower
in the current version of Scala.
- getJavaMap(int) - Method in interface org.apache.spark.sql.Row
-
Returns the value at position i of array type as a Map.
- getJavaSparkContext(SparkSession) - Static method in class org.apache.spark.sql.api.r.SQLUtils
-
- getJDBCType(DataType) - Method in class org.apache.spark.sql.jdbc.AggregatedDialect
-
- getJDBCType(DataType) - Static method in class org.apache.spark.sql.jdbc.DB2Dialect
-
- getJDBCType(DataType) - Static method in class org.apache.spark.sql.jdbc.DerbyDialect
-
- getJDBCType(DataType) - Method in class org.apache.spark.sql.jdbc.JdbcDialect
-
Retrieve the jdbc / sql type for a given datatype.
- getJDBCType(DataType) - Static method in class org.apache.spark.sql.jdbc.MsSqlServerDialect
-
- getJDBCType(DataType) - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
-
- getJDBCType(DataType) - Static method in class org.apache.spark.sql.jdbc.NoopDialect
-
- getJDBCType(DataType) - Static method in class org.apache.spark.sql.jdbc.OracleDialect
-
- getJDBCType(DataType) - Static method in class org.apache.spark.sql.jdbc.PostgresDialect
-
- getJobIdsForGroup(String) - Method in class org.apache.spark.api.java.JavaSparkStatusTracker
-
Return a list of all known jobs in a particular job group.
- getJobIdsForGroup(String) - Method in class org.apache.spark.SparkStatusTracker
-
Return a list of all known jobs in a particular job group.
- getJobInfo(int) - Method in class org.apache.spark.api.java.JavaSparkStatusTracker
-
Returns job information, or null if the job info could not be found or was garbage collected.
- getJobInfo(int) - Method in class org.apache.spark.SparkStatusTracker
-
Returns job information, or None if the job info could not be found or was garbage collected.
- getK() - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- getK() - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- getK() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- getK() - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- getK() - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- getK() - Static method in class org.apache.spark.ml.clustering.KMeans
-
- getK() - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- getK() - Static method in class org.apache.spark.ml.clustering.LDA
-
- getK() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- getK() - Static method in class org.apache.spark.ml.feature.PCA
-
- getK() - Static method in class org.apache.spark.ml.feature.PCAModel
-
- getK() - Method in class org.apache.spark.mllib.clustering.BisectingKMeans
-
Gets the desired number of leaf clusters.
- getK() - Method in class org.apache.spark.mllib.clustering.GaussianMixture
-
Return the number of Gaussians in the mixture model
- getK() - Method in class org.apache.spark.mllib.clustering.KMeans
-
Number of clusters to create (k).
- getK() - Method in class org.apache.spark.mllib.clustering.LDA
-
Number of topics to infer, i.e., the number of soft cluster centers.
- getKappa() - Method in class org.apache.spark.mllib.clustering.OnlineLDAOptimizer
-
Learning rate: exponential decay rate
- getKeepLastCheckpoint() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- getKeepLastCheckpoint() - Static method in class org.apache.spark.ml.clustering.LDA
-
- getKeepLastCheckpoint() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- getKeepLastCheckpoint() - Method in class org.apache.spark.mllib.clustering.EMLDAOptimizer
-
If using checkpointing, this indicates whether to keep the last checkpoint (vs clean up).
- getLabelCol() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- getLabelCol() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- getLabelCol() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- getLabelCol() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- getLabelCol() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getLabelCol() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getLabelCol() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- getLabelCol() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- getLabelCol() - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- getLabelCol() - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- getLabelCol() - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- getLabelCol() - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- getLabelCol() - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- getLabelCol() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- getLabelCol() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- getLabelCol() - Static method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- getLabelCol() - Static method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
- getLabelCol() - Static method in class org.apache.spark.ml.evaluation.RegressionEvaluator
-
- getLabelCol() - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- getLabelCol() - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- getLabelCol() - Static method in class org.apache.spark.ml.feature.RFormula
-
- getLabelCol() - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- getLabelCol() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- getLabelCol() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- getLabelCol() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- getLabelCol() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- getLabelCol() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- getLabelCol() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- getLabelCol() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- getLabelCol() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- getLabelCol() - Static method in class org.apache.spark.ml.regression.IsotonicRegression
-
- getLabelCol() - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- getLabelCol() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- getLabelCol() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- getLabelCol() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- getLabelCol() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- getLabels() - Method in class org.apache.spark.ml.feature.IndexToString
-
- getLambda() - Method in class org.apache.spark.mllib.classification.NaiveBayes
-
Get the smoothing parameter.
- getLastUpdatedEpoch() - Method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
-
- getLatestLeaderOffsets(Set<TopicAndPartition>) - Method in class org.apache.spark.streaming.kafka.KafkaCluster
-
- getLayers() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- getLDAModel(double[]) - Method in interface org.apache.spark.mllib.clustering.LDAOptimizer
-
- getLeaderOffsets(Set<TopicAndPartition>, long) - Method in class org.apache.spark.streaming.kafka.KafkaCluster
-
- getLeaderOffsets(Set<TopicAndPartition>, long, int) - Method in class org.apache.spark.streaming.kafka.KafkaCluster
-
- getLearningDecay() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- getLearningDecay() - Static method in class org.apache.spark.ml.clustering.LDA
-
- getLearningDecay() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- getLearningOffset() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- getLearningOffset() - Static method in class org.apache.spark.ml.clustering.LDA
-
- getLearningOffset() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- getLearningRate() - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- getLeastGroupHash(String) - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
-
Sorts and gets the least element of the list associated with key in groupHash
The returned PartitionGroup is the least loaded of all groups that represent the machine "key"
- getLink() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- getLink() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- getLinkPredictionCol() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- getLinkPredictionCol() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- getList(int) - Method in interface org.apache.spark.sql.Row
-
Returns the value at position i of array type as List.
- getLocalDir(SparkConf) - Static method in class org.apache.spark.util.Utils
-
Get the path of a temporary directory.
- getLocalizedMessage() - Static method in exception org.apache.spark.sql.AnalysisException
-
- getLocalizedMessage() - Static method in exception org.apache.spark.sql.streaming.StreamingQueryException
-
- getLocalProperty(String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Get a local property set in this thread, or null if it is missing.
- getLocalProperty(String) - Method in class org.apache.spark.SparkContext
-
Get a local property set in this thread, or null if it is missing.
- getLocalProperty(String) - Method in class org.apache.spark.TaskContext
-
Get a local property set upstream in the driver, or null if it is missing.
- getLong(String, long) - Method in class org.apache.spark.SparkConf
-
Get a parameter as a long, falling back to a default if not set
- getLong(int) - Method in interface org.apache.spark.sql.Row
-
Returns the value at position i as a primitive long.
- getLong(String) - Method in class org.apache.spark.sql.types.Metadata
-
Gets a Long.
- getLongArray(String) - Method in class org.apache.spark.sql.types.Metadata
-
Gets a Long array.
- getLoss() - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- getLossType() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- getLossType() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- getLossType() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- getLossType() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- getLowerBound(double, long, double) - Static method in class org.apache.spark.util.random.BinomialBounds
-
Returns a threshold p such that if we conduct n Bernoulli trials with success rate = p,
it is very unlikely to have more than fraction * n successes.
- getLowerBound(double) - Static method in class org.apache.spark.util.random.PoissonBounds
-
Returns a lambda such that Pr[X > s] is very small, where X ~ Pois(lambda).
- getMap(int) - Method in interface org.apache.spark.sql.Row
-
Returns the value at position i of map type as a Scala Map.
- getMax() - Static method in class org.apache.spark.ml.feature.MinMaxScaler
-
- getMax() - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- getMaxBins() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- getMaxBins() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- getMaxBins() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- getMaxBins() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- getMaxBins() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- getMaxBins() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- getMaxBins() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- getMaxBins() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- getMaxBins() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- getMaxBins() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- getMaxBins() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- getMaxBins() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- getMaxBins() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getMaxCategories() - Static method in class org.apache.spark.ml.feature.VectorIndexer
-
- getMaxCategories() - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- getMaxDepth() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- getMaxDepth() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- getMaxDepth() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- getMaxDepth() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- getMaxDepth() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- getMaxDepth() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- getMaxDepth() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- getMaxDepth() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- getMaxDepth() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- getMaxDepth() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- getMaxDepth() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- getMaxDepth() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- getMaxDepth() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getMaxFailures(SparkConf, boolean) - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
-
- getMaxIter() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- getMaxIter() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- getMaxIter() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getMaxIter() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getMaxIter() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- getMaxIter() - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- getMaxIter() - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- getMaxIter() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- getMaxIter() - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- getMaxIter() - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- getMaxIter() - Static method in class org.apache.spark.ml.clustering.KMeans
-
- getMaxIter() - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- getMaxIter() - Static method in class org.apache.spark.ml.clustering.LDA
-
- getMaxIter() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- getMaxIter() - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- getMaxIter() - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- getMaxIter() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- getMaxIter() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- getMaxIter() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- getMaxIter() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- getMaxIter() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- getMaxIter() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- getMaxIter() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- getMaxIter() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- getMaxIter() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- getMaxIterations() - Method in class org.apache.spark.mllib.clustering.BisectingKMeans
-
Gets the max number of k-means iterations to split clusters.
- getMaxIterations() - Method in class org.apache.spark.mllib.clustering.GaussianMixture
-
Return the maximum number of iterations allowed
- getMaxIterations() - Method in class org.apache.spark.mllib.clustering.KMeans
-
Maximum number of iterations allowed.
- getMaxIterations() - Method in class org.apache.spark.mllib.clustering.LDA
-
Maximum number of iterations allowed.
- getMaxLocalProjDBSize() - Method in class org.apache.spark.mllib.fpm.PrefixSpan
-
Gets the maximum number of items allowed in a projected database before local processing.
- getMaxMemoryInMB() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- getMaxMemoryInMB() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- getMaxMemoryInMB() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- getMaxMemoryInMB() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- getMaxMemoryInMB() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- getMaxMemoryInMB() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- getMaxMemoryInMB() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- getMaxMemoryInMB() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- getMaxMemoryInMB() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- getMaxMemoryInMB() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- getMaxMemoryInMB() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- getMaxMemoryInMB() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- getMaxMemoryInMB() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getMaxPatternLength() - Method in class org.apache.spark.mllib.fpm.PrefixSpan
-
Gets the maximal pattern length (i.e.
- getMaxResultSize(SparkConf) - Static method in class org.apache.spark.util.Utils
-
- getMaxSentenceLength() - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- getMaxSentenceLength() - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- getMessage() - Method in exception org.apache.spark.sql.AnalysisException
-
- getMessage() - Static method in exception org.apache.spark.sql.streaming.StreamingQueryException
-
- getMetadata(String) - Method in class org.apache.spark.sql.types.Metadata
-
Gets a Metadata.
- getMetadataArray(String) - Method in class org.apache.spark.sql.types.Metadata
-
Gets a Metadata array.
- getMetricName() - Method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- getMetricName() - Method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
- getMetricName() - Method in class org.apache.spark.ml.evaluation.RegressionEvaluator
-
- getMetricsSources(String) - Method in class org.apache.spark.TaskContext
-
::DeveloperApi::
Returns all metrics sources with the given name which are associated with the instance
which runs the task.
- getMin() - Static method in class org.apache.spark.ml.feature.MinMaxScaler
-
- getMin() - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- getMinCount() - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- getMinCount() - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- getMinDF() - Static method in class org.apache.spark.ml.feature.CountVectorizer
-
- getMinDF() - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- getMinDivisibleClusterSize() - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- getMinDivisibleClusterSize() - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- getMinDivisibleClusterSize() - Method in class org.apache.spark.mllib.clustering.BisectingKMeans
-
Gets the minimum number of points (if >= 1.0) or the minimum proportion of points
(if < 1.0) of a divisible cluster.
- getMinDocFreq() - Static method in class org.apache.spark.ml.feature.IDF
-
- getMinDocFreq() - Static method in class org.apache.spark.ml.feature.IDFModel
-
- getMiniBatchFraction() - Method in class org.apache.spark.mllib.clustering.OnlineLDAOptimizer
-
Mini-batch fraction, which sets the fraction of document sampled and used in each iteration
- getMinInfoGain() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- getMinInfoGain() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- getMinInfoGain() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- getMinInfoGain() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- getMinInfoGain() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- getMinInfoGain() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- getMinInfoGain() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- getMinInfoGain() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- getMinInfoGain() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- getMinInfoGain() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- getMinInfoGain() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- getMinInfoGain() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- getMinInfoGain() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getMinInstancesPerNode() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- getMinInstancesPerNode() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- getMinInstancesPerNode() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- getMinInstancesPerNode() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- getMinInstancesPerNode() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- getMinInstancesPerNode() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- getMinInstancesPerNode() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- getMinInstancesPerNode() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- getMinInstancesPerNode() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- getMinInstancesPerNode() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- getMinInstancesPerNode() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- getMinInstancesPerNode() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- getMinInstancesPerNode() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getMinSupport() - Method in class org.apache.spark.mllib.fpm.PrefixSpan
-
Get the minimal support (i.e.
- getMinTF() - Static method in class org.apache.spark.ml.feature.CountVectorizer
-
- getMinTF() - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- getMinTokenLength() - Method in class org.apache.spark.ml.feature.RegexTokenizer
-
- getModelType() - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- getModelType() - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- getModelType() - Method in class org.apache.spark.mllib.classification.NaiveBayes
-
Get the model type.
- getN() - Method in class org.apache.spark.ml.feature.NGram
-
- getNames() - Method in class org.apache.spark.ml.feature.VectorSlicer
-
- getNode(int, Node) - Static method in class org.apache.spark.mllib.tree.model.Node
-
Traces down from a root node to get the node with the given node index.
- getNonnegative() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- getNumBuckets() - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- getNumClasses(StructField) - Static method in class org.apache.spark.ml.util.MetadataUtils
-
Examine a schema to identify the number of classes in a label column.
- getNumClasses() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getNumFeatures() - Method in class org.apache.spark.ml.feature.HashingTF
-
- getNumFeatures() - Static method in class org.apache.spark.mllib.classification.LogisticRegressionWithSGD
-
- getNumFeatures() - Static method in class org.apache.spark.mllib.classification.SVMWithSGD
-
- getNumFeatures() - Method in class org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm
-
The dimension of training features.
- getNumFeatures() - Static method in class org.apache.spark.mllib.regression.LassoWithSGD
-
- getNumFeatures() - Static method in class org.apache.spark.mllib.regression.LinearRegressionWithSGD
-
- getNumFeatures() - Static method in class org.apache.spark.mllib.regression.RidgeRegressionWithSGD
-
- getNumFolds() - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- getNumFolds() - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- getNumItemBlocks() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- getNumIterations() - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- getNumObjFields() - Method in class org.apache.spark.serializer.SerializationDebugger.ObjectStreamClassMethods
-
- getNumPartitions() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- getNumPartitions() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- getNumPartitions() - Static method in class org.apache.spark.api.java.JavaRDD
-
- getNumPartitions() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return the number of partitions in this RDD.
- getNumPartitions() - Static method in class org.apache.spark.api.r.RRDD
-
- getNumPartitions() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- getNumPartitions() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- getNumPartitions() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- getNumPartitions() - Static method in class org.apache.spark.graphx.VertexRDD
-
- getNumPartitions() - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- getNumPartitions() - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- getNumPartitions() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- getNumPartitions() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- getNumPartitions() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- getNumPartitions() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- getNumPartitions() - Method in class org.apache.spark.rdd.RDD
-
Returns the number of partitions of this RDD.
- getNumPartitions() - Static method in class org.apache.spark.rdd.UnionRDD
-
- getNumTopFeatures() - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- getNumTopFeatures() - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- getNumTrees() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- getNumTrees() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- getNumTrees() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- getNumTrees() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- getNumTrees() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- getNumTrees() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- getNumUserBlocks() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- getNumValues() - Method in class org.apache.spark.ml.attribute.NominalAttribute
-
Get the number of values, either from numValues or from values.
- getObject(String) - Static method in class org.apache.spark.api.r.JVMObjectTracker
-
- getObjectInspector(String, Option<Configuration>) - Static method in class org.apache.spark.sql.hive.orc.OrcFileOperator
-
- getObjFieldValues(Object, Object[]) - Method in class org.apache.spark.serializer.SerializationDebugger.ObjectStreamClassMethods
-
- getOptimizeDocConcentration() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- getOptimizeDocConcentration() - Static method in class org.apache.spark.ml.clustering.LDA
-
- getOptimizeDocConcentration() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- getOptimizeDocConcentration() - Method in class org.apache.spark.mllib.clustering.OnlineLDAOptimizer
-
Optimize docConcentration, indicates whether docConcentration (Dirichlet parameter for
document-topic distribution) will be optimized during training.
- getOptimizer() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- getOptimizer() - Static method in class org.apache.spark.ml.clustering.LDA
-
- getOptimizer() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- getOptimizer() - Method in class org.apache.spark.mllib.clustering.LDA
-
:: DeveloperApi ::
- getOption(String) - Method in class org.apache.spark.SparkConf
-
Get a parameter as an Option
- getOption(String) - Method in class org.apache.spark.sql.RuntimeConfig
-
Returns the value of Spark runtime configuration property for the given key.
- getOption() - Method in class org.apache.spark.streaming.State
-
Get the state as a Option.
- getOrCreate(SparkConf) - Static method in class org.apache.spark.SparkContext
-
This function may be used to get or instantiate a SparkContext and register it as a
singleton object.
- getOrCreate() - Static method in class org.apache.spark.SparkContext
-
This function may be used to get or instantiate a SparkContext and register it as a
singleton object.
- getOrCreate() - Method in class org.apache.spark.sql.SparkSession.Builder
-
Gets an existing
SparkSession or, if there is no existing one, creates a new
one based on the options set in this builder.
- getOrCreate(SparkContext) - Static method in class org.apache.spark.sql.SQLContext
-
Deprecated.
Use SparkSession.builder instead. Since 2.0.0.
- getOrCreate(String, Function0<JavaStreamingContext>) - Static method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Either recreate a StreamingContext from checkpoint data or create a new StreamingContext.
- getOrCreate(String, Function0<JavaStreamingContext>, Configuration) - Static method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Either recreate a StreamingContext from checkpoint data or create a new StreamingContext.
- getOrCreate(String, Function0<JavaStreamingContext>, Configuration, boolean) - Static method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Either recreate a StreamingContext from checkpoint data or create a new StreamingContext.
- getOrCreate(String, Function0<StreamingContext>, Configuration, boolean) - Static method in class org.apache.spark.streaming.StreamingContext
-
Either recreate a StreamingContext from checkpoint data or create a new StreamingContext.
- getOrCreateSparkSession(JavaSparkContext, Map<Object, Object>, boolean) - Static method in class org.apache.spark.sql.api.r.SQLUtils
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.clustering.KMeans
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.clustering.LDA
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.evaluation.RegressionEvaluator
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.Binarizer
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.Bucketizer
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.ColumnPruner
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.CountVectorizer
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.DCT
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.ElementwiseProduct
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.HashingTF
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.IDF
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.IDFModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.IndexToString
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.Interaction
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.MaxAbsScaler
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.MinMaxScaler
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.NGram
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.Normalizer
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.OneHotEncoder
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.PCA
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.PCAModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.PolynomialExpansion
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.RegexTokenizer
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.RFormula
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.SQLTransformer
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.StandardScaler
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.StandardScalerModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.StopWordsRemover
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.StringIndexer
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.StringIndexerModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.Tokenizer
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.VectorAssembler
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.VectorAttributeRewriter
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.VectorIndexer
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.VectorSlicer
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- getOrDefault(Param<T>) - Method in interface org.apache.spark.ml.param.Params
-
Gets the value of a param in the embedded param map or its default value.
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.Pipeline
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.PipelineModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.recommendation.ALS
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.recommendation.ALSModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.IsotonicRegression
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
-
- getOrElse(Param<T>, T) - Method in class org.apache.spark.ml.param.ParamMap
-
Returns the value associated with a param or a default value.
- getOutputCol() - Static method in class org.apache.spark.ml.feature.Binarizer
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.Bucketizer
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.CountVectorizer
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.DCT
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.ElementwiseProduct
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.HashingTF
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.IDF
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.IDFModel
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.IndexToString
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.Interaction
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.MaxAbsScaler
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.MinMaxScaler
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.NGram
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.Normalizer
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.OneHotEncoder
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.PCA
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.PCAModel
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.PolynomialExpansion
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.RegexTokenizer
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.StandardScaler
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.StandardScalerModel
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.StopWordsRemover
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.StringIndexer
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.StringIndexerModel
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.Tokenizer
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.VectorAssembler
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.VectorIndexer
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.VectorSlicer
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- getOutputStream(String, Configuration) - Static method in class org.apache.spark.streaming.util.HdfsUtils
-
- getP() - Method in class org.apache.spark.ml.feature.Normalizer
-
- getParam(String) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- getParam(String) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- getParam(String) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- getParam(String) - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- getParam(String) - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getParam(String) - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getParam(String) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- getParam(String) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- getParam(String) - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- getParam(String) - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- getParam(String) - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- getParam(String) - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- getParam(String) - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- getParam(String) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- getParam(String) - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- getParam(String) - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- getParam(String) - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- getParam(String) - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- getParam(String) - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- getParam(String) - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- getParam(String) - Static method in class org.apache.spark.ml.clustering.KMeans
-
- getParam(String) - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- getParam(String) - Static method in class org.apache.spark.ml.clustering.LDA
-
- getParam(String) - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- getParam(String) - Static method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- getParam(String) - Static method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
- getParam(String) - Static method in class org.apache.spark.ml.evaluation.RegressionEvaluator
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.Binarizer
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.Bucketizer
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.ColumnPruner
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.CountVectorizer
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.DCT
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.ElementwiseProduct
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.HashingTF
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.IDF
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.IDFModel
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.IndexToString
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.Interaction
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.MaxAbsScaler
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.MinMaxScaler
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.NGram
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.Normalizer
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.OneHotEncoder
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.PCA
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.PCAModel
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.PolynomialExpansion
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.RegexTokenizer
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.RFormula
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.SQLTransformer
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.StandardScaler
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.StandardScalerModel
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.StopWordsRemover
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.StringIndexer
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.StringIndexerModel
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.Tokenizer
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.VectorAssembler
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.VectorAttributeRewriter
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.VectorIndexer
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.VectorSlicer
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- getParam(String) - Method in interface org.apache.spark.ml.param.Params
-
Gets a param by its name.
- getParam(String) - Static method in class org.apache.spark.ml.Pipeline
-
- getParam(String) - Static method in class org.apache.spark.ml.PipelineModel
-
- getParam(String) - Static method in class org.apache.spark.ml.recommendation.ALS
-
- getParam(String) - Static method in class org.apache.spark.ml.recommendation.ALSModel
-
- getParam(String) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- getParam(String) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- getParam(String) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- getParam(String) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- getParam(String) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- getParam(String) - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- getParam(String) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- getParam(String) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- getParam(String) - Static method in class org.apache.spark.ml.regression.IsotonicRegression
-
- getParam(String) - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- getParam(String) - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- getParam(String) - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- getParam(String) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- getParam(String) - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- getParam(String) - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- getParam(String) - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- getParam(String) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- getParam(String) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
-
- getParents(int) - Method in class org.apache.spark.NarrowDependency
-
Get the parent partitions for a child partition.
- getParents(int) - Method in class org.apache.spark.OneToOneDependency
-
- getParents(int) - Method in class org.apache.spark.RangeDependency
-
- getPartition(long, long, int) - Method in class org.apache.spark.graphx.PartitionStrategy.CanonicalRandomVertexCut$
-
- getPartition(long, long, int) - Method in class org.apache.spark.graphx.PartitionStrategy.EdgePartition1D$
-
- getPartition(long, long, int) - Method in class org.apache.spark.graphx.PartitionStrategy.EdgePartition2D$
-
- getPartition(long, long, int) - Method in interface org.apache.spark.graphx.PartitionStrategy
-
Returns the partition number for a given edge.
- getPartition(long, long, int) - Method in class org.apache.spark.graphx.PartitionStrategy.RandomVertexCut$
-
- getPartition(Object) - Method in class org.apache.spark.HashPartitioner
-
- getPartition(Object) - Method in class org.apache.spark.Partitioner
-
- getPartition(Object) - Method in class org.apache.spark.RangePartitioner
-
- getPartitionId() - Static method in class org.apache.spark.TaskContext
-
Returns the partition id of currently active TaskContext.
- getPartitionMetadata(Set<String>) - Method in class org.apache.spark.streaming.kafka.KafkaCluster
-
- getPartitions() - Method in class org.apache.spark.api.r.BaseRRDD
-
- getPartitions() - Static method in class org.apache.spark.api.r.RRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.CoGroupedRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
-
- getPartitions() - Method in class org.apache.spark.rdd.HadoopRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.JdbcRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.NewHadoopRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.ShuffledRDD
-
- getPartitions() - Method in class org.apache.spark.rdd.UnionRDD
-
- getPartitions(Set<String>) - Method in class org.apache.spark.streaming.kafka.KafkaCluster
-
- getPath() - Method in class org.apache.spark.input.PortableDataStream
-
- getPattern() - Method in class org.apache.spark.ml.feature.RegexTokenizer
-
- getPersistentRDDs() - Method in class org.apache.spark.api.java.JavaSparkContext
-
Returns a Java map of JavaRDDs that have marked themselves as persistent via cache() call.
- getPersistentRDDs() - Method in class org.apache.spark.SparkContext
-
Returns an immutable map of RDDs that have marked themselves as persistent via cache() call.
- getPoissonSamplingFunction(RDD<Tuple2<K, V>>, Map<K, Object>, boolean, long, ClassTag<K>, ClassTag<V>) - Static method in class org.apache.spark.util.random.StratifiedSamplingUtils
-
Return the per partition sampling function used for sampling with replacement.
- getPoolForName(String) - Method in class org.apache.spark.SparkContext
-
:: DeveloperApi ::
Return the pool associated with the given name, if one exists
- getPredictionCol() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- getPredictionCol() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- getPredictionCol() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- getPredictionCol() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- getPredictionCol() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getPredictionCol() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getPredictionCol() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- getPredictionCol() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- getPredictionCol() - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- getPredictionCol() - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- getPredictionCol() - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- getPredictionCol() - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- getPredictionCol() - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- getPredictionCol() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- getPredictionCol() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- getPredictionCol() - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- getPredictionCol() - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- getPredictionCol() - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- getPredictionCol() - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- getPredictionCol() - Static method in class org.apache.spark.ml.clustering.KMeans
-
- getPredictionCol() - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- getPredictionCol() - Static method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
- getPredictionCol() - Static method in class org.apache.spark.ml.evaluation.RegressionEvaluator
-
- getPredictionCol() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- getPredictionCol() - Static method in class org.apache.spark.ml.recommendation.ALSModel
-
- getPredictionCol() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- getPredictionCol() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- getPredictionCol() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- getPredictionCol() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- getPredictionCol() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- getPredictionCol() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- getPredictionCol() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- getPredictionCol() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- getPredictionCol() - Static method in class org.apache.spark.ml.regression.IsotonicRegression
-
- getPredictionCol() - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- getPredictionCol() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- getPredictionCol() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- getPredictionCol() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- getPredictionCol() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- getPreferredLocations(Partition) - Method in class org.apache.spark.rdd.HadoopRDD
-
- getPreferredLocations(Partition) - Method in class org.apache.spark.rdd.NewHadoopRDD
-
- getPreferredLocations(Partition) - Method in class org.apache.spark.rdd.UnionRDD
-
- getProbabilityCol() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- getProbabilityCol() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- getProbabilityCol() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getProbabilityCol() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getProbabilityCol() - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- getProbabilityCol() - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- getProbabilityCol() - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- getProbabilityCol() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- getProbabilityCol() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- getProbabilityCol() - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- getProbabilityCol() - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- getProcessName() - Static method in class org.apache.spark.util.Utils
-
Returns the name of this JVM process.
- getPropertiesFromFile(String) - Static method in class org.apache.spark.util.Utils
-
Load properties present in the given file.
- getQuantileCalculationStrategy() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getQuantileProbabilities() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- getQuantileProbabilities() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- getQuantilesCol() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- getQuantilesCol() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- getRank() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- getRatingCol() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- getRawPredictionCol() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- getRawPredictionCol() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- getRawPredictionCol() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getRawPredictionCol() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getRawPredictionCol() - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- getRawPredictionCol() - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- getRawPredictionCol() - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- getRawPredictionCol() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- getRawPredictionCol() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- getRawPredictionCol() - Static method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- getRddBlockLocations(int, Seq<StorageStatus>) - Static method in class org.apache.spark.storage.StorageUtils
-
Return a mapping from block ID to its locations for each block that belongs to the given RDD.
- getRDDStorageInfo() - Method in class org.apache.spark.SparkContext
-
:: DeveloperApi ::
Return information about what RDDs are cached, if they are in mem or on disk, how much space
they take, etc.
- getReceiver() - Method in class org.apache.spark.streaming.dstream.ReceiverInputDStream
-
Gets the receiver object that will be sent to the worker nodes
to receive data.
- getRegParam() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getRegParam() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getRegParam() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- getRegParam() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- getRegParam() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- getRegParam() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- getRegParam() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- getRelativeError() - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- getRollingIntervalSecs(SparkConf, boolean) - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
-
- getRootDirectory() - Static method in class org.apache.spark.SparkFiles
-
Get the root directory that contains files added through SparkContext.addFile().
- getRuns() - Method in class org.apache.spark.mllib.clustering.KMeans
-
This function has no effect since Spark 2.0.0.
- getScalingVec() - Method in class org.apache.spark.ml.feature.ElementwiseProduct
-
- getSchedulingMode() - Method in class org.apache.spark.SparkContext
-
Return current scheduling mode
- getSeed() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- getSeed() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- getSeed() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- getSeed() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- getSeed() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- getSeed() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- getSeed() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- getSeed() - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- getSeed() - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- getSeed() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- getSeed() - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- getSeed() - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- getSeed() - Static method in class org.apache.spark.ml.clustering.KMeans
-
- getSeed() - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- getSeed() - Static method in class org.apache.spark.ml.clustering.LDA
-
- getSeed() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- getSeed() - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- getSeed() - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- getSeed() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- getSeed() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- getSeed() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- getSeed() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- getSeed() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- getSeed() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- getSeed() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- getSeed() - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- getSeed() - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- getSeed() - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- getSeed() - Static method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
-
- getSeed() - Method in class org.apache.spark.mllib.clustering.BisectingKMeans
-
Gets the random seed.
- getSeed() - Method in class org.apache.spark.mllib.clustering.GaussianMixture
-
Return the random seed
- getSeed() - Method in class org.apache.spark.mllib.clustering.KMeans
-
The random seed for cluster initialization.
- getSeed() - Method in class org.apache.spark.mllib.clustering.LDA
-
Random seed for cluster initialization.
- getSeq(int) - Method in interface org.apache.spark.sql.Row
-
Returns the value at position i of array type as a Scala Seq.
- getSeqOp(boolean, Map<K, Object>, StratifiedSamplingUtils.RandomDataGenerator, Option<Map<K, Object>>) - Static method in class org.apache.spark.util.random.StratifiedSamplingUtils
-
Returns the function used by aggregate to collect sampling statistics for each partition.
- getSessionConf(SparkSession) - Static method in class org.apache.spark.sql.api.r.SQLUtils
-
- getShort(int) - Method in interface org.apache.spark.sql.Row
-
Returns the value at position i as a primitive short.
- getSizeAsBytes(String) - Method in class org.apache.spark.SparkConf
-
Get a size parameter as bytes; throws a NoSuchElementException if it's not set.
- getSizeAsBytes(String, String) - Method in class org.apache.spark.SparkConf
-
Get a size parameter as bytes, falling back to a default if not set.
- getSizeAsBytes(String, long) - Method in class org.apache.spark.SparkConf
-
Get a size parameter as bytes, falling back to a default if not set.
- getSizeAsGb(String) - Method in class org.apache.spark.SparkConf
-
Get a size parameter as Gibibytes; throws a NoSuchElementException if it's not set.
- getSizeAsGb(String, String) - Method in class org.apache.spark.SparkConf
-
Get a size parameter as Gibibytes, falling back to a default if not set.
- getSizeAsKb(String) - Method in class org.apache.spark.SparkConf
-
Get a size parameter as Kibibytes; throws a NoSuchElementException if it's not set.
- getSizeAsKb(String, String) - Method in class org.apache.spark.SparkConf
-
Get a size parameter as Kibibytes, falling back to a default if not set.
- getSizeAsMb(String) - Method in class org.apache.spark.SparkConf
-
Get a size parameter as Mebibytes; throws a NoSuchElementException if it's not set.
- getSizeAsMb(String, String) - Method in class org.apache.spark.SparkConf
-
Get a size parameter as Mebibytes, falling back to a default if not set.
- getSlotDescs() - Method in class org.apache.spark.serializer.SerializationDebugger.ObjectStreamClassMethods
-
- getSmoothing() - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- getSmoothing() - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- getSolver() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- getSolver() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- getSolver() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- getSolver() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- getSolver() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- getSparkClassLoader() - Static method in class org.apache.spark.util.Utils
-
Get the ClassLoader which loaded Spark.
- getSparkHome() - Method in class org.apache.spark.api.java.JavaSparkContext
-
Get Spark's home location from either a value set through the constructor,
or the spark.home Java property, or the SPARK_HOME environment variable
(in that order of preference).
- getSparkOrYarnConfig(SparkConf, String, String) - Static method in class org.apache.spark.util.Utils
-
Return the value of a config either through the SparkConf or the Hadoop configuration
if this is Yarn mode.
- getSplit() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.SplitData
-
- getSplits() - Method in class org.apache.spark.ml.feature.Bucketizer
-
- getSQLDataType(String) - Static method in class org.apache.spark.sql.api.r.SQLUtils
-
- getStackTrace() - Static method in exception org.apache.spark.sql.AnalysisException
-
- getStackTrace() - Static method in exception org.apache.spark.sql.streaming.StreamingQueryException
-
- getStageInfo(int) - Method in class org.apache.spark.api.java.JavaSparkStatusTracker
-
Returns stage information, or null if the stage info could not be found or was
garbage collected.
- getStageInfo(int) - Method in class org.apache.spark.SparkStatusTracker
-
Returns stage information, or None if the stage info could not be found or was
garbage collected.
- getStagePath(String, int, int, String) - Method in class org.apache.spark.ml.Pipeline.SharedReadWrite$
-
Get path for saving the given stage.
- getStages() - Method in class org.apache.spark.ml.Pipeline
-
- getStandardization() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getStandardization() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getStandardization() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- getStandardization() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- getStartTimeEpoch() - Method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
-
- getState() - Method in interface org.apache.spark.launcher.SparkAppHandle
-
Returns the current application state.
- getState() - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
:: DeveloperApi ::
- getState() - Method in class org.apache.spark.streaming.StreamingContext
-
:: DeveloperApi ::
- getStatement() - Method in class org.apache.spark.ml.feature.SQLTransformer
-
- getStderr(Process, long) - Static method in class org.apache.spark.util.Utils
-
Return the stderr of a process after waiting for the process to terminate.
- getStepSize() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- getStepSize() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- getStepSize() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- getStepSize() - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- getStepSize() - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- getStepSize() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- getStepSize() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- getStopWords() - Method in class org.apache.spark.ml.feature.StopWordsRemover
-
- getStorageLevel() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- getStorageLevel() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- getStorageLevel() - Static method in class org.apache.spark.api.java.JavaRDD
-
- getStorageLevel() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Get the RDD's current storage level, or StorageLevel.NONE if none is set.
- getStorageLevel() - Static method in class org.apache.spark.api.r.RRDD
-
- getStorageLevel() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- getStorageLevel() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- getStorageLevel() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- getStorageLevel() - Static method in class org.apache.spark.graphx.VertexRDD
-
- getStorageLevel() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- getStorageLevel() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- getStorageLevel() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- getStorageLevel() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- getStorageLevel() - Method in class org.apache.spark.rdd.RDD
-
Get the RDD's current storage level, or StorageLevel.NONE if none is set.
- getStorageLevel() - Static method in class org.apache.spark.rdd.UnionRDD
-
- getString(int) - Method in interface org.apache.spark.sql.Row
-
Returns the value at position i as a String object.
- getString(String) - Method in class org.apache.spark.sql.types.Metadata
-
Gets a String.
- getStringArray(String) - Method in class org.apache.spark.sql.types.Metadata
-
Gets a String array.
- getStruct(int) - Method in interface org.apache.spark.sql.Row
-
Returns the value at position i of struct type as a
Row object.
- getSubsamplingRate() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- getSubsamplingRate() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- getSubsamplingRate() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- getSubsamplingRate() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- getSubsamplingRate() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- getSubsamplingRate() - Static method in class org.apache.spark.ml.clustering.LDA
-
- getSubsamplingRate() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- getSubsamplingRate() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- getSubsamplingRate() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- getSubsamplingRate() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- getSubsamplingRate() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- getSubsamplingRate() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getSuppressed() - Static method in exception org.apache.spark.sql.AnalysisException
-
- getSuppressed() - Static method in exception org.apache.spark.sql.streaming.StreamingQueryException
-
- getSystemProperties() - Static method in class org.apache.spark.util.Utils
-
Returns the system properties map that is thread-safe to iterator over.
- getTableExistsQuery(String) - Static method in class org.apache.spark.sql.jdbc.DB2Dialect
-
- getTableExistsQuery(String) - Static method in class org.apache.spark.sql.jdbc.DerbyDialect
-
- getTableExistsQuery(String) - Method in class org.apache.spark.sql.jdbc.JdbcDialect
-
Get the SQL query that should be used to find if the given table exists.
- getTableExistsQuery(String) - Static method in class org.apache.spark.sql.jdbc.MsSqlServerDialect
-
- getTableExistsQuery(String) - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
-
- getTableExistsQuery(String) - Static method in class org.apache.spark.sql.jdbc.NoopDialect
-
- getTableExistsQuery(String) - Static method in class org.apache.spark.sql.jdbc.OracleDialect
-
- getTableExistsQuery(String) - Static method in class org.apache.spark.sql.jdbc.PostgresDialect
-
- getTableNames(SparkSession, String) - Static method in class org.apache.spark.sql.api.r.SQLUtils
-
- getTables(SparkSession, String) - Static method in class org.apache.spark.sql.api.r.SQLUtils
-
- getTau0() - Method in class org.apache.spark.mllib.clustering.OnlineLDAOptimizer
-
A (positive) learning parameter that downweights early iterations.
- getThreadDump() - Static method in class org.apache.spark.util.Utils
-
Return a thread dump of all threads' stacktraces.
- getThreshold() - Method in class org.apache.spark.ml.classification.LogisticRegression
-
- getThreshold() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getThreshold() - Method in class org.apache.spark.ml.feature.Binarizer
-
- getThreshold() - Method in class org.apache.spark.mllib.classification.LogisticRegressionModel
-
Returns the threshold (if any) used for converting raw prediction scores into 0/1 predictions.
- getThreshold() - Method in class org.apache.spark.mllib.classification.SVMModel
-
Returns the threshold (if any) used for converting raw prediction scores into 0/1 predictions.
- getThresholds() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- getThresholds() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- getThresholds() - Method in class org.apache.spark.ml.classification.LogisticRegression
-
- getThresholds() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getThresholds() - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- getThresholds() - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- getThresholds() - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- getThresholds() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- getThresholds() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- getTimeAsMs(String) - Method in class org.apache.spark.SparkConf
-
Get a time parameter as milliseconds; throws a NoSuchElementException if it's not set.
- getTimeAsMs(String, String) - Method in class org.apache.spark.SparkConf
-
Get a time parameter as milliseconds, falling back to a default if not set.
- getTimeAsSeconds(String) - Method in class org.apache.spark.SparkConf
-
Get a time parameter as seconds; throws a NoSuchElementException if it's not set.
- getTimeAsSeconds(String, String) - Method in class org.apache.spark.SparkConf
-
Get a time parameter as seconds, falling back to a default if not set.
- getTimestamp(int) - Method in interface org.apache.spark.sql.Row
-
Returns the value at position i of date type as java.sql.Timestamp.
- getTimeZoneOffset() - Static method in class org.apache.spark.ui.UIUtils
-
- GETTING_RESULT_TIME() - Static method in class org.apache.spark.ui.jobs.TaskDetailsClassNames
-
- GETTING_RESULT_TIME() - Static method in class org.apache.spark.ui.ToolTips
-
- gettingResult() - Method in class org.apache.spark.scheduler.TaskInfo
-
- gettingResultTime() - Method in class org.apache.spark.scheduler.TaskInfo
-
The time when the task started remotely getting the result.
- getTol() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getTol() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getTol() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- getTol() - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- getTol() - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- getTol() - Static method in class org.apache.spark.ml.clustering.KMeans
-
- getTol() - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- getTol() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- getTol() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- getTol() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- getTol() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- getTol() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- getTol() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- getToLowercase() - Method in class org.apache.spark.ml.feature.RegexTokenizer
-
- getTopicConcentration() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- getTopicConcentration() - Static method in class org.apache.spark.ml.clustering.LDA
-
- getTopicConcentration() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- getTopicConcentration() - Method in class org.apache.spark.mllib.clustering.LDA
-
Concentration parameter (commonly named "beta" or "eta") for the prior placed on topics'
distributions over terms.
- getTopicDistributionCol() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- getTopicDistributionCol() - Static method in class org.apache.spark.ml.clustering.LDA
-
- getTopicDistributionCol() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- getTrainRatio() - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- getTrainRatio() - Static method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
-
- getTreeStrategy() - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- getUDTFor(String) - Static method in class org.apache.spark.sql.types.UDTRegistration
-
Returns the Class of UserDefinedType for the name of a given user class.
- getUidMap(Params) - Static method in class org.apache.spark.ml.util.MetaAlgorithmReadWrite
-
Examine the given estimator (which may be a compound estimator) and extract a mapping
from UIDs to corresponding Params instances.
- getUpperBound(double, long, double) - Static method in class org.apache.spark.util.random.BinomialBounds
-
Returns a threshold p such that if we conduct n Bernoulli trials with success rate = p,
it is very unlikely to have less than fraction * n successes.
- getUpperBound(double) - Static method in class org.apache.spark.util.random.PoissonBounds
-
Returns a lambda such that Pr[X < s] is very small, where X ~ Pois(lambda).
- getUsedTimeMs(long) - Static method in class org.apache.spark.util.Utils
-
Return the string to tell how long has passed in milliseconds.
- getUseNodeIdCache() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- getUserCol() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- getUserCol() - Static method in class org.apache.spark.ml.recommendation.ALSModel
-
- getUserJars(SparkConf, boolean) - Static method in class org.apache.spark.util.Utils
-
In YARN mode this method returns a union of the jar files pointed by "spark.jars" and the
"spark.yarn.dist.jars" properties, while in other modes it returns the jar files pointed by
only the "spark.jars" property.
- getValidationTol() - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- getValue(int) - Method in class org.apache.spark.ml.attribute.NominalAttribute
-
Gets a value given its index.
- getValuesMap(Seq<String>) - Method in interface org.apache.spark.sql.Row
-
Returns a Map(name -> value) for the requested fieldNames
For primitive types if value is null it returns 'zero value' specific for primitive
ie.
- getVarianceCol() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- getVarianceCol() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- getVectors() - Method in class org.apache.spark.ml.feature.Word2VecModel
-
Returns a dataframe with two fields, "word" and "vector", with "word" being a String and
and the vector the DenseVector that it is mapped to.
- getVectors() - Method in class org.apache.spark.mllib.feature.Word2VecModel
-
Returns a map of words to their vector representations.
- getVectorSize() - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- getVectorSize() - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- getVocabSize() - Static method in class org.apache.spark.ml.feature.CountVectorizer
-
- getVocabSize() - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- getWeightCol() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getWeightCol() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getWeightCol() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- getWeightCol() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- getWeightCol() - Static method in class org.apache.spark.ml.regression.IsotonicRegression
-
- getWeightCol() - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- getWeightCol() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- getWeightCol() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- getWindowSize() - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- getWindowSize() - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- getWithMean() - Static method in class org.apache.spark.ml.feature.StandardScaler
-
- getWithMean() - Static method in class org.apache.spark.ml.feature.StandardScalerModel
-
- getWithStd() - Static method in class org.apache.spark.ml.feature.StandardScaler
-
- getWithStd() - Static method in class org.apache.spark.ml.feature.StandardScalerModel
-
- Gini - Class in org.apache.spark.mllib.tree.impurity
-
Class for calculating the Gini impurity
(http://en.wikipedia.org/wiki/Decision_tree_learning#Gini_impurity)
during multiclass classification.
- Gini() - Constructor for class org.apache.spark.mllib.tree.impurity.Gini
-
- GLMClassificationModel - Class in org.apache.spark.mllib.classification.impl
-
Helper class for import/export of GLM classification models.
- GLMClassificationModel() - Constructor for class org.apache.spark.mllib.classification.impl.GLMClassificationModel
-
- GLMClassificationModel.SaveLoadV1_0$ - Class in org.apache.spark.mllib.classification.impl
-
- GLMClassificationModel.SaveLoadV1_0$() - Constructor for class org.apache.spark.mllib.classification.impl.GLMClassificationModel.SaveLoadV1_0$
-
- GLMClassificationModel.SaveLoadV1_0$.Data - Class in org.apache.spark.mllib.classification.impl
-
Model data for import/export
- GLMClassificationModel.SaveLoadV1_0$.Data(Vector, double, Option<Object>) - Constructor for class org.apache.spark.mllib.classification.impl.GLMClassificationModel.SaveLoadV1_0$.Data
-
- GLMRegressionModel - Class in org.apache.spark.mllib.regression.impl
-
Helper methods for import/export of GLM regression models.
- GLMRegressionModel() - Constructor for class org.apache.spark.mllib.regression.impl.GLMRegressionModel
-
- GLMRegressionModel.SaveLoadV1_0$ - Class in org.apache.spark.mllib.regression.impl
-
- GLMRegressionModel.SaveLoadV1_0$() - Constructor for class org.apache.spark.mllib.regression.impl.GLMRegressionModel.SaveLoadV1_0$
-
- GLMRegressionModel.SaveLoadV1_0$.Data - Class in org.apache.spark.mllib.regression.impl
-
Model data for model import/export
- GLMRegressionModel.SaveLoadV1_0$.Data(Vector, double) - Constructor for class org.apache.spark.mllib.regression.impl.GLMRegressionModel.SaveLoadV1_0$.Data
-
- glom() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- glom() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- glom() - Static method in class org.apache.spark.api.java.JavaRDD
-
- glom() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return an RDD created by coalescing all elements within each partition into an array.
- glom() - Static method in class org.apache.spark.api.r.RRDD
-
- glom() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- glom() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- glom() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- glom() - Static method in class org.apache.spark.graphx.VertexRDD
-
- glom() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- glom() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- glom() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- glom() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- glom() - Method in class org.apache.spark.rdd.RDD
-
Return an RDD created by coalescing all elements within each partition into an array.
- glom() - Static method in class org.apache.spark.rdd.UnionRDD
-
- glom() - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- glom() - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD is generated by applying glom() to each RDD of
this DStream.
- glom() - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- glom() - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- glom() - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- glom() - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- glom() - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- glom() - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream in which each RDD is generated by applying glom() to each RDD of
this DStream.
- goodnessOfFit() - Method in class org.apache.spark.mllib.stat.test.ChiSqTest.NullHypothesis$
-
- grad() - Method in class org.apache.spark.mllib.optimization.NNLS.Workspace
-
- gradient() - Method in class org.apache.spark.ml.classification.LogisticAggregator
-
- gradient() - Method in class org.apache.spark.ml.regression.AFTAggregator
-
- gradient() - Method in class org.apache.spark.ml.regression.LeastSquaresAggregator
-
- Gradient - Class in org.apache.spark.mllib.optimization
-
:: DeveloperApi ::
Class used to compute the gradient for a loss function, given a single data point.
- Gradient() - Constructor for class org.apache.spark.mllib.optimization.Gradient
-
- gradient(double, double) - Static method in class org.apache.spark.mllib.tree.loss.AbsoluteError
-
Method to calculate the gradients for the gradient boosting calculation for least
absolute error calculation.
- gradient(double, double) - Static method in class org.apache.spark.mllib.tree.loss.LogLoss
-
Method to calculate the loss gradients for the gradient boosting calculation for binary
classification
The gradient with respect to F(x) is: - 4 y / (1 + exp(2 y F(x)))
- gradient(double, double) - Method in interface org.apache.spark.mllib.tree.loss.Loss
-
Method to calculate the gradients for the gradient boosting calculation.
- gradient(double, double) - Static method in class org.apache.spark.mllib.tree.loss.SquaredError
-
Method to calculate the gradients for the gradient boosting calculation for least
squares error calculation.
- GradientBoostedTrees - Class in org.apache.spark.ml.tree.impl
-
- GradientBoostedTrees() - Constructor for class org.apache.spark.ml.tree.impl.GradientBoostedTrees
-
- GradientBoostedTrees - Class in org.apache.spark.mllib.tree
-
A class that implements
Stochastic Gradient Boosting
for regression and binary classification.
- GradientBoostedTrees(BoostingStrategy) - Constructor for class org.apache.spark.mllib.tree.GradientBoostedTrees
-
- GradientBoostedTreesModel - Class in org.apache.spark.mllib.tree.model
-
Represents a gradient boosted trees model.
- GradientBoostedTreesModel(Enumeration.Value, DecisionTreeModel[], double[]) - Constructor for class org.apache.spark.mllib.tree.model.GradientBoostedTreesModel
-
- GradientDescent - Class in org.apache.spark.mllib.optimization
-
Class used to solve an optimization problem using Gradient Descent.
- Graph<VD,ED> - Class in org.apache.spark.graphx
-
The Graph abstractly represents a graph with arbitrary objects
associated with vertices and edges.
- GraphGenerators - Class in org.apache.spark.graphx.util
-
A collection of graph generating functions.
- GraphGenerators() - Constructor for class org.apache.spark.graphx.util.GraphGenerators
-
- GraphImpl<VD,ED> - Class in org.apache.spark.graphx.impl
-
An implementation of
Graph to support computation on graphs.
- GraphLoader - Class in org.apache.spark.graphx
-
Provides utilities for loading
Graphs from files.
- GraphLoader() - Constructor for class org.apache.spark.graphx.GraphLoader
-
- GraphOps<VD,ED> - Class in org.apache.spark.graphx
-
Contains additional functionality for
Graph.
- GraphOps(Graph<VD, ED>, ClassTag<VD>, ClassTag<ED>) - Constructor for class org.apache.spark.graphx.GraphOps
-
- graphToGraphOps(Graph<VD, ED>, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.Graph
-
Implicitly extracts the
GraphOps member from a graph.
- GraphXUtils - Class in org.apache.spark.graphx
-
- GraphXUtils() - Constructor for class org.apache.spark.graphx.GraphXUtils
-
- greater(Duration) - Method in class org.apache.spark.streaming.Duration
-
- greater(Time) - Method in class org.apache.spark.streaming.Time
-
- greaterEq(Duration) - Method in class org.apache.spark.streaming.Duration
-
- greaterEq(Time) - Method in class org.apache.spark.streaming.Time
-
- GreaterThan - Class in org.apache.spark.sql.sources
-
A filter that evaluates to true iff the attribute evaluates to a value
greater than value.
- GreaterThan(String, Object) - Constructor for class org.apache.spark.sql.sources.GreaterThan
-
- GreaterThanOrEqual - Class in org.apache.spark.sql.sources
-
A filter that evaluates to true iff the attribute evaluates to a value
greater than or equal to value.
- GreaterThanOrEqual(String, Object) - Constructor for class org.apache.spark.sql.sources.GreaterThanOrEqual
-
- greatest(Column...) - Static method in class org.apache.spark.sql.functions
-
Returns the greatest value of the list of values, skipping null values.
- greatest(String, String...) - Static method in class org.apache.spark.sql.functions
-
Returns the greatest value of the list of column names, skipping null values.
- greatest(Seq<Column>) - Static method in class org.apache.spark.sql.functions
-
Returns the greatest value of the list of values, skipping null values.
- greatest(String, Seq<String>) - Static method in class org.apache.spark.sql.functions
-
Returns the greatest value of the list of column names, skipping null values.
- gridGraph(SparkContext, int, int) - Static method in class org.apache.spark.graphx.util.GraphGenerators
-
Create rows by cols grid graph with each vertex connected to its
row+1 and col+1 neighbors.
- groupArr() - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
-
- groupBy(Function<T, U>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- groupBy(Function<T, U>, int) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- groupBy(Function<T, U>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- groupBy(Function<T, U>, int) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- groupBy(Function<T, U>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- groupBy(Function<T, U>, int) - Static method in class org.apache.spark.api.java.JavaRDD
-
- groupBy(Function<T, U>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return an RDD of grouped elements.
- groupBy(Function<T, U>, int) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return an RDD of grouped elements.
- groupBy(Function1<T, K>, ClassTag<K>) - Static method in class org.apache.spark.api.r.RRDD
-
- groupBy(Function1<T, K>, int, ClassTag<K>) - Static method in class org.apache.spark.api.r.RRDD
-
- groupBy(Function1<T, K>, Partitioner, ClassTag<K>, Ordering<K>) - Static method in class org.apache.spark.api.r.RRDD
-
- groupBy(Function1<T, K>, ClassTag<K>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- groupBy(Function1<T, K>, int, ClassTag<K>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- groupBy(Function1<T, K>, Partitioner, ClassTag<K>, Ordering<K>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- groupBy(Function1<T, K>, ClassTag<K>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- groupBy(Function1<T, K>, int, ClassTag<K>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- groupBy(Function1<T, K>, Partitioner, ClassTag<K>, Ordering<K>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- groupBy(Function1<T, K>, ClassTag<K>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- groupBy(Function1<T, K>, int, ClassTag<K>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- groupBy(Function1<T, K>, Partitioner, ClassTag<K>, Ordering<K>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- groupBy(Function1<T, K>, ClassTag<K>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- groupBy(Function1<T, K>, int, ClassTag<K>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- groupBy(Function1<T, K>, Partitioner, ClassTag<K>, Ordering<K>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- groupBy(Function1<T, K>, ClassTag<K>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- groupBy(Function1<T, K>, int, ClassTag<K>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- groupBy(Function1<T, K>, Partitioner, ClassTag<K>, Ordering<K>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- groupBy(Function1<T, K>, ClassTag<K>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- groupBy(Function1<T, K>, int, ClassTag<K>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- groupBy(Function1<T, K>, Partitioner, ClassTag<K>, Ordering<K>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- groupBy(Function1<T, K>, ClassTag<K>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- groupBy(Function1<T, K>, int, ClassTag<K>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- groupBy(Function1<T, K>, Partitioner, ClassTag<K>, Ordering<K>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- groupBy(Function1<T, K>, ClassTag<K>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- groupBy(Function1<T, K>, int, ClassTag<K>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- groupBy(Function1<T, K>, Partitioner, ClassTag<K>, Ordering<K>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- groupBy(Function1<T, K>, ClassTag<K>) - Method in class org.apache.spark.rdd.RDD
-
Return an RDD of grouped items.
- groupBy(Function1<T, K>, int, ClassTag<K>) - Method in class org.apache.spark.rdd.RDD
-
Return an RDD of grouped elements.
- groupBy(Function1<T, K>, Partitioner, ClassTag<K>, Ordering<K>) - Method in class org.apache.spark.rdd.RDD
-
Return an RDD of grouped items.
- groupBy(Function1<T, K>, ClassTag<K>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- groupBy(Function1<T, K>, int, ClassTag<K>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- groupBy(Function1<T, K>, Partitioner, ClassTag<K>, Ordering<K>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- groupBy(Column...) - Method in class org.apache.spark.sql.Dataset
-
Groups the Dataset using the specified columns, so we can run aggregation on them.
- groupBy(String, String...) - Method in class org.apache.spark.sql.Dataset
-
Groups the Dataset using the specified columns, so that we can run aggregation on them.
- groupBy(Seq<Column>) - Method in class org.apache.spark.sql.Dataset
-
Groups the Dataset using the specified columns, so we can run aggregation on them.
- groupBy(String, Seq<String>) - Method in class org.apache.spark.sql.Dataset
-
Groups the Dataset using the specified columns, so that we can run aggregation on them.
- groupBy(Function1<A, K>) - Static method in class org.apache.spark.sql.types.StructType
-
- groupBy$default$4(Function1<T, K>, Partitioner) - Static method in class org.apache.spark.api.r.RRDD
-
- groupBy$default$4(Function1<T, K>, Partitioner) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- groupBy$default$4(Function1<T, K>, Partitioner) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- groupBy$default$4(Function1<T, K>, Partitioner) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- groupBy$default$4(Function1<T, K>, Partitioner) - Static method in class org.apache.spark.graphx.VertexRDD
-
- groupBy$default$4(Function1<T, K>, Partitioner) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- groupBy$default$4(Function1<T, K>, Partitioner) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- groupBy$default$4(Function1<T, K>, Partitioner) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- groupBy$default$4(Function1<T, K>, Partitioner) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- groupBy$default$4(Function1<T, K>, Partitioner) - Static method in class org.apache.spark.rdd.UnionRDD
-
- groupByKey(Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Group the values for each key in the RDD into a single sequence.
- groupByKey(int) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Group the values for each key in the RDD into a single sequence.
- groupByKey() - Method in class org.apache.spark.api.java.JavaPairRDD
-
Group the values for each key in the RDD into a single sequence.
- groupByKey(Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Group the values for each key in the RDD into a single sequence.
- groupByKey(int) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Group the values for each key in the RDD into a single sequence.
- groupByKey() - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Group the values for each key in the RDD into a single sequence.
- groupByKey(Function1<T, K>, Encoder<K>) - Method in class org.apache.spark.sql.Dataset
-
:: Experimental ::
(Scala-specific)
Returns a
KeyValueGroupedDataset where the data is grouped by the given key
func.
- groupByKey(MapFunction<T, K>, Encoder<K>) - Method in class org.apache.spark.sql.Dataset
-
:: Experimental ::
(Java-specific)
Returns a
KeyValueGroupedDataset where the data is grouped by the given key
func.
- groupByKey() - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying groupByKey to each RDD.
- groupByKey(int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying groupByKey to each RDD.
- groupByKey(Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying groupByKey on each RDD of this DStream.
- groupByKey() - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- groupByKey(int) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- groupByKey(Partitioner) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- groupByKey() - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- groupByKey(int) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- groupByKey(Partitioner) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- groupByKey() - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying groupByKey to each RDD.
- groupByKey(int) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying groupByKey to each RDD.
- groupByKey(Partitioner) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying groupByKey on each RDD.
- groupByKeyAndWindow(Duration) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying groupByKey over a sliding window.
- groupByKeyAndWindow(Duration, Duration) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying groupByKey over a sliding window.
- groupByKeyAndWindow(Duration, Duration, int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying groupByKey over a sliding window on this DStream.
- groupByKeyAndWindow(Duration, Duration, Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying groupByKey over a sliding window on this DStream.
- groupByKeyAndWindow(Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- groupByKeyAndWindow(Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- groupByKeyAndWindow(Duration, Duration, int) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- groupByKeyAndWindow(Duration, Duration, Partitioner) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- groupByKeyAndWindow(Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- groupByKeyAndWindow(Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- groupByKeyAndWindow(Duration, Duration, int) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- groupByKeyAndWindow(Duration, Duration, Partitioner) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- groupByKeyAndWindow(Duration) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying groupByKey over a sliding window.
- groupByKeyAndWindow(Duration, Duration) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying groupByKey over a sliding window.
- groupByKeyAndWindow(Duration, Duration, int) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying groupByKey over a sliding window on this DStream.
- groupByKeyAndWindow(Duration, Duration, Partitioner) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Create a new DStream by applying groupByKey over a sliding window on this DStream.
- grouped(int) - Static method in class org.apache.spark.sql.types.StructType
-
- groupEdges(Function2<ED, ED, ED>) - Method in class org.apache.spark.graphx.Graph
-
Merges multiple edges between two vertices into a single edge.
- groupEdges(Function2<ED, ED, ED>) - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- groupHash() - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
-
- grouping(Column) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: indicates whether a specified column in a GROUP BY list is aggregated
or not, returns 1 for aggregated or 0 for not aggregated in the result set.
- grouping(String) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: indicates whether a specified column in a GROUP BY list is aggregated
or not, returns 1 for aggregated or 0 for not aggregated in the result set.
- grouping_id(Seq<Column>) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the level of grouping, equals to
- grouping_id(String, Seq<String>) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the level of grouping, equals to
- GroupMappingServiceProvider - Interface in org.apache.spark.security
-
This Spark trait is used for mapping a given userName to a set of groups which it belongs to.
- groupWith(JavaPairRDD<K, W>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Alias for cogroup.
- groupWith(JavaPairRDD<K, W1>, JavaPairRDD<K, W2>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Alias for cogroup.
- groupWith(JavaPairRDD<K, W1>, JavaPairRDD<K, W2>, JavaPairRDD<K, W3>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Alias for cogroup.
- groupWith(RDD<Tuple2<K, W>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Alias for cogroup.
- groupWith(RDD<Tuple2<K, W1>>, RDD<Tuple2<K, W2>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Alias for cogroup.
- groupWith(RDD<Tuple2<K, W1>>, RDD<Tuple2<K, W2>>, RDD<Tuple2<K, W3>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Alias for cogroup.
- gt(double) - Static method in class org.apache.spark.ml.param.ParamValidators
-
Check if value > lowerBound
- gt(Object) - Method in class org.apache.spark.sql.Column
-
Greater than.
- gtEq(double) - Static method in class org.apache.spark.ml.param.ParamValidators
-
Check if value >= lowerBound
- guard(Function0<Parsers.Parser<T>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- i() - Method in class org.apache.spark.mllib.linalg.distributed.MatrixEntry
-
- id() - Method in class org.apache.spark.Accumulable
-
Deprecated.
- id() - Static method in class org.apache.spark.Accumulator
-
Deprecated.
- id() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- id() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- id() - Static method in class org.apache.spark.api.java.JavaRDD
-
- id() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
A unique ID for this RDD (within its SparkContext).
- id() - Static method in class org.apache.spark.api.r.RRDD
-
- id() - Method in class org.apache.spark.broadcast.Broadcast
-
- id() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- id() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- id() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- id() - Static method in class org.apache.spark.graphx.VertexRDD
-
- id() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData
-
- id() - Method in class org.apache.spark.mllib.clustering.PowerIterationClustering.Assignment
-
- id() - Method in class org.apache.spark.mllib.tree.model.Node
-
- id() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- id() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- id() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- id() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- id() - Method in class org.apache.spark.rdd.RDD
-
A unique ID for this RDD (within its SparkContext).
- id() - Static method in class org.apache.spark.rdd.UnionRDD
-
- id() - Method in class org.apache.spark.scheduler.AccumulableInfo
-
- id() - Method in class org.apache.spark.scheduler.TaskInfo
-
- id() - Method in interface org.apache.spark.sql.streaming.StreamingQuery
-
Returns the unique id of this query.
- id() - Method in class org.apache.spark.sql.streaming.StreamingQueryInfo
-
- id() - Method in class org.apache.spark.status.api.v1.AccumulableInfo
-
- id() - Method in class org.apache.spark.status.api.v1.ApplicationInfo
-
- id() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
-
- id() - Method in class org.apache.spark.status.api.v1.RDDStorageInfo
-
- id() - Method in class org.apache.spark.storage.RDDInfo
-
- id() - Method in class org.apache.spark.streaming.dstream.InputDStream
-
This is an unique identifier for the input stream.
- id() - Method in class org.apache.spark.streaming.scheduler.OutputOperationInfo
-
- id() - Method in class org.apache.spark.util.AccumulatorV2
-
Returns the id of this accumulator, can only be called after registration.
- Identifiable - Interface in org.apache.spark.ml.util
-
:: DeveloperApi ::
- IDF - Class in org.apache.spark.ml.feature
-
Compute the Inverse Document Frequency (IDF) given a collection of documents.
- IDF(String) - Constructor for class org.apache.spark.ml.feature.IDF
-
- IDF() - Constructor for class org.apache.spark.ml.feature.IDF
-
- idf() - Method in class org.apache.spark.ml.feature.IDFModel
-
Returns the IDF vector.
- IDF - Class in org.apache.spark.mllib.feature
-
Inverse document frequency (IDF).
- IDF(int) - Constructor for class org.apache.spark.mllib.feature.IDF
-
- IDF() - Constructor for class org.apache.spark.mllib.feature.IDF
-
- idf() - Method in class org.apache.spark.mllib.feature.IDF.DocumentFrequencyAggregator
-
Returns the current IDF vector.
- idf() - Method in class org.apache.spark.mllib.feature.IDFModel
-
- IDF.DocumentFrequencyAggregator - Class in org.apache.spark.mllib.feature
-
Document frequency aggregator.
- IDF.DocumentFrequencyAggregator(int) - Constructor for class org.apache.spark.mllib.feature.IDF.DocumentFrequencyAggregator
-
- IDF.DocumentFrequencyAggregator() - Constructor for class org.apache.spark.mllib.feature.IDF.DocumentFrequencyAggregator
-
- IDFModel - Class in org.apache.spark.ml.feature
-
- IDFModel - Class in org.apache.spark.mllib.feature
-
Represents an IDF model that can transform term frequency vectors.
- ifNotExists() - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- ignoreIfExists() - Method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- implicitPrefs() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- implicits() - Method in class org.apache.spark.sql.SparkSession
-
Accessor for nested Scala object
- implicits() - Method in class org.apache.spark.sql.SQLContext
-
Accessor for nested Scala object
- improveException(Object, NotSerializableException) - Static method in class org.apache.spark.serializer.SerializationDebugger
-
Improve the given NotSerializableException with the serialization path leading from the given
object to the problematic object.
- Impurities - Class in org.apache.spark.mllib.tree.impurity
-
Factory for Impurity instances.
- Impurities() - Constructor for class org.apache.spark.mllib.tree.impurity.Impurities
-
- impurity() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- impurity() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- impurity() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- impurity() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- impurity() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- impurity() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- impurity() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- impurity() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- impurity() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- impurity() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- impurity() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- impurity() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- impurity() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData
-
- impurity() - Method in class org.apache.spark.ml.tree.InternalNode
-
- impurity() - Method in class org.apache.spark.ml.tree.LeafNode
-
- impurity() - Method in class org.apache.spark.ml.tree.Node
-
Impurity measure at this node (for training data)
- impurity() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- Impurity - Interface in org.apache.spark.mllib.tree.impurity
-
Trait for calculating information gain.
- impurity() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData
-
- impurity() - Method in class org.apache.spark.mllib.tree.model.InformationGainStats
-
- impurity() - Method in class org.apache.spark.mllib.tree.model.Node
-
- impurityStats() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData
-
- In() - Static method in class org.apache.spark.graphx.EdgeDirection
-
Edges arriving at a vertex.
- In - Class in org.apache.spark.sql.sources
-
A filter that evaluates to true iff the attribute evaluates to one of the values in the array.
- In(String, Object[]) - Constructor for class org.apache.spark.sql.sources.In
-
- INACTIVE() - Static method in class org.apache.spark.streaming.scheduler.ReceiverState
-
- inArray(Object) - Static method in class org.apache.spark.ml.param.ParamValidators
-
Check for value in an allowed set of values.
- inArray(List<T>) - Static method in class org.apache.spark.ml.param.ParamValidators
-
Check for value in an allowed set of values.
- IncompatibleMergeException - Exception in org.apache.spark.util.sketch
-
- IncompatibleMergeException(String) - Constructor for exception org.apache.spark.util.sketch.IncompatibleMergeException
-
- inDegrees() - Method in class org.apache.spark.graphx.GraphOps
-
The in-degree of each vertex in the graph.
- independence() - Method in class org.apache.spark.mllib.stat.test.ChiSqTest.NullHypothesis$
-
- index() - Method in class org.apache.spark.ml.attribute.Attribute
-
Index of the attribute.
- INDEX() - Static method in class org.apache.spark.ml.attribute.AttributeKeys
-
- index() - Method in class org.apache.spark.ml.attribute.BinaryAttribute
-
- index() - Method in class org.apache.spark.ml.attribute.NominalAttribute
-
- index() - Method in class org.apache.spark.ml.attribute.NumericAttribute
-
- index() - Static method in class org.apache.spark.ml.attribute.UnresolvedAttribute
-
- index(int, int) - Method in interface org.apache.spark.ml.linalg.Matrix
-
Return the index for the (i, j)-th element in the backing array.
- index() - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRow
-
- index(int, int) - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Return the index for the (i, j)-th element in the backing array.
- index() - Method in interface org.apache.spark.Partition
-
Get the partition's index within its parent RDD
- index() - Method in class org.apache.spark.scheduler.TaskInfo
-
- index() - Method in class org.apache.spark.status.api.v1.TaskData
-
- IndexedRow - Class in org.apache.spark.mllib.linalg.distributed
-
- IndexedRow(long, Vector) - Constructor for class org.apache.spark.mllib.linalg.distributed.IndexedRow
-
- IndexedRowMatrix - Class in org.apache.spark.mllib.linalg.distributed
-
- IndexedRowMatrix(RDD<IndexedRow>, long, int) - Constructor for class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
-
- IndexedRowMatrix(RDD<IndexedRow>) - Constructor for class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
-
Alternative constructor leaving matrix dimensions to be determined automatically.
- indexOf(String) - Method in class org.apache.spark.ml.attribute.AttributeGroup
-
Index of an attribute specified by name.
- indexOf(String) - Method in class org.apache.spark.ml.attribute.NominalAttribute
-
Index of a specific value.
- indexOf(Object) - Method in class org.apache.spark.mllib.feature.HashingTF
-
Returns the index of the input term.
- indexOf(B) - Static method in class org.apache.spark.sql.types.StructType
-
- indexOf(B, int) - Static method in class org.apache.spark.sql.types.StructType
-
- indexOfSlice(GenSeq<B>) - Static method in class org.apache.spark.sql.types.StructType
-
- indexOfSlice(GenSeq<B>, int) - Static method in class org.apache.spark.sql.types.StructType
-
- indexToLevel(int) - Static method in class org.apache.spark.mllib.tree.model.Node
-
Return the level of a tree which the given node is in.
- IndexToString - Class in org.apache.spark.ml.feature
-
A Transformer that maps a column of indices back to a new column of corresponding
string values.
- IndexToString() - Constructor for class org.apache.spark.ml.feature.IndexToString
-
- indexWhere(Function1<A, Object>) - Static method in class org.apache.spark.sql.types.StructType
-
- indexWhere(Function1<A, Object>, int) - Static method in class org.apache.spark.sql.types.StructType
-
- indices() - Method in class org.apache.spark.ml.feature.VectorSlicer
-
An array of indices to select features from a vector column.
- indices() - Method in class org.apache.spark.ml.linalg.SparseVector
-
- indices() - Method in class org.apache.spark.mllib.linalg.SparseVector
-
- indices() - Static method in class org.apache.spark.sql.types.StructType
-
- inferSchema(SparkSession, Map<String, String>, Seq<FileStatus>) - Method in class org.apache.spark.sql.hive.orc.OrcFileFormat
-
- infoChanged(SparkAppHandle) - Method in interface org.apache.spark.launcher.SparkAppHandle.Listener
-
Callback for changes in any information that is not the handle's state.
- infoGain() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData
-
- InformationGainStats - Class in org.apache.spark.mllib.tree.model
-
:: DeveloperApi ::
Information gain statistics for each split
param: gain information gain value
param: impurity current node impurity
param: leftImpurity left node impurity
param: rightImpurity right node impurity
param: leftPredict left node predict
param: rightPredict right node predict
- InformationGainStats(double, double, double, double, Predict, Predict) - Constructor for class org.apache.spark.mllib.tree.model.InformationGainStats
-
- init() - Static method in class org.apache.spark.sql.types.StructType
-
- initcap(Column) - Static method in class org.apache.spark.sql.functions
-
Returns a new string column by converting the first letter of each word to uppercase.
- initCause(Throwable) - Static method in exception org.apache.spark.sql.AnalysisException
-
- initCause(Throwable) - Static method in exception org.apache.spark.sql.streaming.StreamingQueryException
-
- initDaemon(Logger) - Static method in class org.apache.spark.util.Utils
-
Utility function that should be called early in main() for daemons to set up some common
diagnostic state.
- initialHash() - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
-
- initialize(double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Binomial$
-
- initialize(double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gamma$
-
- initialize(double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gaussian$
-
- initialize(double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Poisson$
-
- initialize(RDD<Tuple2<Object, Vector>>, LDA) - Method in interface org.apache.spark.mllib.clustering.LDAOptimizer
-
Initializer for the optimizer.
- initialize(MutableAggregationBuffer) - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
-
Initializes the given aggregation buffer, i.e.
- Initialized() - Static method in class org.apache.spark.rdd.CheckpointState
-
- initialState(RDD<Tuple2<KeyType, StateType>>) - Method in class org.apache.spark.streaming.StateSpec
-
Set the RDD containing the initial states that will be used by `mapWithState`
- initialState(JavaPairRDD<KeyType, StateType>) - Method in class org.apache.spark.streaming.StateSpec
-
Set the RDD containing the initial states that will be used by `mapWithState`
- initialValue() - Method in class org.apache.spark.partial.PartialResult
-
- initialWeights() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- initInputSerDe(Seq<Expression>) - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- initMode() - Static method in class org.apache.spark.ml.clustering.KMeans
-
- initMode() - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- initOutputSerDe(Seq<Attribute>) - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- inits() - Static method in class org.apache.spark.sql.types.StructType
-
- initSteps() - Static method in class org.apache.spark.ml.clustering.KMeans
-
- initSteps() - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- innerChildren() - Method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- InnerClosureFinder - Class in org.apache.spark.util
-
- InnerClosureFinder(Set<Class<?>>) - Constructor for class org.apache.spark.util.InnerClosureFinder
-
- innerJoin(EdgeRDD<ED2>, Function4<Object, Object, ED, ED2, ED3>, ClassTag<ED2>, ClassTag<ED3>) - Method in class org.apache.spark.graphx.EdgeRDD
-
Inner joins this EdgeRDD with another EdgeRDD, assuming both are partitioned using the same
PartitionStrategy.
- innerJoin(EdgeRDD<ED2>, Function4<Object, Object, ED, ED2, ED3>, ClassTag<ED2>, ClassTag<ED3>) - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- innerJoin(RDD<Tuple2<Object, U>>, Function3<Object, VD, U, VD2>, ClassTag<U>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- innerJoin(RDD<Tuple2<Object, U>>, Function3<Object, VD, U, VD2>, ClassTag<U>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.VertexRDD
-
Inner joins this VertexRDD with an RDD containing vertex attribute pairs.
- innerZipJoin(VertexRDD<U>, Function3<Object, VD, U, VD2>, ClassTag<U>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- innerZipJoin(VertexRDD<U>, Function3<Object, VD, U, VD2>, ClassTag<U>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.VertexRDD
-
Efficiently inner joins this VertexRDD with another VertexRDD sharing the same index.
- input() - Method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- INPUT() - Static method in class org.apache.spark.ui.ToolTips
-
- input_file_name() - Static method in class org.apache.spark.sql.functions
-
Creates a string column for the file name of the current Spark task.
- INPUT_METRICS_PREFIX() - Static method in class org.apache.spark.InternalAccumulator
-
- inputBytes() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
-
- inputBytes() - Method in class org.apache.spark.status.api.v1.StageData
-
- inputBytes() - Method in class org.apache.spark.ui.jobs.UIData.ExecutorSummary
-
- inputBytes() - Method in class org.apache.spark.ui.jobs.UIData.StageUIData
-
- inputCol() - Static method in class org.apache.spark.ml.feature.Binarizer
-
- inputCol() - Static method in class org.apache.spark.ml.feature.Bucketizer
-
- inputCol() - Static method in class org.apache.spark.ml.feature.CountVectorizer
-
- inputCol() - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- inputCol() - Static method in class org.apache.spark.ml.feature.DCT
-
- inputCol() - Static method in class org.apache.spark.ml.feature.ElementwiseProduct
-
- inputCol() - Static method in class org.apache.spark.ml.feature.HashingTF
-
- inputCol() - Static method in class org.apache.spark.ml.feature.IDF
-
- inputCol() - Static method in class org.apache.spark.ml.feature.IDFModel
-
- inputCol() - Static method in class org.apache.spark.ml.feature.IndexToString
-
- inputCol() - Static method in class org.apache.spark.ml.feature.MaxAbsScaler
-
- inputCol() - Static method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- inputCol() - Static method in class org.apache.spark.ml.feature.MinMaxScaler
-
- inputCol() - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- inputCol() - Static method in class org.apache.spark.ml.feature.NGram
-
- inputCol() - Static method in class org.apache.spark.ml.feature.Normalizer
-
- inputCol() - Static method in class org.apache.spark.ml.feature.OneHotEncoder
-
- inputCol() - Static method in class org.apache.spark.ml.feature.PCA
-
- inputCol() - Static method in class org.apache.spark.ml.feature.PCAModel
-
- inputCol() - Static method in class org.apache.spark.ml.feature.PolynomialExpansion
-
- inputCol() - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- inputCol() - Static method in class org.apache.spark.ml.feature.RegexTokenizer
-
- inputCol() - Static method in class org.apache.spark.ml.feature.StandardScaler
-
- inputCol() - Static method in class org.apache.spark.ml.feature.StandardScalerModel
-
- inputCol() - Static method in class org.apache.spark.ml.feature.StopWordsRemover
-
- inputCol() - Static method in class org.apache.spark.ml.feature.StringIndexer
-
- inputCol() - Static method in class org.apache.spark.ml.feature.StringIndexerModel
-
- inputCol() - Static method in class org.apache.spark.ml.feature.Tokenizer
-
- inputCol() - Static method in class org.apache.spark.ml.feature.VectorIndexer
-
- inputCol() - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- inputCol() - Static method in class org.apache.spark.ml.feature.VectorSlicer
-
- inputCol() - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- inputCol() - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- inputCols() - Static method in class org.apache.spark.ml.feature.Interaction
-
- inputCols() - Static method in class org.apache.spark.ml.feature.VectorAssembler
-
- inputDStream() - Method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- inputDStream() - Method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- inputDStream() - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- inputDStream() - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- InputDStream<T> - Class in org.apache.spark.streaming.dstream
-
This is the abstract base class for all input streams.
- InputDStream(StreamingContext, ClassTag<T>) - Constructor for class org.apache.spark.streaming.dstream.InputDStream
-
- InputFileNameHolder - Class in org.apache.spark.rdd
-
This holds file names of the current Spark task.
- InputFileNameHolder() - Constructor for class org.apache.spark.rdd.InputFileNameHolder
-
- inputFiles() - Method in class org.apache.spark.sql.Dataset
-
Returns a best-effort snapshot of the files that compose this Dataset.
- inputFormat() - Method in class org.apache.spark.sql.internal.HiveSerDe
-
- inputFormatClazz() - Method in class org.apache.spark.scheduler.InputFormatInfo
-
- inputFormatClazz() - Method in class org.apache.spark.scheduler.SplitInfo
-
- InputFormatInfo - Class in org.apache.spark.scheduler
-
:: DeveloperApi ::
Parses and holds information about inputFormat (and files) specified as a parameter.
- InputFormatInfo(Configuration, Class<?>, String) - Constructor for class org.apache.spark.scheduler.InputFormatInfo
-
- InputMetricDistributions - Class in org.apache.spark.status.api.v1
-
- InputMetrics - Class in org.apache.spark.status.api.v1
-
- inputMetrics() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
-
- inputMetrics() - Method in class org.apache.spark.status.api.v1.TaskMetrics
-
- inputMetrics() - Method in class org.apache.spark.ui.jobs.UIData.TaskMetricsUIData
-
- inputRecords() - Method in class org.apache.spark.status.api.v1.StageData
-
- inputRecords() - Method in class org.apache.spark.ui.jobs.UIData.ExecutorSummary
-
- inputRecords() - Method in class org.apache.spark.ui.jobs.UIData.StageUIData
-
- inputRowFormat() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- inputRowFormatMap() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- inputSchema() - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
-
A StructType represents data types of input arguments of this aggregate function.
- inputSerdeClass() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- inputSerdeProps() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- inputSet() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- inputSet() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- inputSet() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- inputStreamId() - Method in class org.apache.spark.streaming.scheduler.StreamInputInfo
-
- inputTypes() - Method in class org.apache.spark.sql.expressions.UserDefinedFunction
-
- inRange(double, double, boolean, boolean) - Static method in class org.apache.spark.ml.param.ParamValidators
-
Check for value in range lowerBound to upperBound.
- inRange(double, double) - Static method in class org.apache.spark.ml.param.ParamValidators
-
Version of inRange() which uses inclusive be default: [lowerBound, upperBound]
- insert(Dataset<Row>, boolean) - Method in interface org.apache.spark.sql.sources.InsertableRelation
-
- InsertableRelation - Interface in org.apache.spark.sql.sources
-
::DeveloperApi::
A BaseRelation that can be used to insert data into it through the insert method.
- insertInto(String) - Method in class org.apache.spark.sql.DataFrameWriter
-
Inserts the content of the DataFrame to the specified table.
- InsertIntoHiveTable - Class in org.apache.spark.sql.hive.execution
-
- InsertIntoHiveTable(org.apache.spark.sql.hive.MetastoreRelation, Map<String, Option<String>>, SparkPlan, boolean, boolean) - Constructor for class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- inShutdown() - Static method in class org.apache.spark.util.ShutdownHookManager
-
Detect whether this thread might be executing a shutdown hook.
- inspectorToDataType(ObjectInspector) - Static method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- inspectorToDataType(ObjectInspector) - Static method in class org.apache.spark.sql.hive.orc.OrcRelation
-
- instance() - Static method in class org.apache.spark.mllib.tree.impurity.Entropy
-
Get this impurity instance.
- instance() - Static method in class org.apache.spark.mllib.tree.impurity.Gini
-
Get this impurity instance.
- instance() - Static method in class org.apache.spark.mllib.tree.impurity.Variance
-
Get this impurity instance.
- INSTANCE - Static variable in class org.apache.spark.serializer.DummySerializerInstance
-
- instr(Column, String) - Static method in class org.apache.spark.sql.functions
-
Locate the position of the first occurrence of substr column in the given string.
- INT() - Static method in class org.apache.spark.sql.Encoders
-
An encoder for nullable int type.
- intAccumulator(int) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Deprecated.
use sc().longAccumulator(). Since 2.0.0.
- intAccumulator(int, String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Deprecated.
use sc().longAccumulator(String). Since 2.0.0.
- IntArrayParam - Class in org.apache.spark.ml.param
-
:: DeveloperApi ::
Specialized version of Param[Array[Int} for Java.
- IntArrayParam(Params, String, String, Function1<int[], Object>) - Constructor for class org.apache.spark.ml.param.IntArrayParam
-
- IntArrayParam(Params, String, String) - Constructor for class org.apache.spark.ml.param.IntArrayParam
-
- IntegerType - Static variable in class org.apache.spark.sql.types.DataTypes
-
Gets the IntegerType object.
- IntegerType - Class in org.apache.spark.sql.types
-
:: DeveloperApi ::
The data type representing Int values.
- INTER_JOB_WAIT_MS() - Static method in class org.apache.spark.ui.UIWorkloadGenerator
-
- Interaction - Class in org.apache.spark.ml.feature
-
Implements the feature interaction transform.
- Interaction(String) - Constructor for class org.apache.spark.ml.feature.Interaction
-
- Interaction() - Constructor for class org.apache.spark.ml.feature.Interaction
-
- intercept() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- intercept() - Method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- intercept() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- intercept() - Method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- intercept() - Method in class org.apache.spark.mllib.classification.impl.GLMClassificationModel.SaveLoadV1_0$.Data
-
- intercept() - Method in class org.apache.spark.mllib.classification.LogisticRegressionModel
-
- intercept() - Method in class org.apache.spark.mllib.classification.SVMModel
-
- intercept() - Method in class org.apache.spark.mllib.regression.GeneralizedLinearModel
-
- intercept() - Method in class org.apache.spark.mllib.regression.impl.GLMRegressionModel.SaveLoadV1_0$.Data
-
- intercept() - Method in class org.apache.spark.mllib.regression.LassoModel
-
- intercept() - Method in class org.apache.spark.mllib.regression.LinearRegressionModel
-
- intercept() - Method in class org.apache.spark.mllib.regression.RidgeRegressionModel
-
- intermediateStorageLevel() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- InternalAccumulator - Class in org.apache.spark
-
A collection of fields and methods concerned with internal accumulators that represent
task level metrics.
- InternalAccumulator() - Constructor for class org.apache.spark.InternalAccumulator
-
- InternalAccumulator.input$ - Class in org.apache.spark
-
- InternalAccumulator.input$() - Constructor for class org.apache.spark.InternalAccumulator.input$
-
- InternalAccumulator.output$ - Class in org.apache.spark
-
- InternalAccumulator.output$() - Constructor for class org.apache.spark.InternalAccumulator.output$
-
- InternalAccumulator.shuffleRead$ - Class in org.apache.spark
-
- InternalAccumulator.shuffleRead$() - Constructor for class org.apache.spark.InternalAccumulator.shuffleRead$
-
- InternalAccumulator.shuffleWrite$ - Class in org.apache.spark
-
- InternalAccumulator.shuffleWrite$() - Constructor for class org.apache.spark.InternalAccumulator.shuffleWrite$
-
- InternalNode - Class in org.apache.spark.ml.tree
-
Internal Decision Tree node.
- InternalOutputModes - Class in org.apache.spark.sql
-
Internal helper class to generate objects representing various OutputModes,
- InternalOutputModes() - Constructor for class org.apache.spark.sql.InternalOutputModes
-
- InternalOutputModes.Append$ - Class in org.apache.spark.sql
-
OutputMode in which only the new rows in the streaming DataFrame/Dataset will be
written to the sink.
- InternalOutputModes.Append$() - Constructor for class org.apache.spark.sql.InternalOutputModes.Append$
-
- InternalOutputModes.Complete$ - Class in org.apache.spark.sql
-
OutputMode in which all the rows in the streaming DataFrame/Dataset will be written
to the sink every time these is some updates.
- InternalOutputModes.Complete$() - Constructor for class org.apache.spark.sql.InternalOutputModes.Complete$
-
- InternalOutputModes.Update$ - Class in org.apache.spark.sql
-
OutputMode in which only the rows in the streaming DataFrame/Dataset that were updated will be
written to the sink every time these is some updates.
- InternalOutputModes.Update$() - Constructor for class org.apache.spark.sql.InternalOutputModes.Update$
-
- InterruptibleIterator<T> - Class in org.apache.spark
-
:: DeveloperApi ::
An iterator that wraps around an existing iterator to provide task killing functionality.
- InterruptibleIterator(TaskContext, Iterator<T>) - Constructor for class org.apache.spark.InterruptibleIterator
-
- interruptThread() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillTask
-
- interruptThread() - Method in class org.apache.spark.scheduler.local.KillTask
-
- intersect(Dataset<T>) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset containing rows only in both this Dataset and another Dataset.
- intersect(GenSeq<B>) - Static method in class org.apache.spark.sql.types.StructType
-
- intersection(JavaDoubleRDD) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Return the intersection of this RDD and another one.
- intersection(JavaPairRDD<K, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return the intersection of this RDD and another one.
- intersection(JavaRDD<T>) - Method in class org.apache.spark.api.java.JavaRDD
-
Return the intersection of this RDD and another one.
- intersection(RDD<T>) - Static method in class org.apache.spark.api.r.RRDD
-
- intersection(RDD<T>, Partitioner, Ordering<T>) - Static method in class org.apache.spark.api.r.RRDD
-
- intersection(RDD<T>, int) - Static method in class org.apache.spark.api.r.RRDD
-
- intersection(RDD<T>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- intersection(RDD<T>, Partitioner, Ordering<T>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- intersection(RDD<T>, int) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- intersection(RDD<T>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- intersection(RDD<T>, Partitioner, Ordering<T>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- intersection(RDD<T>, int) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- intersection(RDD<T>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- intersection(RDD<T>, Partitioner, Ordering<T>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- intersection(RDD<T>, int) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- intersection(RDD<T>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- intersection(RDD<T>, Partitioner, Ordering<T>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- intersection(RDD<T>, int) - Static method in class org.apache.spark.graphx.VertexRDD
-
- intersection(RDD<T>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- intersection(RDD<T>, Partitioner, Ordering<T>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- intersection(RDD<T>, int) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- intersection(RDD<T>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- intersection(RDD<T>, Partitioner, Ordering<T>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- intersection(RDD<T>, int) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- intersection(RDD<T>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- intersection(RDD<T>, Partitioner, Ordering<T>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- intersection(RDD<T>, int) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- intersection(RDD<T>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- intersection(RDD<T>, Partitioner, Ordering<T>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- intersection(RDD<T>, int) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- intersection(RDD<T>) - Method in class org.apache.spark.rdd.RDD
-
Return the intersection of this RDD and another one.
- intersection(RDD<T>, Partitioner, Ordering<T>) - Method in class org.apache.spark.rdd.RDD
-
Return the intersection of this RDD and another one.
- intersection(RDD<T>, int) - Method in class org.apache.spark.rdd.RDD
-
Return the intersection of this RDD and another one.
- intersection(RDD<T>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- intersection(RDD<T>, Partitioner, Ordering<T>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- intersection(RDD<T>, int) - Static method in class org.apache.spark.rdd.UnionRDD
-
- intersection$default$3(RDD<T>, Partitioner) - Static method in class org.apache.spark.api.r.RRDD
-
- intersection$default$3(RDD<T>, Partitioner) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- intersection$default$3(RDD<T>, Partitioner) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- intersection$default$3(RDD<T>, Partitioner) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- intersection$default$3(RDD<T>, Partitioner) - Static method in class org.apache.spark.graphx.VertexRDD
-
- intersection$default$3(RDD<T>, Partitioner) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- intersection$default$3(RDD<T>, Partitioner) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- intersection$default$3(RDD<T>, Partitioner) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- intersection$default$3(RDD<T>, Partitioner) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- intersection$default$3(RDD<T>, Partitioner) - Static method in class org.apache.spark.rdd.UnionRDD
-
- intervalMs() - Method in class org.apache.spark.sql.streaming.ProcessingTime
-
- IntParam - Class in org.apache.spark.ml.param
-
:: DeveloperApi ::
Specialized version of Param[Int] for Java.
- IntParam(String, String, String, Function1<Object, Object>) - Constructor for class org.apache.spark.ml.param.IntParam
-
- IntParam(String, String, String) - Constructor for class org.apache.spark.ml.param.IntParam
-
- IntParam(Identifiable, String, String, Function1<Object, Object>) - Constructor for class org.apache.spark.ml.param.IntParam
-
- IntParam(Identifiable, String, String) - Constructor for class org.apache.spark.ml.param.IntParam
-
- IntParam - Class in org.apache.spark.util
-
An extractor object for parsing strings into integers.
- IntParam() - Constructor for class org.apache.spark.util.IntParam
-
- inverse() - Method in class org.apache.spark.ml.feature.DCT
-
Indicates whether to perform the inverse DCT (true) or forward DCT (false).
- inverse(double[], int) - Static method in class org.apache.spark.mllib.linalg.CholeskyDecomposition
-
Computes the inverse of a real symmetric positive definite matrix A
using the Cholesky factorization A = U**T*U.
- invoke(Class<?>, Object, String, Seq<Tuple2<Class<?>, Object>>) - Static method in class org.apache.spark.util.Utils
-
- invokedMethod(Object, Class<?>, String) - Static method in class org.apache.spark.graphx.util.BytecodeUtils
-
Test whether the given closure invokes the specified method in the specified class.
- invokeWriteReplace(Object) - Method in class org.apache.spark.serializer.SerializationDebugger.ObjectStreamClassMethods
-
- ioschema() - Method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- is32BitDecimalType(DataType) - Static method in class org.apache.spark.sql.types.DecimalType
-
Returns if dt is a DecimalType that fits inside an int
- is64BitDecimalType(DataType) - Static method in class org.apache.spark.sql.types.DecimalType
-
Returns if dt is a DecimalType that fits inside a long
- isActive() - Method in interface org.apache.spark.sql.streaming.StreamingQuery
-
Whether the query is currently active or not
- isActive() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
-
- isAddIntercept() - Static method in class org.apache.spark.mllib.classification.LogisticRegressionWithSGD
-
- isAddIntercept() - Static method in class org.apache.spark.mllib.classification.SVMWithSGD
-
- isAddIntercept() - Method in class org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm
-
Get if the algorithm uses addIntercept
- isAddIntercept() - Static method in class org.apache.spark.mllib.regression.LassoWithSGD
-
- isAddIntercept() - Static method in class org.apache.spark.mllib.regression.LinearRegressionWithSGD
-
- isAddIntercept() - Static method in class org.apache.spark.mllib.regression.RidgeRegressionWithSGD
-
- isAllowed(Enumeration.Value, Enumeration.Value) - Static method in class org.apache.spark.scheduler.TaskLocality
-
- isBatchingEnabled(SparkConf, boolean) - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
-
- isBindCollision(Throwable) - Static method in class org.apache.spark.util.Utils
-
Return whether the exception is caused by an address-port collision when binding.
- isBroadcast() - Method in class org.apache.spark.storage.BlockId
-
- isBroadcast() - Static method in class org.apache.spark.storage.BroadcastBlockId
-
- isBroadcast() - Static method in class org.apache.spark.storage.RDDBlockId
-
- isBroadcast() - Static method in class org.apache.spark.storage.ShuffleBlockId
-
- isBroadcast() - Static method in class org.apache.spark.storage.ShuffleDataBlockId
-
- isBroadcast() - Static method in class org.apache.spark.storage.ShuffleIndexBlockId
-
- isBroadcast() - Static method in class org.apache.spark.storage.StreamBlockId
-
- isBroadcast() - Static method in class org.apache.spark.storage.TaskResultBlockId
-
- isBucket() - Method in class org.apache.spark.sql.catalog.Column
-
- isByteArrayDecimalType(DataType) - Static method in class org.apache.spark.sql.types.DecimalType
-
Returns if dt is a DecimalType that doesn't fit inside a long
- isCached(String) - Method in class org.apache.spark.sql.catalog.Catalog
-
Returns true if the table is currently cached in-memory.
- isCached(String) - Method in class org.apache.spark.sql.internal.CatalogImpl
-
Returns true if the table is currently cached in-memory.
- isCached(String) - Method in class org.apache.spark.sql.SQLContext
-
Returns true if the table is currently cached in-memory.
- isCached() - Method in class org.apache.spark.storage.BlockStatus
-
- isCached() - Method in class org.apache.spark.storage.RDDInfo
-
- isCancelled() - Method in class org.apache.spark.ComplexFutureAction
-
- isCancelled() - Method in interface org.apache.spark.FutureAction
-
Returns whether the action has been cancelled.
- isCancelled() - Method in class org.apache.spark.SimpleFutureAction
-
- isCheckpointed() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- isCheckpointed() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- isCheckpointed() - Static method in class org.apache.spark.api.java.JavaRDD
-
- isCheckpointed() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return whether this RDD has been checkpointed or not
- isCheckpointed() - Static method in class org.apache.spark.api.r.RRDD
-
- isCheckpointed() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- isCheckpointed() - Method in class org.apache.spark.graphx.Graph
-
Return whether this Graph has been checkpointed or not.
- isCheckpointed() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- isCheckpointed() - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- isCheckpointed() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- isCheckpointed() - Static method in class org.apache.spark.graphx.VertexRDD
-
- isCheckpointed() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- isCheckpointed() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- isCheckpointed() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- isCheckpointed() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- isCheckpointed() - Method in class org.apache.spark.rdd.RDD
-
Return whether this RDD is checkpointed and materialized, either reliably or locally.
- isCheckpointed() - Static method in class org.apache.spark.rdd.UnionRDD
-
- isCompatible(BloomFilter) - Method in class org.apache.spark.util.sketch.BloomFilter
-
Determines whether a given bloom filter is compatible with this bloom filter.
- isCompleted() - Method in class org.apache.spark.ComplexFutureAction
-
- isCompleted() - Method in interface org.apache.spark.FutureAction
-
Returns whether the action has already been completed with a value or an exception.
- isCompleted() - Method in class org.apache.spark.SimpleFutureAction
-
- isCompleted() - Method in class org.apache.spark.TaskContext
-
Returns true if the task has completed.
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.clustering.KMeans
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.clustering.LDA
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.evaluation.RegressionEvaluator
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.Binarizer
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.Bucketizer
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.ColumnPruner
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.CountVectorizer
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.DCT
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.ElementwiseProduct
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.HashingTF
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.IDF
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.IDFModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.IndexToString
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.Interaction
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.MaxAbsScaler
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.MinMaxScaler
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.NGram
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.Normalizer
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.OneHotEncoder
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.PCA
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.PCAModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.PolynomialExpansion
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.RegexTokenizer
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.RFormula
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.SQLTransformer
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.StandardScaler
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.StandardScalerModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.StopWordsRemover
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.StringIndexer
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.StringIndexerModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.Tokenizer
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.VectorAssembler
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.VectorAttributeRewriter
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.VectorIndexer
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.VectorSlicer
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- isDefined(Param<?>) - Method in interface org.apache.spark.ml.param.Params
-
Checks whether a param is explicitly set or has a default value.
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.Pipeline
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.PipelineModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.recommendation.ALS
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.recommendation.ALSModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.regression.IsotonicRegression
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
-
- isDefinedAt(A) - Static method in class org.apache.spark.sql.types.StructType
-
- isDistributed() - Method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- isDistributed() - Method in class org.apache.spark.ml.clustering.LDAModel
-
- isDistributed() - Method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- isDriver() - Method in class org.apache.spark.storage.BlockManagerId
-
- isDynamicAllocationEnabled(SparkConf) - Static method in class org.apache.spark.util.Utils
-
Return whether dynamic allocation is enabled in the given conf.
- isEmpty() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- isEmpty() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- isEmpty() - Static method in class org.apache.spark.api.java.JavaRDD
-
- isEmpty() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
- isEmpty() - Static method in class org.apache.spark.api.r.RRDD
-
- isEmpty() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- isEmpty() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- isEmpty() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- isEmpty() - Static method in class org.apache.spark.graphx.VertexRDD
-
- isEmpty() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- isEmpty() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- isEmpty() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- isEmpty() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- isEmpty() - Method in class org.apache.spark.rdd.RDD
-
- isEmpty() - Static method in class org.apache.spark.rdd.UnionRDD
-
- isEmpty() - Static method in class org.apache.spark.sql.types.StructType
-
- isExecutorStartupConf(String) - Static method in class org.apache.spark.SparkConf
-
Return whether the given config should be passed to an executor on start-up.
- isExperiment() - Method in class org.apache.spark.mllib.stat.test.BinarySample
-
- isFailed(Enumeration.Value) - Static method in class org.apache.spark.TaskState
-
- isFatalError(Throwable) - Static method in class org.apache.spark.util.Utils
-
Returns true if the given exception was fatal.
- isFinal() - Method in enum org.apache.spark.launcher.SparkAppHandle.State
-
Whether this state is a final state, meaning the application is not running anymore
once it's reached.
- isFinished(Enumeration.Value) - Static method in class org.apache.spark.TaskState
-
- isImmutable() - Static method in class org.apache.spark.serializer.JavaIterableWrapperSerializer
-
- isin(Object...) - Method in class org.apache.spark.sql.Column
-
A boolean expression that is evaluated to true if the value of this expression is contained
by the evaluated values of the arguments.
- isin(Seq<Object>) - Method in class org.apache.spark.sql.Column
-
A boolean expression that is evaluated to true if the value of this expression is contained
by the evaluated values of the arguments.
- isInDirectory(File, File) - Static method in class org.apache.spark.util.Utils
-
Return whether the specified file is a parent directory of the child file.
- isInitialValueFinal() - Method in class org.apache.spark.partial.PartialResult
-
- isInterrupted() - Method in class org.apache.spark.TaskContext
-
Returns true if the task has been killed.
- isLargerBetter() - Method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- isLargerBetter() - Method in class org.apache.spark.ml.evaluation.Evaluator
-
Indicates whether the metric returned by evaluate should be maximized (true, default)
or minimized (false).
- isLargerBetter() - Method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
- isLargerBetter() - Method in class org.apache.spark.ml.evaluation.RegressionEvaluator
-
- isLeaf() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData
-
- isLeaf() - Method in class org.apache.spark.mllib.tree.model.Node
-
- isLeftChild(int) - Static method in class org.apache.spark.mllib.tree.model.Node
-
Returns true if this is a left child.
- isLocal() - Method in class org.apache.spark.api.java.JavaSparkContext
-
- isLocal() - Method in class org.apache.spark.SparkContext
-
- isLocal() - Method in class org.apache.spark.sql.Dataset
-
Returns true if the collect and take methods can be run locally
(without any Spark executors).
- isLocalMaster(SparkConf) - Static method in class org.apache.spark.util.Utils
-
- isMac() - Static method in class org.apache.spark.util.Utils
-
Whether the underlying operating system is Mac OS X.
- isMulticlassClassification() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- isMulticlassWithCategoricalFeatures() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- isMultipleOf(Duration) - Method in class org.apache.spark.streaming.Duration
-
- isMultipleOf(Duration) - Method in class org.apache.spark.streaming.Time
-
- isNaN() - Method in class org.apache.spark.sql.Column
-
True if the current expression is NaN.
- isnan(Column) - Static method in class org.apache.spark.sql.functions
-
Return true iff the column is NaN.
- isNominal() - Method in class org.apache.spark.ml.attribute.Attribute
-
- isNominal() - Method in class org.apache.spark.ml.attribute.BinaryAttribute
-
- isNominal() - Method in class org.apache.spark.ml.attribute.NominalAttribute
-
- isNominal() - Method in class org.apache.spark.ml.attribute.NumericAttribute
-
- isNominal() - Static method in class org.apache.spark.ml.attribute.UnresolvedAttribute
-
- isNotNull() - Method in class org.apache.spark.sql.Column
-
True if the current expression is NOT null.
- IsNotNull - Class in org.apache.spark.sql.sources
-
A filter that evaluates to true iff the attribute evaluates to a non-null value.
- IsNotNull(String) - Constructor for class org.apache.spark.sql.sources.IsNotNull
-
- isNull() - Method in class org.apache.spark.sql.Column
-
True if the current expression is null.
- isnull(Column) - Static method in class org.apache.spark.sql.functions
-
Return true iff the column is null.
- IsNull - Class in org.apache.spark.sql.sources
-
A filter that evaluates to true iff the attribute evaluates to null.
- IsNull(String) - Constructor for class org.apache.spark.sql.sources.IsNull
-
- isNullAt(int) - Method in interface org.apache.spark.sql.Row
-
Checks whether the value at position i is null.
- isNumeric() - Method in class org.apache.spark.ml.attribute.Attribute
-
- isNumeric() - Method in class org.apache.spark.ml.attribute.BinaryAttribute
-
- isNumeric() - Method in class org.apache.spark.ml.attribute.NominalAttribute
-
- isNumeric() - Method in class org.apache.spark.ml.attribute.NumericAttribute
-
- isNumeric() - Static method in class org.apache.spark.ml.attribute.UnresolvedAttribute
-
- isOrdinal() - Method in class org.apache.spark.ml.attribute.NominalAttribute
-
- isotonic() - Static method in class org.apache.spark.ml.regression.IsotonicRegression
-
- isotonic() - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- isotonic() - Method in class org.apache.spark.mllib.regression.IsotonicRegressionModel
-
- IsotonicRegression - Class in org.apache.spark.ml.regression
-
Isotonic regression.
- IsotonicRegression(String) - Constructor for class org.apache.spark.ml.regression.IsotonicRegression
-
- IsotonicRegression() - Constructor for class org.apache.spark.ml.regression.IsotonicRegression
-
- IsotonicRegression - Class in org.apache.spark.mllib.regression
-
Isotonic regression.
- IsotonicRegression() - Constructor for class org.apache.spark.mllib.regression.IsotonicRegression
-
Constructs IsotonicRegression instance with default parameter isotonic = true.
- IsotonicRegressionModel - Class in org.apache.spark.ml.regression
-
Model fitted by IsotonicRegression.
- IsotonicRegressionModel - Class in org.apache.spark.mllib.regression
-
Regression model for isotonic regression.
- IsotonicRegressionModel(double[], double[], boolean) - Constructor for class org.apache.spark.mllib.regression.IsotonicRegressionModel
-
- IsotonicRegressionModel(Iterable<Object>, Iterable<Object>, Boolean) - Constructor for class org.apache.spark.mllib.regression.IsotonicRegressionModel
-
A Java-friendly constructor that takes two Iterable parameters and one Boolean parameter.
- isPartition() - Method in class org.apache.spark.sql.catalog.Column
-
- isPresent() - Method in class org.apache.spark.api.java.Optional
-
- isRDD() - Method in class org.apache.spark.storage.BlockId
-
- isRDD() - Static method in class org.apache.spark.storage.BroadcastBlockId
-
- isRDD() - Static method in class org.apache.spark.storage.RDDBlockId
-
- isRDD() - Static method in class org.apache.spark.storage.ShuffleBlockId
-
- isRDD() - Static method in class org.apache.spark.storage.ShuffleDataBlockId
-
- isRDD() - Static method in class org.apache.spark.storage.ShuffleIndexBlockId
-
- isRDD() - Static method in class org.apache.spark.storage.StreamBlockId
-
- isRDD() - Static method in class org.apache.spark.storage.TaskResultBlockId
-
- isRegistered() - Method in class org.apache.spark.util.AccumulatorV2
-
Returns true if this accumulator has been registered.
- isRInstalled() - Static method in class org.apache.spark.api.r.RUtils
-
Check if R is installed before running tests that use R commands.
- isRunningLocally() - Method in class org.apache.spark.TaskContext
-
Deprecated.
Local execution was removed, so this always returns false. Since 2.0.0.
- isSet(Param<?>) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.clustering.KMeans
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.clustering.LDA
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.evaluation.RegressionEvaluator
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.Binarizer
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.Bucketizer
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.ColumnPruner
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.CountVectorizer
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.DCT
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.ElementwiseProduct
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.HashingTF
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.IDF
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.IDFModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.IndexToString
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.Interaction
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.MaxAbsScaler
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.MinMaxScaler
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.NGram
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.Normalizer
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.OneHotEncoder
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.PCA
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.PCAModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.PolynomialExpansion
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.RegexTokenizer
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.RFormula
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.SQLTransformer
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.StandardScaler
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.StandardScalerModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.StopWordsRemover
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.StringIndexer
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.StringIndexerModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.Tokenizer
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.VectorAssembler
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.VectorAttributeRewriter
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.VectorIndexer
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.VectorSlicer
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- isSet(Param<?>) - Method in interface org.apache.spark.ml.param.Params
-
Checks whether a param is explicitly set.
- isSet(Param<?>) - Static method in class org.apache.spark.ml.Pipeline
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.PipelineModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.recommendation.ALS
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.recommendation.ALSModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.regression.IsotonicRegression
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
-
- isShuffle() - Method in class org.apache.spark.storage.BlockId
-
- isShuffle() - Static method in class org.apache.spark.storage.BroadcastBlockId
-
- isShuffle() - Static method in class org.apache.spark.storage.RDDBlockId
-
- isShuffle() - Static method in class org.apache.spark.storage.ShuffleBlockId
-
- isShuffle() - Static method in class org.apache.spark.storage.ShuffleDataBlockId
-
- isShuffle() - Static method in class org.apache.spark.storage.ShuffleIndexBlockId
-
- isShuffle() - Static method in class org.apache.spark.storage.StreamBlockId
-
- isShuffle() - Static method in class org.apache.spark.storage.TaskResultBlockId
-
- isSparkPortConf(String) - Static method in class org.apache.spark.SparkConf
-
Return true if the given config matches either spark.*.port or spark.port.*.
- isSparkRInstalled() - Static method in class org.apache.spark.api.r.RUtils
-
Check if SparkR is installed before running tests that use SparkR.
- isSplitable(SparkSession, Map<String, String>, Path) - Method in class org.apache.spark.sql.hive.orc.OrcFileFormat
-
- isStarted() - Method in class org.apache.spark.streaming.receiver.Receiver
-
Check if the receiver has started or not.
- isStopped() - Method in class org.apache.spark.SparkContext
-
- isStopped() - Method in class org.apache.spark.streaming.receiver.Receiver
-
Check if receiver has been marked for stopping.
- isStreaming() - Method in class org.apache.spark.sql.Dataset
-
Returns true if this Dataset contains one or more sources that continuously
return data as it arrives.
- isStreaming() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- isSymlink(File) - Static method in class org.apache.spark.util.Utils
-
Check to see if file is a symbolic link.
- isTemporary() - Method in class org.apache.spark.sql.catalog.Function
-
- isTemporary() - Method in class org.apache.spark.sql.catalog.Table
-
- isTesting() - Static method in class org.apache.spark.util.Utils
-
Indicates whether Spark is currently running unit tests.
- isTimingOut() - Method in class org.apache.spark.streaming.State
-
Whether the state is timing out and going to be removed by the system after the current batch.
- isTransposed() - Method in class org.apache.spark.ml.linalg.DenseMatrix
-
- isTransposed() - Method in interface org.apache.spark.ml.linalg.Matrix
-
Flag that keeps track whether the matrix is transposed or not.
- isTransposed() - Method in class org.apache.spark.ml.linalg.SparseMatrix
-
- isTransposed() - Method in class org.apache.spark.mllib.linalg.DenseMatrix
-
- isTransposed() - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Flag that keeps track whether the matrix is transposed or not.
- isTransposed() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
-
- isTraversableAgain() - Static method in class org.apache.spark.sql.types.StructType
-
- isValid() - Static method in class org.apache.spark.ml.param.DoubleParam
-
- isValid() - Static method in class org.apache.spark.ml.param.FloatParam
-
- isValid() - Method in class org.apache.spark.ml.param.Param
-
- isValid() - Method in class org.apache.spark.storage.StorageLevel
-
- isWindows() - Static method in class org.apache.spark.util.Utils
-
Whether the underlying operating system is Windows.
- isZero() - Method in class org.apache.spark.sql.types.Decimal
-
- isZero() - Method in class org.apache.spark.streaming.Duration
-
- isZero() - Method in class org.apache.spark.util.AccumulatorV2
-
Returns if this accumulator is zero value or not.
- isZero() - Method in class org.apache.spark.util.CollectionAccumulator
-
- isZero() - Method in class org.apache.spark.util.DoubleAccumulator
-
- isZero() - Method in class org.apache.spark.util.LegacyAccumulatorWrapper
-
- isZero() - Method in class org.apache.spark.util.LongAccumulator
-
Adds v to the accumulator, i.e.
- item() - Method in class org.apache.spark.ml.recommendation.ALS.Rating
-
- itemCol() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- itemCol() - Static method in class org.apache.spark.ml.recommendation.ALSModel
-
- itemFactors() - Method in class org.apache.spark.ml.recommendation.ALSModel
-
- items() - Method in class org.apache.spark.mllib.fpm.FPGrowth.FreqItemset
-
- iterator(Partition, TaskContext) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- iterator(Partition, TaskContext) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- iterator(Partition, TaskContext) - Static method in class org.apache.spark.api.java.JavaRDD
-
- iterator(Partition, TaskContext) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Internal method to this RDD; will read from cache if applicable, or otherwise compute it.
- iterator(Partition, TaskContext) - Static method in class org.apache.spark.api.r.RRDD
-
- iterator(Partition, TaskContext) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- iterator(Partition, TaskContext) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- iterator(Partition, TaskContext) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- iterator(Partition, TaskContext) - Static method in class org.apache.spark.graphx.VertexRDD
-
- iterator(Partition, TaskContext) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- iterator(Partition, TaskContext) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- iterator(Partition, TaskContext) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- iterator(Partition, TaskContext) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- iterator(Partition, TaskContext) - Method in class org.apache.spark.rdd.RDD
-
Internal method to this RDD; will read from cache if applicable, or otherwise compute it.
- iterator(Partition, TaskContext) - Static method in class org.apache.spark.rdd.UnionRDD
-
- iterator() - Method in class org.apache.spark.sql.types.StructType
-
- L1Updater - Class in org.apache.spark.mllib.optimization
-
:: DeveloperApi ::
Updater for L1 regularized problems.
- L1Updater() - Constructor for class org.apache.spark.mllib.optimization.L1Updater
-
- label() - Method in class org.apache.spark.ml.feature.LabeledPoint
-
- label() - Method in class org.apache.spark.mllib.regression.LabeledPoint
-
- labelCol() - Method in class org.apache.spark.ml.classification.BinaryLogisticRegressionSummary
-
- labelCol() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- labelCol() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- labelCol() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- labelCol() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- labelCol() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- labelCol() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- labelCol() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
-
Field in "predictions" which gives the true label of each instance (if available).
- labelCol() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- labelCol() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- labelCol() - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- labelCol() - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- labelCol() - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- labelCol() - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- labelCol() - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- labelCol() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- labelCol() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- labelCol() - Static method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- labelCol() - Static method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
- labelCol() - Static method in class org.apache.spark.ml.evaluation.RegressionEvaluator
-
- labelCol() - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- labelCol() - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- labelCol() - Static method in class org.apache.spark.ml.feature.RFormula
-
- labelCol() - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- labelCol() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- labelCol() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- labelCol() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- labelCol() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- labelCol() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- labelCol() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- labelCol() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- labelCol() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- labelCol() - Static method in class org.apache.spark.ml.regression.IsotonicRegression
-
- labelCol() - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- labelCol() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- labelCol() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- labelCol() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
-
- labelCol() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- labelCol() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- LabelConverter - Class in org.apache.spark.ml.classification
-
Label to vector converter.
- LabelConverter() - Constructor for class org.apache.spark.ml.classification.LabelConverter
-
- LabeledPoint - Class in org.apache.spark.ml.feature
-
:: Experimental ::
- LabeledPoint(double, Vector) - Constructor for class org.apache.spark.ml.feature.LabeledPoint
-
- LabeledPoint - Class in org.apache.spark.mllib.regression
-
Class that represents the features and labels of a data point.
- LabeledPoint(double, Vector) - Constructor for class org.apache.spark.mllib.regression.LabeledPoint
-
- LabelPropagation - Class in org.apache.spark.graphx.lib
-
Label Propagation algorithm.
- LabelPropagation() - Constructor for class org.apache.spark.graphx.lib.LabelPropagation
-
- labels() - Method in class org.apache.spark.ml.feature.IndexToString
-
Optional param for array of labels specifying index-string mapping.
- labels() - Method in class org.apache.spark.ml.feature.StringIndexerModel
-
- labels() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel
-
- labels() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0$.Data
-
- labels() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$.Data
-
- labels() - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
-
Returns the sequence of labels in ascending order
- labels() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
-
Returns the sequence of labels in ascending order
- lag(Column, int) - Static method in class org.apache.spark.sql.functions
-
Window function: returns the value that is offset rows before the current row, and
null if there is less than offset rows before the current row.
- lag(String, int) - Static method in class org.apache.spark.sql.functions
-
Window function: returns the value that is offset rows before the current row, and
null if there is less than offset rows before the current row.
- lag(String, int, Object) - Static method in class org.apache.spark.sql.functions
-
Window function: returns the value that is offset rows before the current row, and
defaultValue if there is less than offset rows before the current row.
- lag(Column, int, Object) - Static method in class org.apache.spark.sql.functions
-
Window function: returns the value that is offset rows before the current row, and
defaultValue if there is less than offset rows before the current row.
- LassoModel - Class in org.apache.spark.mllib.regression
-
Regression model trained using Lasso.
- LassoModel(Vector, double) - Constructor for class org.apache.spark.mllib.regression.LassoModel
-
- LassoWithSGD - Class in org.apache.spark.mllib.regression
-
Train a regression model with L1-regularization using Stochastic Gradient Descent.
- LassoWithSGD() - Constructor for class org.apache.spark.mllib.regression.LassoWithSGD
-
Deprecated.
Use ml.regression.LinearRegression with elasticNetParam = 1.0. Note the default regParam is 0.01 for LassoWithSGD, but is 0.0 for LinearRegression. Since 2.0.0.
- last(Column, boolean) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the last value in a group.
- last(String, boolean) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the last value of the column in a group.
- last(Column) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the last value in a group.
- last(String) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the last value of the column in a group.
- last() - Static method in class org.apache.spark.sql.types.StructType
-
- last_day(Column) - Static method in class org.apache.spark.sql.functions
-
Given a date column, returns the last day of the month which the given date belongs to.
- lastDir() - Method in class org.apache.spark.mllib.optimization.NNLS.Workspace
-
- lastError() - Method in class org.apache.spark.streaming.scheduler.ReceiverInfo
-
- lastErrorMessage() - Method in class org.apache.spark.streaming.scheduler.ReceiverInfo
-
- lastErrorTime() - Method in class org.apache.spark.streaming.scheduler.ReceiverInfo
-
- lastIndexOf(B) - Static method in class org.apache.spark.sql.types.StructType
-
- lastIndexOf(B, int) - Static method in class org.apache.spark.sql.types.StructType
-
- lastIndexOfSlice(GenSeq<B>) - Static method in class org.apache.spark.sql.types.StructType
-
- lastIndexOfSlice(GenSeq<B>, int) - Static method in class org.apache.spark.sql.types.StructType
-
- lastIndexWhere(Function1<A, Object>) - Static method in class org.apache.spark.sql.types.StructType
-
- lastIndexWhere(Function1<A, Object>, int) - Static method in class org.apache.spark.sql.types.StructType
-
- lastOption() - Static method in class org.apache.spark.sql.types.StructType
-
- lastUpdated() - Method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
-
- latestModel() - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
-
Return the latest model.
- latestModel() - Method in class org.apache.spark.mllib.regression.StreamingLinearAlgorithm
-
Return the latest model.
- launch() - Method in class org.apache.spark.launcher.SparkLauncher
-
Launches a sub-process that will start the configured Spark application.
- LAUNCHING() - Static method in class org.apache.spark.TaskState
-
- launchTime() - Method in class org.apache.spark.scheduler.TaskInfo
-
- launchTime() - Method in class org.apache.spark.status.api.v1.TaskData
-
- layers() - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- layers() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- LBFGS - Class in org.apache.spark.mllib.optimization
-
:: DeveloperApi ::
Class used to solve an optimization problem using Limited-memory BFGS.
- LBFGS(Gradient, Updater) - Constructor for class org.apache.spark.mllib.optimization.LBFGS
-
- LDA - Class in org.apache.spark.ml.clustering
-
:: Experimental ::
- LDA(String) - Constructor for class org.apache.spark.ml.clustering.LDA
-
- LDA() - Constructor for class org.apache.spark.ml.clustering.LDA
-
- LDA - Class in org.apache.spark.mllib.clustering
-
Latent Dirichlet Allocation (LDA), a topic model designed for text documents.
- LDA() - Constructor for class org.apache.spark.mllib.clustering.LDA
-
Constructs a LDA instance with default parameters.
- LDAModel - Class in org.apache.spark.ml.clustering
-
:: Experimental ::
Model fitted by
LDA.
- LDAModel - Class in org.apache.spark.mllib.clustering
-
Latent Dirichlet Allocation (LDA) model.
- LDAOptimizer - Interface in org.apache.spark.mllib.clustering
-
:: DeveloperApi ::
- LDAUtils - Class in org.apache.spark.mllib.clustering
-
Utility methods for LDA.
- LDAUtils() - Constructor for class org.apache.spark.mllib.clustering.LDAUtils
-
- lead(String, int) - Static method in class org.apache.spark.sql.functions
-
Window function: returns the value that is offset rows after the current row, and
null if there is less than offset rows after the current row.
- lead(Column, int) - Static method in class org.apache.spark.sql.functions
-
Window function: returns the value that is offset rows after the current row, and
null if there is less than offset rows after the current row.
- lead(String, int, Object) - Static method in class org.apache.spark.sql.functions
-
Window function: returns the value that is offset rows after the current row, and
defaultValue if there is less than offset rows after the current row.
- lead(Column, int, Object) - Static method in class org.apache.spark.sql.functions
-
Window function: returns the value that is offset rows after the current row, and
defaultValue if there is less than offset rows after the current row.
- LeafNode - Class in org.apache.spark.ml.tree
-
Decision tree leaf node.
- learningDecay() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- learningDecay() - Static method in class org.apache.spark.ml.clustering.LDA
-
- learningDecay() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- learningOffset() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- learningOffset() - Static method in class org.apache.spark.ml.clustering.LDA
-
- learningOffset() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- learningRate() - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- least(Column...) - Static method in class org.apache.spark.sql.functions
-
Returns the least value of the list of values, skipping null values.
- least(String, String...) - Static method in class org.apache.spark.sql.functions
-
Returns the least value of the list of column names, skipping null values.
- least(Seq<Column>) - Static method in class org.apache.spark.sql.functions
-
Returns the least value of the list of values, skipping null values.
- least(String, Seq<String>) - Static method in class org.apache.spark.sql.functions
-
Returns the least value of the list of column names, skipping null values.
- LeastSquaresAggregator - Class in org.apache.spark.ml.regression
-
LeastSquaresAggregator computes the gradient and loss for a Least-squared loss function,
as used in linear regression for samples in sparse or dense vector in an online fashion.
- LeastSquaresAggregator(Vector, double, double, boolean, double[], double[]) - Constructor for class org.apache.spark.ml.regression.LeastSquaresAggregator
-
- LeastSquaresCostFun - Class in org.apache.spark.ml.regression
-
LeastSquaresCostFun implements Breeze's DiffFunction[T] for Least Squares cost.
- LeastSquaresCostFun(RDD<org.apache.spark.ml.feature.Instance>, double, double, boolean, boolean, double[], double[], double) - Constructor for class org.apache.spark.ml.regression.LeastSquaresCostFun
-
- LeastSquaresGradient - Class in org.apache.spark.mllib.optimization
-
:: DeveloperApi ::
Compute gradient and loss for a Least-squared loss function, as used in linear regression.
- LeastSquaresGradient() - Constructor for class org.apache.spark.mllib.optimization.LeastSquaresGradient
-
- left() - Method in class org.apache.spark.sql.sources.And
-
- left() - Method in class org.apache.spark.sql.sources.Or
-
- leftCategories() - Method in class org.apache.spark.ml.tree.CategoricalSplit
-
Get sorted categories which split to the left
- leftCategoriesOrThreshold() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.SplitData
-
- leftChild() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData
-
- leftChild() - Method in class org.apache.spark.ml.tree.InternalNode
-
- leftChildIndex(int) - Static method in class org.apache.spark.mllib.tree.model.Node
-
Return the index of the left child of this node.
- leftImpurity() - Method in class org.apache.spark.mllib.tree.model.InformationGainStats
-
- leftJoin(RDD<Tuple2<Object, VD2>>, Function3<Object, VD, Option<VD2>, VD3>, ClassTag<VD2>, ClassTag<VD3>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- leftJoin(RDD<Tuple2<Object, VD2>>, Function3<Object, VD, Option<VD2>, VD3>, ClassTag<VD2>, ClassTag<VD3>) - Method in class org.apache.spark.graphx.VertexRDD
-
Left joins this VertexRDD with an RDD containing vertex attribute pairs.
- leftNode() - Method in class org.apache.spark.mllib.tree.model.Node
-
- leftNodeId() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData
-
- leftOuterJoin(JavaPairRDD<K, W>, Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Perform a left outer join of this and other.
- leftOuterJoin(JavaPairRDD<K, W>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Perform a left outer join of this and other.
- leftOuterJoin(JavaPairRDD<K, W>, int) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Perform a left outer join of this and other.
- leftOuterJoin(RDD<Tuple2<K, W>>, Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Perform a left outer join of this and other.
- leftOuterJoin(RDD<Tuple2<K, W>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Perform a left outer join of this and other.
- leftOuterJoin(RDD<Tuple2<K, W>>, int) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Perform a left outer join of this and other.
- leftOuterJoin(JavaPairDStream<K, W>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying 'left outer join' between RDDs of this DStream and
other DStream.
- leftOuterJoin(JavaPairDStream<K, W>, int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying 'left outer join' between RDDs of this DStream and
other DStream.
- leftOuterJoin(JavaPairDStream<K, W>, Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying 'left outer join' between RDDs of this DStream and
other DStream.
- leftOuterJoin(JavaPairDStream<K, W>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- leftOuterJoin(JavaPairDStream<K, W>, int) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- leftOuterJoin(JavaPairDStream<K, W>, Partitioner) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- leftOuterJoin(JavaPairDStream<K, W>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- leftOuterJoin(JavaPairDStream<K, W>, int) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- leftOuterJoin(JavaPairDStream<K, W>, Partitioner) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- leftOuterJoin(DStream<Tuple2<K, W>>, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying 'left outer join' between RDDs of this DStream and
other DStream.
- leftOuterJoin(DStream<Tuple2<K, W>>, int, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying 'left outer join' between RDDs of this DStream and
other DStream.
- leftOuterJoin(DStream<Tuple2<K, W>>, Partitioner, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying 'left outer join' between RDDs of this DStream and
other DStream.
- leftPredict() - Method in class org.apache.spark.mllib.tree.model.InformationGainStats
-
- leftZipJoin(VertexRDD<VD2>, Function3<Object, VD, Option<VD2>, VD3>, ClassTag<VD2>, ClassTag<VD3>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- leftZipJoin(VertexRDD<VD2>, Function3<Object, VD, Option<VD2>, VD3>, ClassTag<VD2>, ClassTag<VD3>) - Method in class org.apache.spark.graphx.VertexRDD
-
Left joins this RDD with another VertexRDD with the same index.
- LegacyAccumulatorWrapper<R,T> - Class in org.apache.spark.util
-
- LegacyAccumulatorWrapper(R, AccumulableParam<R, T>) - Constructor for class org.apache.spark.util.LegacyAccumulatorWrapper
-
- length() - Method in class org.apache.spark.scheduler.SplitInfo
-
- length(Column) - Static method in class org.apache.spark.sql.functions
-
Computes the length of a given string or binary column.
- length() - Method in interface org.apache.spark.sql.Row
-
Number of elements in the Row.
- length() - Method in class org.apache.spark.sql.types.StructType
-
- lengthCompare(int) - Static method in class org.apache.spark.sql.types.StructType
-
- leq(Object) - Method in class org.apache.spark.sql.Column
-
Less than or equal to.
- less(Duration) - Method in class org.apache.spark.streaming.Duration
-
- less(Time) - Method in class org.apache.spark.streaming.Time
-
- lessEq(Duration) - Method in class org.apache.spark.streaming.Duration
-
- lessEq(Time) - Method in class org.apache.spark.streaming.Time
-
- LessThan - Class in org.apache.spark.sql.sources
-
A filter that evaluates to true iff the attribute evaluates to a value
less than value.
- LessThan(String, Object) - Constructor for class org.apache.spark.sql.sources.LessThan
-
- LessThanOrEqual - Class in org.apache.spark.sql.sources
-
A filter that evaluates to true iff the attribute evaluates to a value
less than or equal to value.
- LessThanOrEqual(String, Object) - Constructor for class org.apache.spark.sql.sources.LessThanOrEqual
-
- levenshtein(Column, Column) - Static method in class org.apache.spark.sql.functions
-
Computes the Levenshtein distance of the two given string columns.
- libraryPathEnvName() - Static method in class org.apache.spark.util.Utils
-
Return the current system LD_LIBRARY_PATH name
- libraryPathEnvPrefix(Seq<String>) - Static method in class org.apache.spark.util.Utils
-
Return the prefix of a command that appends the given library paths to the
system-specific library path environment variable.
- LibSVMDataSource - Class in org.apache.spark.ml.source.libsvm
-
libsvm package implements Spark SQL data source API for loading LIBSVM data as DataFrame.
- lift() - Static method in class org.apache.spark.sql.types.StructType
-
- like(String) - Method in class org.apache.spark.sql.Column
-
SQL like expression.
- limit(int) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset by taking the first n rows.
- line() - Method in exception org.apache.spark.sql.AnalysisException
-
- LinearDataGenerator - Class in org.apache.spark.mllib.util
-
:: DeveloperApi ::
Generate sample data used for Linear Data.
- LinearDataGenerator() - Constructor for class org.apache.spark.mllib.util.LinearDataGenerator
-
- LinearRegression - Class in org.apache.spark.ml.regression
-
Linear regression.
- LinearRegression(String) - Constructor for class org.apache.spark.ml.regression.LinearRegression
-
- LinearRegression() - Constructor for class org.apache.spark.ml.regression.LinearRegression
-
- LinearRegressionModel - Class in org.apache.spark.ml.regression
-
- LinearRegressionModel - Class in org.apache.spark.mllib.regression
-
Regression model trained using LinearRegression.
- LinearRegressionModel(Vector, double) - Constructor for class org.apache.spark.mllib.regression.LinearRegressionModel
-
- LinearRegressionSummary - Class in org.apache.spark.ml.regression
-
:: Experimental ::
Linear regression results evaluated on a dataset.
- LinearRegressionTrainingSummary - Class in org.apache.spark.ml.regression
-
:: Experimental ::
Linear regression training results.
- LinearRegressionWithSGD - Class in org.apache.spark.mllib.regression
-
Train a linear regression model with no regularization using Stochastic Gradient Descent.
- LinearRegressionWithSGD() - Constructor for class org.apache.spark.mllib.regression.LinearRegressionWithSGD
-
Deprecated.
Use ml.regression.LinearRegression or LBFGS. Since 2.0.0.
- link(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.CLogLog$
-
- link(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Identity$
-
- link(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Inverse$
-
- link() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- link(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Log$
-
- link(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Logit$
-
- link(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Probit$
-
- link(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Sqrt$
-
- link() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- linkPredictionCol() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- linkPredictionCol() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- listColumns(String) - Method in class org.apache.spark.sql.catalog.Catalog
-
Returns a list of columns for the given table in the current database or
the given temporary table.
- listColumns(String, String) - Method in class org.apache.spark.sql.catalog.Catalog
-
Returns a list of columns for the given table in the specified database.
- listColumns(String) - Method in class org.apache.spark.sql.internal.CatalogImpl
-
Returns a list of columns for the given table in the current database.
- listColumns(String, String) - Method in class org.apache.spark.sql.internal.CatalogImpl
-
Returns a list of columns for the given table in the specified database.
- listDatabases() - Method in class org.apache.spark.sql.catalog.Catalog
-
Returns a list of databases available across all sessions.
- listDatabases() - Method in class org.apache.spark.sql.internal.CatalogImpl
-
Returns a list of databases available across all sessions.
- listenerManager() - Method in class org.apache.spark.sql.SparkSession
-
- listenerManager() - Method in class org.apache.spark.sql.SQLContext
-
- listFiles() - Method in class org.apache.spark.SparkContext
-
Returns a list of file paths that are added to resources.
- listFunctions() - Method in class org.apache.spark.sql.catalog.Catalog
-
Returns a list of functions registered in the current database.
- listFunctions(String) - Method in class org.apache.spark.sql.catalog.Catalog
-
Returns a list of functions registered in the specified database.
- listFunctions() - Method in class org.apache.spark.sql.internal.CatalogImpl
-
Returns a list of functions registered in the current database.
- listFunctions(String) - Method in class org.apache.spark.sql.internal.CatalogImpl
-
Returns a list of functions registered in the specified database.
- listingTable(Seq<String>, Function1<T, Seq<Node>>, Iterable<T>, boolean, Option<String>, Seq<String>, boolean, boolean) - Static method in class org.apache.spark.ui.UIUtils
-
Returns an HTML table constructed by generating a row for each object in a sequence.
- listJars() - Method in class org.apache.spark.SparkContext
-
Returns a list of jar files that are added to resources.
- listOrcFiles(String, Configuration) - Static method in class org.apache.spark.sql.hive.orc.OrcFileOperator
-
- listTables() - Method in class org.apache.spark.sql.catalog.Catalog
-
Returns a list of tables in the current database.
- listTables(String) - Method in class org.apache.spark.sql.catalog.Catalog
-
Returns a list of tables in the specified database.
- listTables() - Method in class org.apache.spark.sql.internal.CatalogImpl
-
Returns a list of tables in the current database.
- listTables(String) - Method in class org.apache.spark.sql.internal.CatalogImpl
-
Returns a list of tables in the specified database.
- lit(Object) - Static method in class org.apache.spark.sql.functions
-
Creates a
Column of literal value.
- literal(String) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- load(String) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- load(String) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- load(String) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- load(String) - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- load(String) - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- load(String) - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- load(String) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- load(String) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- load(String) - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- load(String) - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- load(String) - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- load(String) - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- load(String) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- load(String) - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- load(String) - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- load(String) - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- load(String) - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- load(String) - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- load(String) - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- load(String) - Static method in class org.apache.spark.ml.clustering.KMeans
-
- load(String) - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- load(String) - Static method in class org.apache.spark.ml.clustering.LDA
-
- load(String) - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- load(String) - Static method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- load(String) - Static method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
- load(String) - Static method in class org.apache.spark.ml.evaluation.RegressionEvaluator
-
- load(String) - Static method in class org.apache.spark.ml.feature.Binarizer
-
- load(String) - Static method in class org.apache.spark.ml.feature.Bucketizer
-
- load(String) - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- load(String) - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- load(String) - Static method in class org.apache.spark.ml.feature.ColumnPruner
-
- load(String) - Static method in class org.apache.spark.ml.feature.CountVectorizer
-
- load(String) - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- load(String) - Static method in class org.apache.spark.ml.feature.DCT
-
- load(String) - Static method in class org.apache.spark.ml.feature.ElementwiseProduct
-
- load(String) - Static method in class org.apache.spark.ml.feature.HashingTF
-
- load(String) - Static method in class org.apache.spark.ml.feature.IDF
-
- load(String) - Static method in class org.apache.spark.ml.feature.IDFModel
-
- load(String) - Static method in class org.apache.spark.ml.feature.IndexToString
-
- load(String) - Static method in class org.apache.spark.ml.feature.Interaction
-
- load(String) - Static method in class org.apache.spark.ml.feature.MaxAbsScaler
-
- load(String) - Static method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- load(String) - Static method in class org.apache.spark.ml.feature.MinMaxScaler
-
- load(String) - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- load(String) - Static method in class org.apache.spark.ml.feature.NGram
-
- load(String) - Static method in class org.apache.spark.ml.feature.Normalizer
-
- load(String) - Static method in class org.apache.spark.ml.feature.OneHotEncoder
-
- load(String) - Static method in class org.apache.spark.ml.feature.PCA
-
- load(String) - Static method in class org.apache.spark.ml.feature.PCAModel
-
- load(String) - Static method in class org.apache.spark.ml.feature.PolynomialExpansion
-
- load(String) - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- load(String) - Static method in class org.apache.spark.ml.feature.RegexTokenizer
-
- load(String) - Static method in class org.apache.spark.ml.feature.RFormula
-
- load(String) - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- load(String) - Static method in class org.apache.spark.ml.feature.SQLTransformer
-
- load(String) - Static method in class org.apache.spark.ml.feature.StandardScaler
-
- load(String) - Static method in class org.apache.spark.ml.feature.StandardScalerModel
-
- load(String) - Static method in class org.apache.spark.ml.feature.StopWordsRemover
-
- load(String) - Static method in class org.apache.spark.ml.feature.StringIndexer
-
- load(String) - Static method in class org.apache.spark.ml.feature.StringIndexerModel
-
- load(String) - Static method in class org.apache.spark.ml.feature.Tokenizer
-
- load(String) - Static method in class org.apache.spark.ml.feature.VectorAssembler
-
- load(String) - Static method in class org.apache.spark.ml.feature.VectorAttributeRewriter
-
- load(String) - Static method in class org.apache.spark.ml.feature.VectorIndexer
-
- load(String) - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- load(String) - Static method in class org.apache.spark.ml.feature.VectorSlicer
-
- load(String) - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- load(String) - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- load(String) - Static method in class org.apache.spark.ml.Pipeline
-
- load(String, SparkContext, String) - Method in class org.apache.spark.ml.Pipeline.SharedReadWrite$
-
- load(String) - Static method in class org.apache.spark.ml.PipelineModel
-
- load(String) - Static method in class org.apache.spark.ml.r.RWrappers
-
- load(String) - Static method in class org.apache.spark.ml.recommendation.ALS
-
- load(String) - Static method in class org.apache.spark.ml.recommendation.ALSModel
-
- load(String) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- load(String) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- load(String) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- load(String) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- load(String) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- load(String) - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- load(String) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- load(String) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- load(String) - Static method in class org.apache.spark.ml.regression.IsotonicRegression
-
- load(String) - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- load(String) - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- load(String) - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- load(String) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- load(String) - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- load(String) - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- load(String) - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- load(String) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- load(String) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
-
- load(String) - Method in interface org.apache.spark.ml.util.MLReadable
-
Reads an ML instance from the input path, a shortcut of read.load(path).
- load(String) - Method in class org.apache.spark.ml.util.MLReader
-
Loads the ML component from the input path.
- load(SparkContext, String) - Static method in class org.apache.spark.mllib.classification.LogisticRegressionModel
-
- load(SparkContext, String) - Static method in class org.apache.spark.mllib.classification.NaiveBayesModel
-
- load(SparkContext, String) - Method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0$
-
- load(SparkContext, String) - Method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$
-
- load(SparkContext, String) - Static method in class org.apache.spark.mllib.classification.SVMModel
-
- load(SparkContext, String) - Static method in class org.apache.spark.mllib.clustering.BisectingKMeansModel
-
- load(SparkContext, String, int) - Method in class org.apache.spark.mllib.clustering.BisectingKMeansModel.SaveLoadV1_0$
-
- load(SparkContext, String) - Static method in class org.apache.spark.mllib.clustering.DistributedLDAModel
-
- load(SparkContext, String) - Static method in class org.apache.spark.mllib.clustering.GaussianMixtureModel
-
- load(SparkContext, String) - Static method in class org.apache.spark.mllib.clustering.KMeansModel
-
- load(SparkContext, String) - Method in class org.apache.spark.mllib.clustering.KMeansModel.SaveLoadV1_0$
-
- load(SparkContext, String) - Static method in class org.apache.spark.mllib.clustering.LocalLDAModel
-
- load(SparkContext, String) - Static method in class org.apache.spark.mllib.clustering.PowerIterationClusteringModel
-
- load(SparkContext, String) - Method in class org.apache.spark.mllib.clustering.PowerIterationClusteringModel.SaveLoadV1_0$
-
- load(SparkContext, String) - Static method in class org.apache.spark.mllib.feature.ChiSqSelectorModel
-
- load(SparkContext, String) - Method in class org.apache.spark.mllib.feature.ChiSqSelectorModel.SaveLoadV1_0$
-
- load(SparkContext, String) - Static method in class org.apache.spark.mllib.feature.Word2VecModel
-
- load(SparkContext, String) - Static method in class org.apache.spark.mllib.fpm.FPGrowthModel
-
- load(SparkContext, String) - Method in class org.apache.spark.mllib.fpm.FPGrowthModel.SaveLoadV1_0$
-
- load(SparkContext, String) - Static method in class org.apache.spark.mllib.fpm.PrefixSpanModel
-
- load(SparkContext, String) - Method in class org.apache.spark.mllib.fpm.PrefixSpanModel.SaveLoadV1_0$
-
- load(SparkContext, String) - Static method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
-
Load a model from the given path.
- load(SparkContext, String) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel.SaveLoadV1_0$
-
- load(SparkContext, String) - Static method in class org.apache.spark.mllib.regression.IsotonicRegressionModel
-
- load(SparkContext, String) - Static method in class org.apache.spark.mllib.regression.LassoModel
-
- load(SparkContext, String) - Static method in class org.apache.spark.mllib.regression.LinearRegressionModel
-
- load(SparkContext, String) - Static method in class org.apache.spark.mllib.regression.RidgeRegressionModel
-
- load(SparkContext, String) - Static method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
-
- load(SparkContext, String, String, int) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$
-
- load(SparkContext, String) - Static method in class org.apache.spark.mllib.tree.model.GradientBoostedTreesModel
-
- load(SparkContext, String) - Static method in class org.apache.spark.mllib.tree.model.RandomForestModel
-
- load(SparkContext, String) - Method in interface org.apache.spark.mllib.util.Loader
-
Load a model from the given path.
- load(String...) - Method in class org.apache.spark.sql.DataFrameReader
-
Loads input in as a DataFrame, for data sources that support multiple paths.
- load() - Method in class org.apache.spark.sql.DataFrameReader
-
Loads input in as a DataFrame, for data sources that don't require a path (e.g.
- load(String) - Method in class org.apache.spark.sql.DataFrameReader
-
Loads input in as a DataFrame, for data sources that require a path (e.g.
- load(Seq<String>) - Method in class org.apache.spark.sql.DataFrameReader
-
Loads input in as a DataFrame, for data sources that support multiple paths.
- load(String) - Method in class org.apache.spark.sql.SQLContext
-
Deprecated.
As of 1.4.0, replaced by read().load(path).
- load(String, String) - Method in class org.apache.spark.sql.SQLContext
-
Deprecated.
As of 1.4.0, replaced by read().format(source).load(path).
- load(String, Map<String, String>) - Method in class org.apache.spark.sql.SQLContext
-
Deprecated.
As of 1.4.0, replaced by read().format(source).options(options).load().
- load(String, Map<String, String>) - Method in class org.apache.spark.sql.SQLContext
-
Deprecated.
As of 1.4.0, replaced by read().format(source).options(options).load().
- load(String, StructType, Map<String, String>) - Method in class org.apache.spark.sql.SQLContext
-
Deprecated.
As of 1.4.0, replaced by
read().format(source).schema(schema).options(options).load().
- load(String, StructType, Map<String, String>) - Method in class org.apache.spark.sql.SQLContext
-
Deprecated.
As of 1.4.0, replaced by
read().format(source).schema(schema).options(options).load().
- load() - Method in class org.apache.spark.sql.streaming.DataStreamReader
-
:: Experimental ::
Loads input data stream in as a DataFrame, for data streams that don't require a path
(e.g.
- load(String) - Method in class org.apache.spark.sql.streaming.DataStreamReader
-
:: Experimental ::
Loads input in as a DataFrame, for data streams that read from some path.
- loadData(SparkContext, String, String) - Method in class org.apache.spark.mllib.classification.impl.GLMClassificationModel.SaveLoadV1_0$
-
Helper method for loading GLM classification model data.
- loadData(SparkContext, String, String, int) - Method in class org.apache.spark.mllib.regression.impl.GLMRegressionModel.SaveLoadV1_0$
-
Helper method for loading GLM regression model data.
- loadDefaultSparkProperties(SparkConf, String) - Static method in class org.apache.spark.util.Utils
-
Load default Spark properties from the given file.
- loadDefaultStopWords(String) - Static method in class org.apache.spark.ml.feature.StopWordsRemover
-
Loads the default stop words for the given language.
- loadDF(SparkSession, String, Map<String, String>) - Static method in class org.apache.spark.sql.api.r.SQLUtils
-
- loadDF(SparkSession, String, StructType, Map<String, String>) - Static method in class org.apache.spark.sql.api.r.SQLUtils
-
- Loader<M extends Saveable> - Interface in org.apache.spark.mllib.util
-
:: DeveloperApi ::
- loadImpl(String, SparkSession, String, String) - Static method in class org.apache.spark.ml.tree.EnsembleModelReadWrite
-
Helper method for loading a tree ensemble from disk.
- loadImpl(Dataset<Row>, Item, ClassTag<Item>) - Method in class org.apache.spark.mllib.fpm.FPGrowthModel.SaveLoadV1_0$
-
- loadImpl(Dataset<Row>, Item, ClassTag<Item>) - Method in class org.apache.spark.mllib.fpm.PrefixSpanModel.SaveLoadV1_0$
-
- loadLabeledPoints(SparkContext, String, int) - Static method in class org.apache.spark.mllib.util.MLUtils
-
Loads labeled points saved using RDD[LabeledPoint].saveAsTextFile.
- loadLabeledPoints(SparkContext, String) - Static method in class org.apache.spark.mllib.util.MLUtils
-
Loads labeled points saved using RDD[LabeledPoint].saveAsTextFile with the default number of
partitions.
- loadLibSVMFile(SparkContext, String, int, int) - Static method in class org.apache.spark.mllib.util.MLUtils
-
Loads labeled data in the LIBSVM format into an RDD[LabeledPoint].
- loadLibSVMFile(SparkContext, String, int) - Static method in class org.apache.spark.mllib.util.MLUtils
-
Loads labeled data in the LIBSVM format into an RDD[LabeledPoint], with the default number of
partitions.
- loadLibSVMFile(SparkContext, String) - Static method in class org.apache.spark.mllib.util.MLUtils
-
Loads binary labeled data in the LIBSVM format into an RDD[LabeledPoint], with number of
features determined automatically and the default number of partitions.
- loadTreeNodes(String, org.apache.spark.ml.util.DefaultParamsReader.Metadata, SparkSession) - Static method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite
-
Load a decision tree from a file.
- loadVectors(SparkContext, String, int) - Static method in class org.apache.spark.mllib.util.MLUtils
-
Loads vectors saved using RDD[Vector].saveAsTextFile.
- loadVectors(SparkContext, String) - Static method in class org.apache.spark.mllib.util.MLUtils
-
Loads vectors saved using RDD[Vector].saveAsTextFile with the default number of partitions.
- LOCAL_BLOCKS_FETCHED() - Method in class org.apache.spark.InternalAccumulator.shuffleRead$
-
- LOCAL_BYTES_READ() - Method in class org.apache.spark.InternalAccumulator.shuffleRead$
-
- LOCAL_CLUSTER_REGEX() - Static method in class org.apache.spark.SparkMasterRegex
-
- LOCAL_N_FAILURES_REGEX() - Static method in class org.apache.spark.SparkMasterRegex
-
- LOCAL_N_REGEX() - Static method in class org.apache.spark.SparkMasterRegex
-
- localBlocksFetched() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetricDistributions
-
- localBlocksFetched() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetrics
-
- localBlocksFetched() - Method in class org.apache.spark.ui.jobs.UIData.ShuffleReadMetricsUIData
-
- localBytesRead() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetrics
-
- localBytesRead() - Method in class org.apache.spark.ui.jobs.UIData.ShuffleReadMetricsUIData
-
- localCheckpoint() - Static method in class org.apache.spark.api.r.RRDD
-
- localCheckpoint() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- localCheckpoint() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- localCheckpoint() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- localCheckpoint() - Static method in class org.apache.spark.graphx.VertexRDD
-
- localCheckpoint() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- localCheckpoint() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- localCheckpoint() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- localCheckpoint() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- localCheckpoint() - Method in class org.apache.spark.rdd.RDD
-
Mark this RDD for local checkpointing using Spark's existing caching layer.
- localCheckpoint() - Static method in class org.apache.spark.rdd.UnionRDD
-
- localHostName() - Static method in class org.apache.spark.util.Utils
-
Get the local machine's hostname.
- localHostNameForURI() - Static method in class org.apache.spark.util.Utils
-
Get the local machine's URI.
- localityAwareTasks() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RequestExecutors
-
- LocalKMeans - Class in org.apache.spark.mllib.clustering
-
An utility object to run K-means locally.
- LocalKMeans() - Constructor for class org.apache.spark.mllib.clustering.LocalKMeans
-
- LocalLDAModel - Class in org.apache.spark.ml.clustering
-
:: Experimental ::
- LocalLDAModel - Class in org.apache.spark.mllib.clustering
-
Local LDA model.
- localSeqToDatasetHolder(Seq<T>, Encoder<T>) - Method in class org.apache.spark.sql.SQLImplicits
-
Creates a
Dataset from a local Seq.
- localSparkRPackagePath() - Static method in class org.apache.spark.api.r.RUtils
-
Get the SparkR package path in the local spark distribution.
- localValue() - Method in class org.apache.spark.Accumulable
-
Deprecated.
Get the current value of this accumulator from within a task.
- localValue() - Static method in class org.apache.spark.Accumulator
-
Deprecated.
- locate(String, Column) - Static method in class org.apache.spark.sql.functions
-
Locate the position of the first occurrence of substr.
- locate(String, Column, int) - Static method in class org.apache.spark.sql.functions
-
Locate the position of the first occurrence of substr in a string column, after position pos.
- location() - Method in class org.apache.spark.streaming.scheduler.ReceiverInfo
-
- locationUri() - Method in class org.apache.spark.sql.catalog.Database
-
- log(Function0<Parsers.Parser<T>>, String) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- log(Column) - Static method in class org.apache.spark.sql.functions
-
Computes the natural logarithm of the given value.
- log(String) - Static method in class org.apache.spark.sql.functions
-
Computes the natural logarithm of the given column.
- log(double, Column) - Static method in class org.apache.spark.sql.functions
-
Returns the first argument-base logarithm of the second argument.
- log(double, String) - Static method in class org.apache.spark.sql.functions
-
Returns the first argument-base logarithm of the second argument.
- log10(Column) - Static method in class org.apache.spark.sql.functions
-
Computes the logarithm of the given value in base 10.
- log10(String) - Static method in class org.apache.spark.sql.functions
-
Computes the logarithm of the given value in base 10.
- log1p(Column) - Static method in class org.apache.spark.sql.functions
-
Computes the natural logarithm of the given value plus one.
- log1p(String) - Static method in class org.apache.spark.sql.functions
-
Computes the natural logarithm of the given column plus one.
- log2(Column) - Static method in class org.apache.spark.sql.functions
-
Computes the logarithm of the given column in base 2.
- log2(String) - Static method in class org.apache.spark.sql.functions
-
Computes the logarithm of the given value in base 2.
- logDeprecationWarning(String) - Static method in class org.apache.spark.SparkConf
-
Logs a warning message if the given config key is deprecated.
- logEvent() - Method in interface org.apache.spark.scheduler.SparkListenerEvent
-
- LogisticAggregator - Class in org.apache.spark.ml.classification
-
LogisticAggregator computes the gradient and loss for binary logistic loss function, as used
in binary classification for instances in sparse or dense vector in an online fashion.
- LogisticAggregator(int, int, boolean) - Constructor for class org.apache.spark.ml.classification.LogisticAggregator
-
- LogisticCostFun - Class in org.apache.spark.ml.classification
-
LogisticCostFun implements Breeze's DiffFunction[T] for a multinomial logistic loss function,
as used in multi-class classification (it is also used in binary logistic regression).
- LogisticCostFun(RDD<org.apache.spark.ml.feature.Instance>, int, boolean, boolean, double[], double[], double) - Constructor for class org.apache.spark.ml.classification.LogisticCostFun
-
- LogisticGradient - Class in org.apache.spark.mllib.optimization
-
:: DeveloperApi ::
Compute gradient and loss for a multinomial logistic loss function, as used
in multi-class classification (it is also used in binary logistic regression).
- LogisticGradient(int) - Constructor for class org.apache.spark.mllib.optimization.LogisticGradient
-
- LogisticGradient() - Constructor for class org.apache.spark.mllib.optimization.LogisticGradient
-
- LogisticRegression - Class in org.apache.spark.ml.classification
-
Logistic regression.
- LogisticRegression(String) - Constructor for class org.apache.spark.ml.classification.LogisticRegression
-
- LogisticRegression() - Constructor for class org.apache.spark.ml.classification.LogisticRegression
-
- LogisticRegressionDataGenerator - Class in org.apache.spark.mllib.util
-
:: DeveloperApi ::
Generate test data for LogisticRegression.
- LogisticRegressionDataGenerator() - Constructor for class org.apache.spark.mllib.util.LogisticRegressionDataGenerator
-
- LogisticRegressionModel - Class in org.apache.spark.ml.classification
-
- LogisticRegressionModel - Class in org.apache.spark.mllib.classification
-
Classification model trained using Multinomial/Binary Logistic Regression.
- LogisticRegressionModel(Vector, double, int, int) - Constructor for class org.apache.spark.mllib.classification.LogisticRegressionModel
-
- LogisticRegressionModel(Vector, double) - Constructor for class org.apache.spark.mllib.classification.LogisticRegressionModel
-
- LogisticRegressionSummary - Interface in org.apache.spark.ml.classification
-
Abstraction for Logistic Regression Results for a given model.
- LogisticRegressionTrainingSummary - Interface in org.apache.spark.ml.classification
-
Abstraction for multinomial Logistic Regression Training results.
- LogisticRegressionWithLBFGS - Class in org.apache.spark.mllib.classification
-
Train a classification model for Multinomial/Binary Logistic Regression using
Limited-memory BFGS.
- LogisticRegressionWithLBFGS() - Constructor for class org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS
-
- LogisticRegressionWithSGD - Class in org.apache.spark.mllib.classification
-
Train a classification model for Binary Logistic Regression
using Stochastic Gradient Descent.
- LogisticRegressionWithSGD() - Constructor for class org.apache.spark.mllib.classification.LogisticRegressionWithSGD
-
Deprecated.
Use ml.classification.LogisticRegression or LogisticRegressionWithLBFGS. Since 2.0.0.
- logLikelihood(Dataset<?>) - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- logLikelihood(Dataset<?>) - Method in class org.apache.spark.ml.clustering.LDAModel
-
Calculates a lower bound on the log likelihood of the entire corpus.
- logLikelihood(Dataset<?>) - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- logLikelihood() - Method in class org.apache.spark.mllib.clustering.DistributedLDAModel
-
Log likelihood of the observed tokens in the training set,
given the current parameter estimates:
log P(docs | topics, topic distributions for docs, alpha, eta)
- logLikelihood() - Method in class org.apache.spark.mllib.clustering.ExpectationSum
-
- logLikelihood(RDD<Tuple2<Object, Vector>>) - Method in class org.apache.spark.mllib.clustering.LocalLDAModel
-
Calculates a lower bound on the log likelihood of the entire corpus.
- logLikelihood(JavaPairRDD<Long, Vector>) - Method in class org.apache.spark.mllib.clustering.LocalLDAModel
-
Java-friendly version of logLikelihood
- LogLoss - Class in org.apache.spark.mllib.tree.loss
-
:: DeveloperApi ::
Class for log loss calculation (for classification).
- LogLoss() - Constructor for class org.apache.spark.mllib.tree.loss.LogLoss
-
- LogNormalGenerator - Class in org.apache.spark.mllib.random
-
:: DeveloperApi ::
Generates i.i.d.
- LogNormalGenerator(double, double) - Constructor for class org.apache.spark.mllib.random.LogNormalGenerator
-
- logNormalGraph(SparkContext, int, int, double, double, long) - Static method in class org.apache.spark.graphx.util.GraphGenerators
-
Generate a graph whose vertex out degree distribution is log normal.
- logNormalJavaRDD(JavaSparkContext, double, double, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- logNormalJavaRDD(JavaSparkContext, double, double, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- logNormalJavaRDD(JavaSparkContext, double, double, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- logNormalJavaVectorRDD(JavaSparkContext, double, double, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- logNormalJavaVectorRDD(JavaSparkContext, double, double, long, int, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- logNormalJavaVectorRDD(JavaSparkContext, double, double, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- logNormalRDD(SparkContext, double, double, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
Generates an RDD comprised of i.i.d. samples from the log normal distribution with the input
mean and standard deviation
- logNormalVectorRDD(SparkContext, double, double, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
Generates an RDD[Vector] with vectors containing i.i.d. samples drawn from a
log normal distribution.
- logpdf(Vector) - Method in class org.apache.spark.ml.stat.distribution.MultivariateGaussian
-
Returns the log-density of this multivariate Gaussian at given point, x
- logpdf(Vector) - Method in class org.apache.spark.mllib.stat.distribution.MultivariateGaussian
-
Returns the log-density of this multivariate Gaussian at given point, x
- logPerplexity(Dataset<?>) - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- logPerplexity(Dataset<?>) - Method in class org.apache.spark.ml.clustering.LDAModel
-
Calculate an upper bound bound on perplexity.
- logPerplexity(Dataset<?>) - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- logPerplexity(RDD<Tuple2<Object, Vector>>) - Method in class org.apache.spark.mllib.clustering.LocalLDAModel
-
Calculate an upper bound bound on perplexity.
- logPerplexity(JavaPairRDD<Long, Vector>) - Method in class org.apache.spark.mllib.clustering.LocalLDAModel
-
Java-friendly version of logPerplexity
- logPrior() - Method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
Log probability of the current parameter estimate:
log P(topics, topic distributions for docs | Dirichlet hyperparameters)
- logPrior() - Method in class org.apache.spark.mllib.clustering.DistributedLDAModel
-
Log probability of the current parameter estimate:
log P(topics, topic distributions for docs | alpha, eta)
- logStartFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
- logStartToJson(org.apache.spark.scheduler.SparkListenerLogStart) - Static method in class org.apache.spark.util.JsonProtocol
-
- logUncaughtExceptions(Function0<T>) - Static method in class org.apache.spark.util.Utils
-
Execute the given block, logging and re-throwing any uncaught exception.
- logUrlMap() - Method in class org.apache.spark.scheduler.cluster.ExecutorInfo
-
- logUrls() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutor
-
- LONG() - Static method in class org.apache.spark.sql.Encoders
-
An encoder for nullable long type.
- longAccumulator() - Method in class org.apache.spark.SparkContext
-
Create and register a long accumulator, which starts with 0 and accumulates inputs by add.
- longAccumulator(String) - Method in class org.apache.spark.SparkContext
-
Create and register a long accumulator, which starts with 0 and accumulates inputs by add.
- LongAccumulator - Class in org.apache.spark.util
-
An
accumulator for computing sum, count, and averages for 64-bit integers.
- LongAccumulator() - Constructor for class org.apache.spark.util.LongAccumulator
-
- longMetric(String) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- longMetric(String) - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- LongParam - Class in org.apache.spark.ml.param
-
:: DeveloperApi ::
Specialized version of Param[Long] for Java.
- LongParam(String, String, String, Function1<Object, Object>) - Constructor for class org.apache.spark.ml.param.LongParam
-
- LongParam(String, String, String) - Constructor for class org.apache.spark.ml.param.LongParam
-
- LongParam(Identifiable, String, String, Function1<Object, Object>) - Constructor for class org.apache.spark.ml.param.LongParam
-
- LongParam(Identifiable, String, String) - Constructor for class org.apache.spark.ml.param.LongParam
-
- LongType - Static variable in class org.apache.spark.sql.types.DataTypes
-
Gets the LongType object.
- LongType - Class in org.apache.spark.sql.types
-
:: DeveloperApi ::
The data type representing Long values.
- lookup(K) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return the list of values in the RDD for key key.
- lookup(K) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Return the list of values in the RDD for key key.
- lookupRpcTimeout(SparkConf) - Static method in class org.apache.spark.util.RpcUtils
-
Returns the default Spark timeout to use for RPC remote endpoint lookup.
- loss() - Method in class org.apache.spark.ml.classification.LogisticAggregator
-
- loss() - Method in class org.apache.spark.ml.regression.AFTAggregator
-
- loss() - Method in class org.apache.spark.ml.regression.LeastSquaresAggregator
-
- loss() - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- Loss - Interface in org.apache.spark.mllib.tree.loss
-
:: DeveloperApi ::
Trait for adding "pluggable" loss functions for the gradient boosting algorithm.
- Losses - Class in org.apache.spark.mllib.tree.loss
-
- Losses() - Constructor for class org.apache.spark.mllib.tree.loss.Losses
-
- LossReasonPending - Class in org.apache.spark.scheduler
-
A loss reason that means we don't yet know why the executor exited.
- LossReasonPending() - Constructor for class org.apache.spark.scheduler.LossReasonPending
-
- lossType() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- lossType() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- lossType() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- lossType() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- LOST() - Static method in class org.apache.spark.TaskState
-
- low() - Method in class org.apache.spark.partial.BoundedDouble
-
- lower(Column) - Static method in class org.apache.spark.sql.functions
-
Converts a string column to lower case.
- lpad(Column, int, String) - Static method in class org.apache.spark.sql.functions
-
Left-pad the string column with
- lt(double) - Static method in class org.apache.spark.ml.param.ParamValidators
-
Check if value < upperBound
- lt(Object) - Method in class org.apache.spark.sql.Column
-
Less than.
- ltEq(double) - Static method in class org.apache.spark.ml.param.ParamValidators
-
Check if value <= upperBound
- ltrim(Column) - Static method in class org.apache.spark.sql.functions
-
Trim the spaces from left end for the specified string value.
- LZ4BlockInputStream - Class in org.apache.spark.io
-
InputStream implementation to decode data written with
LZ4BlockOutputStream.
- LZ4BlockInputStream(InputStream, LZ4FastDecompressor, Checksum) - Constructor for class org.apache.spark.io.LZ4BlockInputStream
-
Create a new InputStream.
- LZ4BlockInputStream(InputStream, LZ4FastDecompressor) - Constructor for class org.apache.spark.io.LZ4BlockInputStream
-
Create a new instance using XXHash32 for checksuming.
- LZ4BlockInputStream(InputStream) - Constructor for class org.apache.spark.io.LZ4BlockInputStream
-
Create a new instance which uses the fastest LZ4FastDecompressor available.
- LZ4CompressionCodec - Class in org.apache.spark.io
-
- LZ4CompressionCodec(SparkConf) - Constructor for class org.apache.spark.io.LZ4CompressionCodec
-
- LZFCompressionCodec - Class in org.apache.spark.io
-
- LZFCompressionCodec(SparkConf) - Constructor for class org.apache.spark.io.LZFCompressionCodec
-
- main(String[]) - Static method in class org.apache.spark.ml.param.shared.SharedParamsCodeGen
-
- main(String[]) - Static method in class org.apache.spark.mllib.util.KMeansDataGenerator
-
- main(String[]) - Static method in class org.apache.spark.mllib.util.LinearDataGenerator
-
- main(String[]) - Static method in class org.apache.spark.mllib.util.LogisticRegressionDataGenerator
-
- main(String[]) - Static method in class org.apache.spark.mllib.util.MFDataGenerator
-
- main(String[]) - Static method in class org.apache.spark.mllib.util.SVMDataGenerator
-
- main(String[]) - Static method in class org.apache.spark.streaming.util.RawTextSender
-
- main(String[]) - Static method in class org.apache.spark.ui.UIWorkloadGenerator
-
- majorMinorVersion(String) - Static method in class org.apache.spark.util.VersionUtils
-
Given a Spark version string, return the (major version number, minor version number).
- majorVersion(String) - Static method in class org.apache.spark.util.VersionUtils
-
Given a Spark version string, return the major version number.
- makeBinarySearch(Ordering<K>, ClassTag<K>) - Static method in class org.apache.spark.util.CollectionsUtils
-
- makeCopy(Object[]) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- makeCopy(Object[]) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- makeCopy(Object[]) - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- makeDataset(Seq<T>, SparkSession, TypeTags.TypeTag<T>) - Static method in class org.apache.spark.sql.internal.CatalogImpl
-
- makeDescription(String, String, boolean) - Static method in class org.apache.spark.ui.UIUtils
-
Returns HTML rendering of a job or stage description.
- makeDriverRef(String, SparkConf, org.apache.spark.rpc.RpcEnv) - Static method in class org.apache.spark.util.RpcUtils
-
Retrieve a RpcEndpointRef which is located in the driver via its name.
- makeProgressBar(int, int, int, int, int) - Static method in class org.apache.spark.ui.UIUtils
-
- makeRDD(Seq<T>, int, ClassTag<T>) - Method in class org.apache.spark.SparkContext
-
Distribute a local Scala collection to form an RDD.
- makeRDD(Seq<Tuple2<T, Seq<String>>>, ClassTag<T>) - Method in class org.apache.spark.SparkContext
-
Distribute a local Scala collection to form an RDD, with one or more
location preferences (hostnames of Spark nodes) for each object.
- map(Function<T, R>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- map(Function<T, R>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- map(Function<T, R>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- map(Function<T, R>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by applying a function to all elements of this RDD.
- map(Function1<T, U>, ClassTag<U>) - Static method in class org.apache.spark.api.r.RRDD
-
- map(Function1<T, U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- map(Function1<T, U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- map(Function1<T, U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- map(Function1<T, U>, ClassTag<U>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- map(Function1<Object, Object>) - Method in interface org.apache.spark.ml.linalg.Matrix
-
Map the values of this matrix using a function.
- map(Function1<Object, Object>) - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Map the values of this matrix using a function.
- map(Function1<R, T>) - Method in class org.apache.spark.partial.PartialResult
-
Transform this PartialResult into a PartialResult of type T.
- map(Function1<T, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- map(Function1<T, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- map(Function1<T, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- map(Function1<T, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- map(Function1<T, U>, ClassTag<U>) - Method in class org.apache.spark.rdd.RDD
-
Return a new RDD by applying a function to all elements of this RDD.
- map(Function1<T, U>, ClassTag<U>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- map(DataType, DataType) - Method in class org.apache.spark.sql.ColumnName
-
Creates a new StructField of type map.
- map(MapType) - Method in class org.apache.spark.sql.ColumnName
-
- map(Function1<T, U>, Encoder<U>) - Method in class org.apache.spark.sql.Dataset
-
:: Experimental ::
(Scala-specific)
Returns a new Dataset that contains the result of applying func to each element.
- map(MapFunction<T, U>, Encoder<U>) - Method in class org.apache.spark.sql.Dataset
-
:: Experimental ::
(Java-specific)
Returns a new Dataset that contains the result of applying func to each element.
- map(Column...) - Static method in class org.apache.spark.sql.functions
-
Creates a new map column.
- map(Seq<Column>) - Static method in class org.apache.spark.sql.functions
-
Creates a new map column.
- map(Function1<BaseType, A>) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- map(Function1<BaseType, A>) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- map(Function1<BaseType, A>) - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- map(Function1<A, B>, CanBuildFrom<Repr, B, That>) - Static method in class org.apache.spark.sql.types.StructType
-
- map(Function<T, R>) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- map(Function<T, R>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream by applying a function to all elements of this DStream.
- map(Function<T, R>) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- map(Function<T, R>) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- map(Function<T, R>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- map(Function<T, R>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- map(Function<T, R>) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- map(Function1<T, U>, ClassTag<U>) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream by applying a function to all elements of this DStream.
- mapAsSerializableJavaMap(Map<A, B>) - Static method in class org.apache.spark.api.java.JavaUtils
-
- mapChildren(Function1<BaseType, BaseType>) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- mapChildren(Function1<BaseType, BaseType>) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- mapChildren(Function1<BaseType, BaseType>) - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- mapEdgePartitions(Function2<Object, EdgePartition<ED, VD>, EdgePartition<ED2, VD2>>, ClassTag<ED2>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- mapEdges(Function1<Edge<ED>, ED2>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.Graph
-
Transforms each edge attribute in the graph using the map function.
- mapEdges(Function2<Object, Iterator<Edge<ED>>, Iterator<ED2>>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.Graph
-
Transforms each edge attribute using the map function, passing it a whole partition at a
time.
- mapEdges(Function2<Object, Iterator<Edge<ED>>, Iterator<ED2>>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- mapFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
-------------------------------- *
Util JSON deserialization methods |
- MapFunction<T,U> - Interface in org.apache.spark.api.java.function
-
Base interface for a map function used in Dataset's map function.
- mapGroups(Function2<K, Iterator<V>, U>, Encoder<U>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
-
Applies the given function to each group of data.
- mapGroups(MapGroupsFunction<K, V, U>, Encoder<U>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
-
Applies the given function to each group of data.
- MapGroupsFunction<K,V,R> - Interface in org.apache.spark.api.java.function
-
Base interface for a map function used in GroupedDataset's mapGroup function.
- mapId() - Method in class org.apache.spark.FetchFailed
-
- mapId() - Method in class org.apache.spark.storage.ShuffleBlockId
-
- mapId() - Method in class org.apache.spark.storage.ShuffleDataBlockId
-
- mapId() - Method in class org.apache.spark.storage.ShuffleIndexBlockId
-
- mapOutputTracker() - Method in class org.apache.spark.SparkEnv
-
- mapPartitions(FlatMapFunction<Iterator<T>, U>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- mapPartitions(FlatMapFunction<Iterator<T>, U>, boolean) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- mapPartitions(FlatMapFunction<Iterator<T>, U>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- mapPartitions(FlatMapFunction<Iterator<T>, U>, boolean) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- mapPartitions(FlatMapFunction<Iterator<T>, U>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- mapPartitions(FlatMapFunction<Iterator<T>, U>, boolean) - Static method in class org.apache.spark.api.java.JavaRDD
-
- mapPartitions(FlatMapFunction<Iterator<T>, U>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by applying a function to each partition of this RDD.
- mapPartitions(FlatMapFunction<Iterator<T>, U>, boolean) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by applying a function to each partition of this RDD.
- mapPartitions(Function1<Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Static method in class org.apache.spark.api.r.RRDD
-
- mapPartitions(Function1<Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- mapPartitions(Function1<Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- mapPartitions(Function1<Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- mapPartitions(Function1<Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- mapPartitions(Function1<Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- mapPartitions(Function1<Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- mapPartitions(Function1<Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- mapPartitions(Function1<Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- mapPartitions(Function1<Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Method in class org.apache.spark.rdd.RDD
-
Return a new RDD by applying a function to each partition of this RDD.
- mapPartitions(Function1<Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- mapPartitions(Function1<Iterator<T>, Iterator<U>>, Encoder<U>) - Method in class org.apache.spark.sql.Dataset
-
:: Experimental ::
(Scala-specific)
Returns a new Dataset that contains the result of applying func to each partition.
- mapPartitions(MapPartitionsFunction<T, U>, Encoder<U>) - Method in class org.apache.spark.sql.Dataset
-
:: Experimental ::
(Java-specific)
Returns a new Dataset that contains the result of applying f to each partition.
- mapPartitions(FlatMapFunction<Iterator<T>, U>) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- mapPartitions(FlatMapFunction<Iterator<T>, U>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD is generated by applying mapPartitions() to each RDDs
of this DStream.
- mapPartitions(FlatMapFunction<Iterator<T>, U>) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- mapPartitions(FlatMapFunction<Iterator<T>, U>) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- mapPartitions(FlatMapFunction<Iterator<T>, U>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- mapPartitions(FlatMapFunction<Iterator<T>, U>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- mapPartitions(FlatMapFunction<Iterator<T>, U>) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- mapPartitions(Function1<Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream in which each RDD is generated by applying mapPartitions() to each RDDs
of this DStream.
- mapPartitions$default$2() - Static method in class org.apache.spark.api.r.RRDD
-
- mapPartitions$default$2() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- mapPartitions$default$2() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- mapPartitions$default$2() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- mapPartitions$default$2() - Static method in class org.apache.spark.graphx.VertexRDD
-
- mapPartitions$default$2() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- mapPartitions$default$2() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- mapPartitions$default$2() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- mapPartitions$default$2() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- mapPartitions$default$2() - Static method in class org.apache.spark.rdd.UnionRDD
-
- MapPartitionsFunction<T,U> - Interface in org.apache.spark.api.java.function
-
Base interface for function used in Dataset's mapPartitions.
- mapPartitionsInternal$default$2() - Static method in class org.apache.spark.api.r.RRDD
-
- mapPartitionsInternal$default$2() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- mapPartitionsInternal$default$2() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- mapPartitionsInternal$default$2() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- mapPartitionsInternal$default$2() - Static method in class org.apache.spark.graphx.VertexRDD
-
- mapPartitionsInternal$default$2() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- mapPartitionsInternal$default$2() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- mapPartitionsInternal$default$2() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- mapPartitionsInternal$default$2() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- mapPartitionsInternal$default$2() - Static method in class org.apache.spark.rdd.UnionRDD
-
- mapPartitionsToDouble(DoubleFlatMapFunction<Iterator<T>>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- mapPartitionsToDouble(DoubleFlatMapFunction<Iterator<T>>, boolean) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- mapPartitionsToDouble(DoubleFlatMapFunction<Iterator<T>>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- mapPartitionsToDouble(DoubleFlatMapFunction<Iterator<T>>, boolean) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- mapPartitionsToDouble(DoubleFlatMapFunction<Iterator<T>>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- mapPartitionsToDouble(DoubleFlatMapFunction<Iterator<T>>, boolean) - Static method in class org.apache.spark.api.java.JavaRDD
-
- mapPartitionsToDouble(DoubleFlatMapFunction<Iterator<T>>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by applying a function to each partition of this RDD.
- mapPartitionsToDouble(DoubleFlatMapFunction<Iterator<T>>, boolean) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by applying a function to each partition of this RDD.
- mapPartitionsToPair(PairFlatMapFunction<Iterator<T>, K2, V2>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- mapPartitionsToPair(PairFlatMapFunction<Iterator<T>, K2, V2>, boolean) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- mapPartitionsToPair(PairFlatMapFunction<Iterator<T>, K2, V2>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- mapPartitionsToPair(PairFlatMapFunction<Iterator<T>, K2, V2>, boolean) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- mapPartitionsToPair(PairFlatMapFunction<Iterator<T>, K2, V2>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- mapPartitionsToPair(PairFlatMapFunction<Iterator<T>, K2, V2>, boolean) - Static method in class org.apache.spark.api.java.JavaRDD
-
- mapPartitionsToPair(PairFlatMapFunction<Iterator<T>, K2, V2>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by applying a function to each partition of this RDD.
- mapPartitionsToPair(PairFlatMapFunction<Iterator<T>, K2, V2>, boolean) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by applying a function to each partition of this RDD.
- mapPartitionsToPair(PairFlatMapFunction<Iterator<T>, K2, V2>) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- mapPartitionsToPair(PairFlatMapFunction<Iterator<T>, K2, V2>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD is generated by applying mapPartitions() to each RDDs
of this DStream.
- mapPartitionsToPair(PairFlatMapFunction<Iterator<T>, K2, V2>) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- mapPartitionsToPair(PairFlatMapFunction<Iterator<T>, K2, V2>) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- mapPartitionsToPair(PairFlatMapFunction<Iterator<T>, K2, V2>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- mapPartitionsToPair(PairFlatMapFunction<Iterator<T>, K2, V2>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- mapPartitionsToPair(PairFlatMapFunction<Iterator<T>, K2, V2>) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- mapPartitionsWithIndex(Function2<Integer, Iterator<T>, Iterator<R>>, boolean) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- mapPartitionsWithIndex(Function2<Integer, Iterator<T>, Iterator<R>>, boolean) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- mapPartitionsWithIndex(Function2<Integer, Iterator<T>, Iterator<R>>, boolean) - Static method in class org.apache.spark.api.java.JavaRDD
-
- mapPartitionsWithIndex(Function2<Integer, Iterator<T>, Iterator<R>>, boolean) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by applying a function to each partition of this RDD, while tracking the index
of the original partition.
- mapPartitionsWithIndex(Function2<Object, Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Static method in class org.apache.spark.api.r.RRDD
-
- mapPartitionsWithIndex(Function2<Object, Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- mapPartitionsWithIndex(Function2<Object, Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- mapPartitionsWithIndex(Function2<Object, Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- mapPartitionsWithIndex(Function2<Object, Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- mapPartitionsWithIndex(Function2<Object, Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- mapPartitionsWithIndex(Function2<Object, Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- mapPartitionsWithIndex(Function2<Object, Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- mapPartitionsWithIndex(Function2<Object, Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- mapPartitionsWithIndex(Function2<Object, Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Method in class org.apache.spark.rdd.RDD
-
Return a new RDD by applying a function to each partition of this RDD, while tracking the index
of the original partition.
- mapPartitionsWithIndex(Function2<Object, Iterator<T>, Iterator<U>>, boolean, ClassTag<U>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- mapPartitionsWithIndex$default$2() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- mapPartitionsWithIndex$default$2() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- mapPartitionsWithIndex$default$2() - Static method in class org.apache.spark.api.java.JavaRDD
-
- mapPartitionsWithIndex$default$2() - Static method in class org.apache.spark.api.r.RRDD
-
- mapPartitionsWithIndex$default$2() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- mapPartitionsWithIndex$default$2() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- mapPartitionsWithIndex$default$2() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- mapPartitionsWithIndex$default$2() - Static method in class org.apache.spark.graphx.VertexRDD
-
- mapPartitionsWithIndex$default$2() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- mapPartitionsWithIndex$default$2() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- mapPartitionsWithIndex$default$2() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- mapPartitionsWithIndex$default$2() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- mapPartitionsWithIndex$default$2() - Static method in class org.apache.spark.rdd.UnionRDD
-
- mapPartitionsWithInputSplit(Function2<InputSplit, Iterator<Tuple2<K, V>>, Iterator<R>>, boolean) - Method in class org.apache.spark.api.java.JavaHadoopRDD
-
Maps over a partition, providing the InputSplit that was used as the base of the partition.
- mapPartitionsWithInputSplit(Function2<InputSplit, Iterator<Tuple2<K, V>>, Iterator<R>>, boolean) - Method in class org.apache.spark.api.java.JavaNewHadoopRDD
-
Maps over a partition, providing the InputSplit that was used as the base of the partition.
- mapPartitionsWithInputSplit(Function2<InputSplit, Iterator<Tuple2<K, V>>, Iterator<U>>, boolean, ClassTag<U>) - Method in class org.apache.spark.rdd.HadoopRDD
-
Maps over a partition, providing the InputSplit that was used as the base of the partition.
- mapPartitionsWithInputSplit(Function2<InputSplit, Iterator<Tuple2<K, V>>, Iterator<U>>, boolean, ClassTag<U>) - Method in class org.apache.spark.rdd.NewHadoopRDD
-
Maps over a partition, providing the InputSplit that was used as the base of the partition.
- mapredInputFormat() - Method in class org.apache.spark.scheduler.InputFormatInfo
-
- mapreduceInputFormat() - Method in class org.apache.spark.scheduler.InputFormatInfo
-
- mapSideCombine() - Method in class org.apache.spark.ShuffleDependency
-
- mapToDouble(DoubleFunction<T>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- mapToDouble(DoubleFunction<T>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- mapToDouble(DoubleFunction<T>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- mapToDouble(DoubleFunction<T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by applying a function to all elements of this RDD.
- mapToJson(Map<String, String>) - Static method in class org.apache.spark.util.JsonProtocol
-
------------------------------ *
Util JSON serialization methods |
- mapToPair(PairFunction<T, K2, V2>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- mapToPair(PairFunction<T, K2, V2>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- mapToPair(PairFunction<T, K2, V2>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- mapToPair(PairFunction<T, K2, V2>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return a new RDD by applying a function to all elements of this RDD.
- mapToPair(PairFunction<T, K2, V2>) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- mapToPair(PairFunction<T, K2, V2>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream by applying a function to all elements of this DStream.
- mapToPair(PairFunction<T, K2, V2>) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- mapToPair(PairFunction<T, K2, V2>) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- mapToPair(PairFunction<T, K2, V2>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- mapToPair(PairFunction<T, K2, V2>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- mapToPair(PairFunction<T, K2, V2>) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- mapTriplets(Function1<EdgeTriplet<VD, ED>, ED2>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.Graph
-
Transforms each edge attribute using the map function, passing it the adjacent vertex
attributes as well.
- mapTriplets(Function1<EdgeTriplet<VD, ED>, ED2>, TripletFields, ClassTag<ED2>) - Method in class org.apache.spark.graphx.Graph
-
Transforms each edge attribute using the map function, passing it the adjacent vertex
attributes as well.
- mapTriplets(Function2<Object, Iterator<EdgeTriplet<VD, ED>>, Iterator<ED2>>, TripletFields, ClassTag<ED2>) - Method in class org.apache.spark.graphx.Graph
-
Transforms each edge attribute a partition at a time using the map function, passing it the
adjacent vertex attributes as well.
- mapTriplets(Function2<Object, Iterator<EdgeTriplet<VD, ED>>, Iterator<ED2>>, TripletFields, ClassTag<ED2>) - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- MapType - Class in org.apache.spark.sql.types
-
:: DeveloperApi ::
The data type for Maps.
- MapType(DataType, DataType, boolean) - Constructor for class org.apache.spark.sql.types.MapType
-
- MapType() - Constructor for class org.apache.spark.sql.types.MapType
-
No-arg constructor for kryo.
- mapValues(Function<V, U>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Pass each value in the key-value pair RDD through a map function without changing the keys;
this also retains the original RDD's partitioning.
- mapValues(Function1<Edge<ED>, ED2>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.EdgeRDD
-
Map the values in an edge partitioning preserving the structure but changing the values.
- mapValues(Function1<Edge<ED>, ED2>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- mapValues(Function1<VD, VD2>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- mapValues(Function2<Object, VD, VD2>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- mapValues(Function1<VD, VD2>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.VertexRDD
-
Maps each vertex attribute, preserving the index.
- mapValues(Function2<Object, VD, VD2>, ClassTag<VD2>) - Method in class org.apache.spark.graphx.VertexRDD
-
Maps each vertex attribute, additionally supplying the vertex ID.
- mapValues(Function1<V, U>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Pass each value in the key-value pair RDD through a map function without changing the keys;
this also retains the original RDD's partitioning.
- mapValues(Function<V, U>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying a map function to the value of each key-value pairs in
'this' DStream without changing the key.
- mapValues(Function<V, U>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- mapValues(Function<V, U>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- mapValues(Function1<V, U>, ClassTag<U>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying a map function to the value of each key-value pairs in
'this' DStream without changing the key.
- mapVertices(Function2<Object, VD, VD2>, ClassTag<VD2>, Predef.$eq$colon$eq<VD, VD2>) - Method in class org.apache.spark.graphx.Graph
-
Transforms each vertex attribute in the graph using the map function.
- mapVertices(Function2<Object, VD, VD2>, ClassTag<VD2>, Predef.$eq$colon$eq<VD, VD2>) - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- mapVertices$default$3(Function2<Object, VD, VD2>) - Static method in class org.apache.spark.graphx.impl.GraphImpl
-
- mapWithState(StateSpec<K, V, StateType, MappedType>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
:: Experimental ::
Return a
JavaMapWithStateDStream by applying a function to every key-value element of
this stream, while maintaining some state data for each unique key.
- mapWithState(StateSpec<K, V, StateType, MappedType>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- mapWithState(StateSpec<K, V, StateType, MappedType>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- mapWithState(StateSpec<K, V, StateType, MappedType>, ClassTag<StateType>, ClassTag<MappedType>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
:: Experimental ::
Return a
MapWithStateDStream by applying a function to every key-value element of
this stream, while maintaining some state data for each unique key.
- MapWithStateDStream<KeyType,ValueType,StateType,MappedType> - Class in org.apache.spark.streaming.dstream
-
:: Experimental ::
DStream representing the stream of data generated by
mapWithState operation on a
pair DStream.
- MapWithStateDStream(StreamingContext, ClassTag<MappedType>) - Constructor for class org.apache.spark.streaming.dstream.MapWithStateDStream
-
- mark(int) - Method in class org.apache.spark.io.LZ4BlockInputStream
-
- mark(int) - Method in class org.apache.spark.storage.BufferReleasingInputStream
-
- markSupported() - Method in class org.apache.spark.io.LZ4BlockInputStream
-
- markSupported() - Method in class org.apache.spark.storage.BufferReleasingInputStream
-
- mask(Graph<VD2, ED2>, ClassTag<VD2>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.Graph
-
Restricts the graph to only the vertices and edges that are also in other, but keeps the
attributes from this graph.
- mask(Graph<VD2, ED2>, ClassTag<VD2>, ClassTag<ED2>) - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- master() - Method in class org.apache.spark.api.java.JavaSparkContext
-
- master() - Method in class org.apache.spark.SparkContext
-
- master(String) - Method in class org.apache.spark.sql.SparkSession.Builder
-
Sets the Spark master URL to connect to, such as "local" to run locally, "local[4]" to
run locally with 4 cores, or "spark://master:7077" to run on a Spark standalone cluster.
- Matrices - Class in org.apache.spark.ml.linalg
-
- Matrices() - Constructor for class org.apache.spark.ml.linalg.Matrices
-
- Matrices - Class in org.apache.spark.mllib.linalg
-
- Matrices() - Constructor for class org.apache.spark.mllib.linalg.Matrices
-
- Matrix - Interface in org.apache.spark.ml.linalg
-
Trait for a local matrix.
- Matrix - Interface in org.apache.spark.mllib.linalg
-
Trait for a local matrix.
- MatrixEntry - Class in org.apache.spark.mllib.linalg.distributed
-
Represents an entry in a distributed matrix.
- MatrixEntry(long, long, double) - Constructor for class org.apache.spark.mllib.linalg.distributed.MatrixEntry
-
- MatrixFactorizationModel - Class in org.apache.spark.mllib.recommendation
-
Model representing the result of matrix factorization.
- MatrixFactorizationModel(int, RDD<Tuple2<Object, double[]>>, RDD<Tuple2<Object, double[]>>) - Constructor for class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
-
- MatrixFactorizationModel.SaveLoadV1_0$ - Class in org.apache.spark.mllib.recommendation
-
- MatrixFactorizationModel.SaveLoadV1_0$() - Constructor for class org.apache.spark.mllib.recommendation.MatrixFactorizationModel.SaveLoadV1_0$
-
- MatrixImplicits - Class in org.apache.spark.mllib.linalg
-
Implicit methods available in Scala for converting
Matrix to
Matrix and vice versa.
- MatrixImplicits() - Constructor for class org.apache.spark.mllib.linalg.MatrixImplicits
-
- MatrixType() - Static method in class org.apache.spark.ml.linalg.SQLDataTypes
-
- max() - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Returns the maximum element from this RDD as defined by
the default comparator natural order.
- max(Comparator<T>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- max(Comparator<T>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- max(Comparator<T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Returns the maximum element from this RDD as defined by the specified
Comparator[T].
- max(Ordering<T>) - Static method in class org.apache.spark.api.r.RRDD
-
- max(Ordering<T>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- max(Ordering<T>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- max(Ordering<T>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- max(Ordering<T>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- MAX() - Static method in class org.apache.spark.ml.attribute.AttributeKeys
-
- max() - Method in class org.apache.spark.ml.attribute.NumericAttribute
-
- max() - Static method in class org.apache.spark.ml.feature.MinMaxScaler
-
- max() - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- max() - Method in class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
-
Maximum value of each dimension.
- max() - Method in interface org.apache.spark.mllib.stat.MultivariateStatisticalSummary
-
Maximum value of each column.
- max(Ordering<T>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- max(Ordering<T>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- max(Ordering<T>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- max(Ordering<T>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- max(Ordering<T>) - Method in class org.apache.spark.rdd.RDD
-
Returns the max of this RDD as defined by the implicit Ordering[T].
- max(Ordering<T>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- max(Column) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the maximum value of the expression in a group.
- max(String) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the maximum value of the column in a group.
- max(String...) - Method in class org.apache.spark.sql.RelationalGroupedDataset
-
Compute the max value for each numeric columns for each group.
- max(Seq<String>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
-
Compute the max value for each numeric columns for each group.
- max(Ordering<B>) - Static method in class org.apache.spark.sql.types.StructType
-
- max(Duration) - Method in class org.apache.spark.streaming.Duration
-
- max(Time) - Method in class org.apache.spark.streaming.Time
-
- max(long, long) - Static method in class org.apache.spark.streaming.util.RawTextHelper
-
- max() - Method in class org.apache.spark.util.StatCounter
-
- MAX_INT_DIGITS() - Static method in class org.apache.spark.sql.types.Decimal
-
Maximum number of decimal digits an Int can represent
- MAX_LONG_DIGITS() - Static method in class org.apache.spark.sql.types.Decimal
-
Maximum number of decimal digits a Long can represent
- MAX_PRECISION() - Static method in class org.apache.spark.sql.types.DecimalType
-
- MAX_SCALE() - Static method in class org.apache.spark.sql.types.DecimalType
-
- maxAbs() - Method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- MaxAbsScaler - Class in org.apache.spark.ml.feature
-
:: Experimental ::
Rescale each feature individually to range [-1, 1] by dividing through the largest maximum
absolute value in each feature.
- MaxAbsScaler(String) - Constructor for class org.apache.spark.ml.feature.MaxAbsScaler
-
- MaxAbsScaler() - Constructor for class org.apache.spark.ml.feature.MaxAbsScaler
-
- MaxAbsScalerModel - Class in org.apache.spark.ml.feature
-
- maxBins() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- maxBins() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- maxBins() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- maxBins() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- maxBins() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- maxBins() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- maxBins() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- maxBins() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- maxBins() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- maxBins() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- maxBins() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- maxBins() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- maxBins() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- maxBufferSizeMb() - Method in class org.apache.spark.serializer.KryoSerializer
-
- maxBy(Function1<A, B>, Ordering<B>) - Static method in class org.apache.spark.sql.types.StructType
-
- maxCategories() - Static method in class org.apache.spark.ml.feature.VectorIndexer
-
- maxCategories() - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- maxCores() - Method in class org.apache.spark.status.api.v1.ApplicationInfo
-
- maxDepth() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- maxDepth() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- maxDepth() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- maxDepth() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- maxDepth() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- maxDepth() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- maxDepth() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- maxDepth() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- maxDepth() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- maxDepth() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- maxDepth() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- maxDepth() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- maxDepth() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- maxId() - Static method in class org.apache.spark.mllib.tree.configuration.Algo
-
- maxId() - Static method in class org.apache.spark.mllib.tree.configuration.EnsembleCombiningStrategy
-
- maxId() - Static method in class org.apache.spark.mllib.tree.configuration.FeatureType
-
- maxId() - Static method in class org.apache.spark.mllib.tree.configuration.QuantileStrategy
-
- maxId() - Static method in class org.apache.spark.rdd.CheckpointState
-
- maxId() - Static method in class org.apache.spark.scheduler.SchedulingMode
-
- maxId() - Static method in class org.apache.spark.scheduler.TaskLocality
-
- maxId() - Static method in class org.apache.spark.streaming.scheduler.ReceiverState
-
- maxId() - Static method in class org.apache.spark.TaskState
-
- maxIter() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- maxIter() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- maxIter() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- maxIter() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- maxIter() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- maxIter() - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- maxIter() - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- maxIter() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- maxIter() - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- maxIter() - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- maxIter() - Static method in class org.apache.spark.ml.clustering.KMeans
-
- maxIter() - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- maxIter() - Static method in class org.apache.spark.ml.clustering.LDA
-
- maxIter() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- maxIter() - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- maxIter() - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- maxIter() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- maxIter() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- maxIter() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- maxIter() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- maxIter() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- maxIter() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- maxIter() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- maxIter() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- maxIter() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- maxIters() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
-
- maxMem() - Method in class org.apache.spark.scheduler.SparkListenerBlockManagerAdded
-
- maxMem() - Method in class org.apache.spark.storage.StorageStatus
-
- maxMemory() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
-
- maxMemoryInMB() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- maxMemoryInMB() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- maxMemoryInMB() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- maxMemoryInMB() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- maxMemoryInMB() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- maxMemoryInMB() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- maxMemoryInMB() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- maxMemoryInMB() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- maxMemoryInMB() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- maxMemoryInMB() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- maxMemoryInMB() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- maxMemoryInMB() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- maxMemoryInMB() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- maxMemSize() - Method in class org.apache.spark.storage.BlockManagerMessages.RegisterBlockManager
-
- maxMessageSizeBytes(SparkConf) - Static method in class org.apache.spark.util.RpcUtils
-
Returns the configured max message size for messages in bytes.
- maxNodesInLevel(int) - Static method in class org.apache.spark.mllib.tree.model.Node
-
Return the maximum number of nodes which can be in the given level of the tree.
- maxRows() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- maxSentenceLength() - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- maxSentenceLength() - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- maxTasks() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
-
- maxVal() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
-
- md5(Column) - Static method in class org.apache.spark.sql.functions
-
Calculates the MD5 digest of a binary column and returns the value
as a 32 character hex string.
- mean() - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Compute the mean of this RDD's elements.
- mean() - Method in class org.apache.spark.ml.feature.StandardScalerModel
-
- mean() - Method in class org.apache.spark.ml.stat.distribution.MultivariateGaussian
-
- mean() - Method in class org.apache.spark.mllib.feature.StandardScalerModel
-
- mean() - Method in class org.apache.spark.mllib.random.ExponentialGenerator
-
- mean() - Method in class org.apache.spark.mllib.random.LogNormalGenerator
-
- mean() - Method in class org.apache.spark.mllib.random.PoissonGenerator
-
- mean() - Method in class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
-
Sample mean of each dimension.
- mean() - Method in interface org.apache.spark.mllib.stat.MultivariateStatisticalSummary
-
Sample mean vector.
- mean() - Method in class org.apache.spark.partial.BoundedDouble
-
- mean() - Method in class org.apache.spark.rdd.DoubleRDDFunctions
-
Compute the mean of this RDD's elements.
- mean(Column) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the average of the values in a group.
- mean(String) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the average of the values in a group.
- mean(String...) - Method in class org.apache.spark.sql.RelationalGroupedDataset
-
Compute the average value for each numeric columns for each group.
- mean(Seq<String>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
-
Compute the average value for each numeric columns for each group.
- mean() - Method in class org.apache.spark.util.StatCounter
-
- meanAbsoluteError() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
-
Returns the mean absolute error, which is a risk function corresponding to the
expected value of the absolute error loss or l1-norm loss.
- meanAbsoluteError() - Method in class org.apache.spark.mllib.evaluation.RegressionMetrics
-
Returns the mean absolute error, which is a risk function corresponding to the
expected value of the absolute error loss or l1-norm loss.
- meanApprox(long, Double) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Return the approximate mean of the elements in this RDD.
- meanApprox(long) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Approximate operation to return the mean within a timeout.
- meanApprox(long, double) - Method in class org.apache.spark.rdd.DoubleRDDFunctions
-
Approximate operation to return the mean within a timeout.
- meanAveragePrecision() - Method in class org.apache.spark.mllib.evaluation.RankingMetrics
-
Returns the mean average precision (MAP) of all the queries.
- means() - Method in class org.apache.spark.mllib.clustering.ExpectationSum
-
- meanSquaredError() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
-
Returns the mean squared error, which is a risk function corresponding to the
expected value of the squared error loss or quadratic loss.
- meanSquaredError() - Method in class org.apache.spark.mllib.evaluation.RegressionMetrics
-
Returns the mean squared error, which is a risk function corresponding to the
expected value of the squared error loss or quadratic loss.
- megabytesToString(long) - Static method in class org.apache.spark.util.Utils
-
Convert a quantity in megabytes to a human-readable string such as "4.0 MB".
- MEMORY_AND_DISK - Static variable in class org.apache.spark.api.java.StorageLevels
-
- MEMORY_AND_DISK() - Static method in class org.apache.spark.storage.StorageLevel
-
- MEMORY_AND_DISK_2 - Static variable in class org.apache.spark.api.java.StorageLevels
-
- MEMORY_AND_DISK_2() - Static method in class org.apache.spark.storage.StorageLevel
-
- MEMORY_AND_DISK_SER - Static variable in class org.apache.spark.api.java.StorageLevels
-
- MEMORY_AND_DISK_SER() - Static method in class org.apache.spark.storage.StorageLevel
-
- MEMORY_AND_DISK_SER_2 - Static variable in class org.apache.spark.api.java.StorageLevels
-
- MEMORY_AND_DISK_SER_2() - Static method in class org.apache.spark.storage.StorageLevel
-
- MEMORY_BYTES_SPILLED() - Static method in class org.apache.spark.InternalAccumulator
-
- MEMORY_ONLY - Static variable in class org.apache.spark.api.java.StorageLevels
-
- MEMORY_ONLY() - Static method in class org.apache.spark.storage.StorageLevel
-
- MEMORY_ONLY_2 - Static variable in class org.apache.spark.api.java.StorageLevels
-
- MEMORY_ONLY_2() - Static method in class org.apache.spark.storage.StorageLevel
-
- MEMORY_ONLY_SER - Static variable in class org.apache.spark.api.java.StorageLevels
-
- MEMORY_ONLY_SER() - Static method in class org.apache.spark.storage.StorageLevel
-
- MEMORY_ONLY_SER_2 - Static variable in class org.apache.spark.api.java.StorageLevels
-
- MEMORY_ONLY_SER_2() - Static method in class org.apache.spark.storage.StorageLevel
-
- memoryBytesSpilled() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
-
- memoryBytesSpilled() - Method in class org.apache.spark.status.api.v1.StageData
-
- memoryBytesSpilled() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
-
- memoryBytesSpilled() - Method in class org.apache.spark.status.api.v1.TaskMetrics
-
- memoryBytesSpilled() - Method in class org.apache.spark.ui.jobs.UIData.ExecutorSummary
-
- memoryBytesSpilled() - Method in class org.apache.spark.ui.jobs.UIData.StageUIData
-
- memoryBytesSpilled() - Method in class org.apache.spark.ui.jobs.UIData.TaskMetricsUIData
-
- MemoryEntry<T> - Interface in org.apache.spark.storage.memory
-
- memoryManager() - Method in class org.apache.spark.SparkEnv
-
- memoryMode() - Method in class org.apache.spark.storage.memory.DeserializedMemoryEntry
-
- memoryMode() - Method in interface org.apache.spark.storage.memory.MemoryEntry
-
- memoryMode() - Method in class org.apache.spark.storage.memory.SerializedMemoryEntry
-
- MemoryParam - Class in org.apache.spark.util
-
An extractor object for parsing JVM memory strings, such as "10g", into an Int representing
the number of megabytes.
- MemoryParam() - Constructor for class org.apache.spark.util.MemoryParam
-
- memoryPerExecutorMB() - Method in class org.apache.spark.status.api.v1.ApplicationInfo
-
- memoryRemaining() - Method in class org.apache.spark.status.api.v1.RDDDataDistribution
-
- memoryStringToMb(String) - Static method in class org.apache.spark.util.Utils
-
Convert a Java memory parameter passed to -Xmx (such as 300m or 1g) to a number of mebibytes.
- memoryUsed() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
-
- memoryUsed() - Method in class org.apache.spark.status.api.v1.RDDDataDistribution
-
- memoryUsed() - Method in class org.apache.spark.status.api.v1.RDDPartitionInfo
-
- memoryUsed() - Method in class org.apache.spark.status.api.v1.RDDStorageInfo
-
- memRemaining() - Method in class org.apache.spark.storage.StorageStatus
-
Return the memory remaining in this block manager.
- memSize() - Method in class org.apache.spark.storage.BlockManagerMessages.UpdateBlockInfo
-
- memSize() - Method in class org.apache.spark.storage.BlockStatus
-
- memSize() - Method in class org.apache.spark.storage.BlockUpdatedInfo
-
- memSize() - Method in class org.apache.spark.storage.RDDInfo
-
- memUsed() - Method in class org.apache.spark.storage.StorageStatus
-
Return the memory used by this block manager.
- memUsedByRdd(int) - Method in class org.apache.spark.storage.StorageStatus
-
Return the memory used by the given RDD in this block manager in O(1) time.
- merge(R) - Method in class org.apache.spark.Accumulable
-
Deprecated.
Merge two accumulable objects together
- merge(R) - Static method in class org.apache.spark.Accumulator
-
Deprecated.
- merge(LogisticAggregator) - Method in class org.apache.spark.ml.classification.LogisticAggregator
-
Merge another LogisticAggregator, and update the loss and gradient
of the objective function.
- merge(AFTAggregator) - Method in class org.apache.spark.ml.regression.AFTAggregator
-
Merge another AFTAggregator, and update the loss and gradient
of the objective function.
- merge(LeastSquaresAggregator) - Method in class org.apache.spark.ml.regression.LeastSquaresAggregator
-
Merge another LeastSquaresAggregator, and update the loss and gradient
of the objective function.
- merge(IDF.DocumentFrequencyAggregator) - Method in class org.apache.spark.mllib.feature.IDF.DocumentFrequencyAggregator
-
Merges another.
- merge(MultivariateOnlineSummarizer) - Method in class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
-
Merge another MultivariateOnlineSummarizer, and update the statistical summary.
- merge(BUF, BUF) - Method in class org.apache.spark.sql.expressions.Aggregator
-
Merge two intermediate values.
- merge(MutableAggregationBuffer, Row) - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
-
Merges two aggregation buffers and stores the updated buffer values back to buffer1.
- merge(AccumulatorV2<IN, OUT>) - Method in class org.apache.spark.util.AccumulatorV2
-
Merges another same-type accumulator into this one and update its state, i.e.
- merge(AccumulatorV2<T, List<T>>) - Method in class org.apache.spark.util.CollectionAccumulator
-
- merge(AccumulatorV2<Double, Double>) - Method in class org.apache.spark.util.DoubleAccumulator
-
- merge(AccumulatorV2<T, R>) - Method in class org.apache.spark.util.LegacyAccumulatorWrapper
-
- merge(AccumulatorV2<Long, Long>) - Method in class org.apache.spark.util.LongAccumulator
-
- merge(double) - Method in class org.apache.spark.util.StatCounter
-
Add a value into this StatCounter, updating the internal statistics.
- merge(TraversableOnce<Object>) - Method in class org.apache.spark.util.StatCounter
-
Add multiple values into this StatCounter, updating the internal statistics.
- merge(StatCounter) - Method in class org.apache.spark.util.StatCounter
-
Merge another StatCounter into this one, adding up the internal statistics.
- mergeCombiners() - Method in class org.apache.spark.Aggregator
-
- mergeInPlace(BloomFilter) - Method in class org.apache.spark.util.sketch.BloomFilter
-
Combines this bloom filter with another bloom filter by performing a bitwise OR of the
underlying data.
- mergeInPlace(CountMinSketch) - Method in class org.apache.spark.util.sketch.CountMinSketch
-
- mergeValue() - Method in class org.apache.spark.Aggregator
-
- MESOS_REGEX() - Static method in class org.apache.spark.SparkMasterRegex
-
- MesosSchedulerBackendUtil - Class in org.apache.spark.scheduler.cluster.mesos
-
A collection of utility functions which can be used by both the
MesosSchedulerBackend and the MesosFineGrainedSchedulerBackend.
- MesosSchedulerBackendUtil() - Constructor for class org.apache.spark.scheduler.cluster.mesos.MesosSchedulerBackendUtil
-
- message() - Method in class org.apache.spark.FetchFailed
-
- message() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutorFailed
-
- message() - Static method in class org.apache.spark.scheduler.ExecutorKilled
-
- message() - Static method in class org.apache.spark.scheduler.LossReasonPending
-
- message() - Method in exception org.apache.spark.sql.AnalysisException
-
- message() - Method in exception org.apache.spark.sql.streaming.StreamingQueryException
-
- MetaAlgorithmReadWrite - Class in org.apache.spark.ml.util
-
Default Meta-Algorithm read and write implementation.
- MetaAlgorithmReadWrite() - Constructor for class org.apache.spark.ml.util.MetaAlgorithmReadWrite
-
- metadata() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- metadata() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- Metadata - Class in org.apache.spark.sql.types
-
:: DeveloperApi ::
- metadata() - Method in class org.apache.spark.sql.types.StructField
-
- metadata() - Method in class org.apache.spark.streaming.scheduler.StreamInputInfo
-
- METADATA_KEY_DESCRIPTION() - Static method in class org.apache.spark.streaming.scheduler.StreamInputInfo
-
The key for description in StreamInputInfo.metadata.
- MetadataBuilder - Class in org.apache.spark.sql.types
-
:: DeveloperApi ::
- MetadataBuilder() - Constructor for class org.apache.spark.sql.types.MetadataBuilder
-
- metadataDescription() - Method in class org.apache.spark.streaming.scheduler.StreamInputInfo
-
- MetadataUtils - Class in org.apache.spark.ml.util
-
Helper utilities for algorithms using ML metadata
- MetadataUtils() - Constructor for class org.apache.spark.ml.util.MetadataUtils
-
- method() - Method in class org.apache.spark.mllib.stat.test.ChiSqTestResult
-
- MethodIdentifier<T> - Class in org.apache.spark.util
-
Helper class to identify a method.
- MethodIdentifier(Class<T>, String, String) - Constructor for class org.apache.spark.util.MethodIdentifier
-
- methodName() - Static method in class org.apache.spark.mllib.stat.test.StudentTTest
-
- methodName() - Static method in class org.apache.spark.mllib.stat.test.WelchTTest
-
- METRIC_COMPILATION_TIME() - Static method in class org.apache.spark.metrics.source.CodegenMetrics
-
Histogram of the time it took to compile source code text (in milliseconds).
- METRIC_GENERATED_CLASS_BYTECODE_SIZE() - Static method in class org.apache.spark.metrics.source.CodegenMetrics
-
Histogram of the bytecode size of each class generated by CodeGenerator.
- METRIC_GENERATED_METHOD_BYTECODE_SIZE() - Static method in class org.apache.spark.metrics.source.CodegenMetrics
-
Histogram of the bytecode size of each method in classes generated by CodeGenerator.
- METRIC_SOURCE_CODE_SIZE() - Static method in class org.apache.spark.metrics.source.CodegenMetrics
-
Histogram of the length of source code text compiled by CodeGenerator (in characters).
- metricName() - Method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
param for metric name in evaluation (supports "areaUnderROC" (default), "areaUnderPR")
- metricName() - Method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
param for metric name in evaluation (supports "f1" (default), "weightedPrecision",
"weightedRecall", "accuracy")
- metricName() - Method in class org.apache.spark.ml.evaluation.RegressionEvaluator
-
Param for metric name in evaluation.
- metricRegistry() - Static method in class org.apache.spark.metrics.source.CodegenMetrics
-
- metrics() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- metrics() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- metrics() - Method in class org.apache.spark.ui.jobs.UIData.TaskUIData
-
- METRICS_PREFIX() - Static method in class org.apache.spark.InternalAccumulator
-
- metricsSystem() - Method in class org.apache.spark.SparkEnv
-
- MFDataGenerator - Class in org.apache.spark.mllib.util
-
:: DeveloperApi ::
Generate RDD(s) containing data for Matrix Factorization.
- MFDataGenerator() - Constructor for class org.apache.spark.mllib.util.MFDataGenerator
-
- microF1Measure() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
-
Returns micro-averaged label-based f1-measure
(equals to micro-averaged document-based f1-measure)
- microPrecision() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
-
Returns micro-averaged label-based precision
(equals to micro-averaged document-based precision)
- microRecall() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
-
Returns micro-averaged label-based recall
(equals to micro-averaged document-based recall)
- mightContain(Object) - Method in class org.apache.spark.util.sketch.BloomFilter
-
Returns true if the element might have been put in this Bloom filter,
false if this is definitely not the case.
- mightContainBinary(byte[]) - Method in class org.apache.spark.util.sketch.BloomFilter
-
- mightContainLong(long) - Method in class org.apache.spark.util.sketch.BloomFilter
-
- mightContainString(String) - Method in class org.apache.spark.util.sketch.BloomFilter
-
- milliseconds() - Method in class org.apache.spark.streaming.Duration
-
- milliseconds(long) - Static method in class org.apache.spark.streaming.Durations
-
- Milliseconds - Class in org.apache.spark.streaming
-
Helper object that creates instance of
Duration representing
a given number of milliseconds.
- Milliseconds() - Constructor for class org.apache.spark.streaming.Milliseconds
-
- milliseconds() - Method in class org.apache.spark.streaming.Time
-
- millisToString(long) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
Reformat a time interval in milliseconds to a prettier format for output
- min() - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Returns the minimum element from this RDD as defined by
the default comparator natural order.
- min(Comparator<T>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- min(Comparator<T>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- min(Comparator<T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Returns the minimum element from this RDD as defined by the specified
Comparator[T].
- min(Ordering<T>) - Static method in class org.apache.spark.api.r.RRDD
-
- min(Ordering<T>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- min(Ordering<T>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- min(Ordering<T>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- min(Ordering<T>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- MIN() - Static method in class org.apache.spark.ml.attribute.AttributeKeys
-
- min() - Method in class org.apache.spark.ml.attribute.NumericAttribute
-
- min() - Static method in class org.apache.spark.ml.feature.MinMaxScaler
-
- min() - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- min() - Method in class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
-
Minimum value of each dimension.
- min() - Method in interface org.apache.spark.mllib.stat.MultivariateStatisticalSummary
-
Minimum value of each column.
- min(Ordering<T>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- min(Ordering<T>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- min(Ordering<T>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- min(Ordering<T>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- min(Ordering<T>) - Method in class org.apache.spark.rdd.RDD
-
Returns the min of this RDD as defined by the implicit Ordering[T].
- min(Ordering<T>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- min(Column) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the minimum value of the expression in a group.
- min(String) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the minimum value of the column in a group.
- min(String...) - Method in class org.apache.spark.sql.RelationalGroupedDataset
-
Compute the min value for each numeric column for each group.
- min(Seq<String>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
-
Compute the min value for each numeric column for each group.
- min(Ordering<B>) - Static method in class org.apache.spark.sql.types.StructType
-
- min(Duration) - Method in class org.apache.spark.streaming.Duration
-
- min(Time) - Method in class org.apache.spark.streaming.Time
-
- min() - Method in class org.apache.spark.util.StatCounter
-
- minBy(Function1<A, B>, Ordering<B>) - Static method in class org.apache.spark.sql.types.StructType
-
- minCount() - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- minCount() - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- minDF() - Static method in class org.apache.spark.ml.feature.CountVectorizer
-
- minDF() - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- minDivisibleClusterSize() - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- minDivisibleClusterSize() - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- minDocFreq() - Static method in class org.apache.spark.ml.feature.IDF
-
- minDocFreq() - Static method in class org.apache.spark.ml.feature.IDFModel
-
- minDocFreq() - Method in class org.apache.spark.mllib.feature.IDF.DocumentFrequencyAggregator
-
- minDocFreq() - Method in class org.apache.spark.mllib.feature.IDF
-
- minInfoGain() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- minInfoGain() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- minInfoGain() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- minInfoGain() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- minInfoGain() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- minInfoGain() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- minInfoGain() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- minInfoGain() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- minInfoGain() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- minInfoGain() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- minInfoGain() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- minInfoGain() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- minInfoGain() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- minInstancesPerNode() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- minInstancesPerNode() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- minInstancesPerNode() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- minInstancesPerNode() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- minInstancesPerNode() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- minInstancesPerNode() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- minInstancesPerNode() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- minInstancesPerNode() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- minInstancesPerNode() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- minInstancesPerNode() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- minInstancesPerNode() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- minInstancesPerNode() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- minInstancesPerNode() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- MinMax() - Static method in class org.apache.spark.mllib.tree.configuration.QuantileStrategy
-
- MinMaxScaler - Class in org.apache.spark.ml.feature
-
Rescale each feature individually to a common range [min, max] linearly using column summary
statistics, which is also known as min-max normalization or Rescaling.
- MinMaxScaler(String) - Constructor for class org.apache.spark.ml.feature.MinMaxScaler
-
- MinMaxScaler() - Constructor for class org.apache.spark.ml.feature.MinMaxScaler
-
- MinMaxScalerModel - Class in org.apache.spark.ml.feature
-
- minorVersion(String) - Static method in class org.apache.spark.util.VersionUtils
-
Given a Spark version string, return the minor version number.
- minSamplingRate() - Static method in class org.apache.spark.util.random.BinomialBounds
-
- minTF() - Static method in class org.apache.spark.ml.feature.CountVectorizer
-
- minTF() - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- minTokenLength() - Method in class org.apache.spark.ml.feature.RegexTokenizer
-
Minimum token length, >= 0.
- minus(RDD<Tuple2<Object, VD>>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- minus(VertexRDD<VD>) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- minus(RDD<Tuple2<Object, VD>>) - Method in class org.apache.spark.graphx.VertexRDD
-
For each VertexId present in both this and other, minus will act as a set difference
operation returning only those unique VertexId's present in this.
- minus(VertexRDD<VD>) - Method in class org.apache.spark.graphx.VertexRDD
-
For each VertexId present in both this and other, minus will act as a set difference
operation returning only those unique VertexId's present in this.
- minus(Object) - Method in class org.apache.spark.sql.Column
-
Subtraction.
- minus(Duration) - Method in class org.apache.spark.streaming.Duration
-
- minus(Time) - Method in class org.apache.spark.streaming.Time
-
- minus(Duration) - Method in class org.apache.spark.streaming.Time
-
- minute(Column) - Static method in class org.apache.spark.sql.functions
-
Extracts the minutes as an integer from a given date/timestamp/string.
- minutes() - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- minutes(long) - Static method in class org.apache.spark.streaming.Durations
-
- Minutes - Class in org.apache.spark.streaming
-
Helper object that creates instance of
Duration representing
a given number of minutes.
- Minutes() - Constructor for class org.apache.spark.streaming.Minutes
-
- minVal() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
-
- missingInput() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- missingInput() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- missingInput() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- mkList() - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- mkString() - Method in interface org.apache.spark.sql.Row
-
Displays all elements of this sequence in a string (without a separator).
- mkString(String) - Method in interface org.apache.spark.sql.Row
-
Displays all elements of this sequence in a string using a separator string.
- mkString(String, String, String) - Method in interface org.apache.spark.sql.Row
-
Displays all elements of this traversable or iterator in a string using
start, end, and separator strings.
- mkString(String, String, String) - Static method in class org.apache.spark.sql.types.StructType
-
- mkString(String) - Static method in class org.apache.spark.sql.types.StructType
-
- mkString() - Static method in class org.apache.spark.sql.types.StructType
-
- ML_ATTR() - Static method in class org.apache.spark.ml.attribute.AttributeKeys
-
- mlDenseMatrixToMLlibDenseMatrix(DenseMatrix) - Static method in class org.apache.spark.mllib.linalg.MatrixImplicits
-
- mlDenseVectorToMLlibDenseVector(DenseVector) - Static method in class org.apache.spark.mllib.linalg.VectorImplicits
-
- mllibDenseMatrixToMLDenseMatrix(DenseMatrix) - Static method in class org.apache.spark.mllib.linalg.MatrixImplicits
-
- mllibDenseVectorToMLDenseVector(DenseVector) - Static method in class org.apache.spark.mllib.linalg.VectorImplicits
-
- mllibMatrixToMLMatrix(Matrix) - Static method in class org.apache.spark.mllib.linalg.MatrixImplicits
-
- mllibSparseMatrixToMLSparseMatrix(SparseMatrix) - Static method in class org.apache.spark.mllib.linalg.MatrixImplicits
-
- mllibSparseVectorToMLSparseVector(SparseVector) - Static method in class org.apache.spark.mllib.linalg.VectorImplicits
-
- mllibVectorToMLVector(Vector) - Static method in class org.apache.spark.mllib.linalg.VectorImplicits
-
- mlMatrixToMLlibMatrix(Matrix) - Static method in class org.apache.spark.mllib.linalg.MatrixImplicits
-
- MLPairRDDFunctions<K,V> - Class in org.apache.spark.mllib.rdd
-
:: DeveloperApi ::
Machine learning specific Pair RDD functions.
- MLPairRDDFunctions(RDD<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>) - Constructor for class org.apache.spark.mllib.rdd.MLPairRDDFunctions
-
- MLReadable<T> - Interface in org.apache.spark.ml.util
-
:: Experimental ::
- MLReader<T> - Class in org.apache.spark.ml.util
-
:: Experimental ::
- MLReader() - Constructor for class org.apache.spark.ml.util.MLReader
-
- mlSparseMatrixToMLlibSparseMatrix(SparseMatrix) - Static method in class org.apache.spark.mllib.linalg.MatrixImplicits
-
- mlSparseVectorToMLlibSparseVector(SparseVector) - Static method in class org.apache.spark.mllib.linalg.VectorImplicits
-
- MLUtils - Class in org.apache.spark.mllib.util
-
Helper methods to load, save and pre-process data used in ML Lib.
- MLUtils() - Constructor for class org.apache.spark.mllib.util.MLUtils
-
- mlVectorToMLlibVector(Vector) - Static method in class org.apache.spark.mllib.linalg.VectorImplicits
-
- MLWritable - Interface in org.apache.spark.ml.util
-
:: Experimental ::
- MLWriter - Class in org.apache.spark.ml.util
-
:: Experimental ::
- MLWriter() - Constructor for class org.apache.spark.ml.util.MLWriter
-
- mod(Object) - Method in class org.apache.spark.sql.Column
-
Modulo (a.k.a.
- mode(SaveMode) - Method in class org.apache.spark.sql.DataFrameWriter
-
Specifies the behavior when data or table already exists.
- mode(String) - Method in class org.apache.spark.sql.DataFrameWriter
-
Specifies the behavior when data or table already exists.
- Model<M extends Model<M>> - Class in org.apache.spark.ml
-
- Model() - Constructor for class org.apache.spark.ml.Model
-
- model() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
-
Deprecated.
The model field is deprecated and will be removed in 2.1.0. Since 2.0.0.
- models() - Method in class org.apache.spark.ml.classification.OneVsRestModel
-
- modelType() - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- modelType() - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- modelType() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel
-
- modelType() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$.Data
-
- MODULE$ - Static variable in class org.apache.spark.AccumulatorParam.DoubleAccumulatorParam$
-
Deprecated.
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.AccumulatorParam.FloatAccumulatorParam$
-
Deprecated.
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.AccumulatorParam.IntAccumulatorParam$
-
Deprecated.
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.AccumulatorParam.LongAccumulatorParam$
-
Deprecated.
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.AccumulatorParam.StringAccumulatorParam$
-
Deprecated.
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.graphx.PartitionStrategy.CanonicalRandomVertexCut$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.graphx.PartitionStrategy.EdgePartition1D$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.graphx.PartitionStrategy.EdgePartition2D$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.graphx.PartitionStrategy.RandomVertexCut$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.InternalAccumulator.input$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.InternalAccumulator.output$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.InternalAccumulator.shuffleRead$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.InternalAccumulator.shuffleWrite$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ml.Pipeline.SharedReadWrite$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ml.recommendation.ALS.InBlock$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ml.recommendation.ALS.Rating$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ml.recommendation.ALS.RatingBlock$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Binomial$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.CLogLog$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Family$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gamma$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gaussian$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Identity$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Inverse$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Link$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Log$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Logit$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Poisson$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Probit$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Sqrt$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.SplitData$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ml.tree.EnsembleModelReadWrite.EnsembleNodeData$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.mllib.classification.impl.GLMClassificationModel.SaveLoadV1_0$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.mllib.clustering.BisectingKMeansModel.SaveLoadV1_0$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.mllib.clustering.KMeansModel.SaveLoadV1_0$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.mllib.clustering.PowerIterationClustering.Assignment$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.mllib.clustering.PowerIterationClusteringModel.SaveLoadV1_0$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.mllib.feature.ChiSqSelectorModel.SaveLoadV1_0$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.mllib.fpm.FPGrowthModel.SaveLoadV1_0$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.mllib.fpm.PrefixSpan.Postfix$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.mllib.fpm.PrefixSpan.Prefix$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.mllib.fpm.PrefixSpanModel.SaveLoadV1_0$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel.SaveLoadV1_0$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.mllib.regression.impl.GLMRegressionModel.SaveLoadV1_0$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.mllib.stat.test.ChiSqTest.Method$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.mllib.stat.test.ChiSqTest.NullHypothesis$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.mllib.stat.test.KolmogorovSmirnovTest.NullHypothesis$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.rdd.HadoopRDD.HadoopMapPartitionsWithSplitRDD$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.rdd.NewHadoopRDD.NewHadoopMapPartitionsWithSplitRDD$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.AddWebUIFilter$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.GetExecutorLossReason$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillExecutors$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.KillTask$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.LaunchTask$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterClusterManager$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisteredExecutor$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutor$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutorFailed$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RemoveExecutor$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RequestExecutors$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RetrieveLastAllocatedExecutorId$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RetrieveSparkProps$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.ReviveOffers$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.SetupDriver$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.Shutdown$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StatusUpdate$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StopDriver$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StopExecutor$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.StopExecutors$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.serializer.SerializationDebugger.ObjectStreamClassMethods$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.sql.hive.HiveShim.HiveFunctionWrapper$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.sql.InternalOutputModes.Append$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.sql.InternalOutputModes.Complete$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.sql.InternalOutputModes.Update$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.sql.RelationalGroupedDataset.CubeType$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.sql.RelationalGroupedDataset.GroupByType$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.sql.RelationalGroupedDataset.PivotType$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.sql.RelationalGroupedDataset.RollupType$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.sql.types.Decimal.DecimalAsIfIntegral$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.sql.types.Decimal.DecimalIsFractional$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.sql.types.DecimalType.Expression$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.sql.types.DecimalType.Fixed$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.BlockManagerHeartbeat$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetBlockStatus$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetExecutorEndpointRef$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetLocations$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetLocationsMultipleBlockIds$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetMatchingBlockIds$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetMemoryStatus$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetPeers$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.GetStorageStatus$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.HasCachedBlocks$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.RegisterBlockManager$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.RemoveBlock$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.RemoveBroadcast$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.RemoveExecutor$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.RemoveRdd$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.RemoveShuffle$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.StopBlockManagerMaster$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.TriggerThreadDump$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.storage.BlockManagerMessages.UpdateBlockInfo$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.streaming.kafka.KafkaCluster.LeaderOffset$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.streaming.kafka.KafkaCluster.SimpleConsumerConfig$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ui.JettyUtils.ServletParams$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ui.jobs.UIData.ExecutorUIData$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ui.jobs.UIData.InputMetricsUIData$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ui.jobs.UIData.JobUIData$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ui.jobs.UIData.OutputMetricsUIData$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ui.jobs.UIData.ShuffleReadMetricsUIData$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ui.jobs.UIData.ShuffleWriteMetricsUIData$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ui.jobs.UIData.TaskMetricsUIData$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ui.jobs.UIData.TaskUIData$
-
Static reference to the singleton instance of this Scala object.
- monotonically_increasing_id() - Static method in class org.apache.spark.sql.functions
-
A column expression that generates monotonically increasing 64-bit integers.
- monotonicallyIncreasingId() - Static method in class org.apache.spark.sql.functions
-
Deprecated.
Use monotonically_increasing_id(). Since 2.0.0.
- month(Column) - Static method in class org.apache.spark.sql.functions
-
Extracts the month as an integer from a given date/timestamp/string.
- months_between(Column, Column) - Static method in class org.apache.spark.sql.functions
-
Returns number of months between dates date1 and date2.
- msDurationToString(long) - Static method in class org.apache.spark.util.Utils
-
Returns a human-readable string representing a duration such as "35ms"
- MsSqlServerDialect - Class in org.apache.spark.sql.jdbc
-
- MsSqlServerDialect() - Constructor for class org.apache.spark.sql.jdbc.MsSqlServerDialect
-
- mu() - Method in class org.apache.spark.mllib.stat.distribution.MultivariateGaussian
-
- MulticlassClassificationEvaluator - Class in org.apache.spark.ml.evaluation
-
:: Experimental ::
Evaluator for multiclass classification, which expects two input columns: prediction and label.
- MulticlassClassificationEvaluator(String) - Constructor for class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
- MulticlassClassificationEvaluator() - Constructor for class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
- MulticlassMetrics - Class in org.apache.spark.mllib.evaluation
-
Evaluator for multiclass classification.
- MulticlassMetrics(RDD<Tuple2<Object, Object>>) - Constructor for class org.apache.spark.mllib.evaluation.MulticlassMetrics
-
- MultilabelMetrics - Class in org.apache.spark.mllib.evaluation
-
Evaluator for multilabel classification.
- MultilabelMetrics(RDD<Tuple2<double[], double[]>>) - Constructor for class org.apache.spark.mllib.evaluation.MultilabelMetrics
-
- multiLabelValidator(int) - Static method in class org.apache.spark.mllib.util.DataValidators
-
Function to check if labels used for k class multi-label classification are
in the range of {0, 1, ..., k - 1}.
- MultilayerPerceptronClassificationModel - Class in org.apache.spark.ml.classification
-
:: Experimental ::
Classification model based on the Multilayer Perceptron.
- MultilayerPerceptronClassifier - Class in org.apache.spark.ml.classification
-
:: Experimental ::
Classifier trainer based on the Multilayer Perceptron.
- MultilayerPerceptronClassifier(String) - Constructor for class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- MultilayerPerceptronClassifier() - Constructor for class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- multiply(DenseMatrix) - Static method in class org.apache.spark.ml.linalg.DenseMatrix
-
- multiply(DenseVector) - Static method in class org.apache.spark.ml.linalg.DenseMatrix
-
- multiply(Vector) - Static method in class org.apache.spark.ml.linalg.DenseMatrix
-
- multiply(DenseMatrix) - Method in interface org.apache.spark.ml.linalg.Matrix
-
Convenience method for `Matrix`-`DenseMatrix` multiplication.
- multiply(DenseVector) - Method in interface org.apache.spark.ml.linalg.Matrix
-
Convenience method for `Matrix`-`DenseVector` multiplication.
- multiply(Vector) - Method in interface org.apache.spark.ml.linalg.Matrix
-
Convenience method for `Matrix`-`Vector` multiplication.
- multiply(DenseMatrix) - Static method in class org.apache.spark.ml.linalg.SparseMatrix
-
- multiply(DenseVector) - Static method in class org.apache.spark.ml.linalg.SparseMatrix
-
- multiply(Vector) - Static method in class org.apache.spark.ml.linalg.SparseMatrix
-
- multiply(DenseMatrix) - Static method in class org.apache.spark.mllib.linalg.DenseMatrix
-
- multiply(DenseVector) - Static method in class org.apache.spark.mllib.linalg.DenseMatrix
-
- multiply(Vector) - Static method in class org.apache.spark.mllib.linalg.DenseMatrix
-
- multiply(BlockMatrix) - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
-
- multiply(Matrix) - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
-
Multiply this matrix by a local matrix on the right.
- multiply(Matrix) - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
-
Multiply this matrix by a local matrix on the right.
- multiply(DenseMatrix) - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Convenience method for `Matrix`-`DenseMatrix` multiplication.
- multiply(DenseVector) - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Convenience method for `Matrix`-`DenseVector` multiplication.
- multiply(Vector) - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Convenience method for `Matrix`-`Vector` multiplication.
- multiply(DenseMatrix) - Static method in class org.apache.spark.mllib.linalg.SparseMatrix
-
- multiply(DenseVector) - Static method in class org.apache.spark.mllib.linalg.SparseMatrix
-
- multiply(Vector) - Static method in class org.apache.spark.mllib.linalg.SparseMatrix
-
- multiply(Object) - Method in class org.apache.spark.sql.Column
-
Multiplication of this expression and another expression.
- MultivariateGaussian - Class in org.apache.spark.ml.stat.distribution
-
This class provides basic functionality for a Multivariate Gaussian (Normal) Distribution.
- MultivariateGaussian(Vector, Matrix) - Constructor for class org.apache.spark.ml.stat.distribution.MultivariateGaussian
-
- MultivariateGaussian - Class in org.apache.spark.mllib.stat.distribution
-
:: DeveloperApi ::
This class provides basic functionality for a Multivariate Gaussian (Normal) Distribution.
- MultivariateGaussian(Vector, Matrix) - Constructor for class org.apache.spark.mllib.stat.distribution.MultivariateGaussian
-
- MultivariateOnlineSummarizer - Class in org.apache.spark.mllib.stat
-
:: DeveloperApi ::
MultivariateOnlineSummarizer implements
MultivariateStatisticalSummary to compute the mean,
variance, minimum, maximum, counts, and nonzero counts for instances in sparse or dense vector
format in an online fashion.
- MultivariateOnlineSummarizer() - Constructor for class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
-
- MultivariateStatisticalSummary - Interface in org.apache.spark.mllib.stat
-
Trait for multivariate statistical summary of a data matrix.
- MutableAggregationBuffer - Class in org.apache.spark.sql.expressions
-
:: Experimental ::
A Row representing a mutable aggregation buffer.
- MutableAggregationBuffer() - Constructor for class org.apache.spark.sql.expressions.MutableAggregationBuffer
-
- MutablePair<T1,T2> - Class in org.apache.spark.util
-
:: DeveloperApi ::
A tuple of 2 elements.
- MutablePair(T1, T2) - Constructor for class org.apache.spark.util.MutablePair
-
- MutablePair() - Constructor for class org.apache.spark.util.MutablePair
-
No-arg constructor for serialization
- myName() - Method in class org.apache.spark.util.InnerClosureFinder
-
- MySQLDialect - Class in org.apache.spark.sql.jdbc
-
- MySQLDialect() - Constructor for class org.apache.spark.sql.jdbc.MySQLDialect
-
- n() - Method in class org.apache.spark.ml.feature.NGram
-
Minimum n-gram length, >= 1.
- n() - Method in class org.apache.spark.mllib.optimization.NNLS.Workspace
-
- na() - Method in class org.apache.spark.sql.Dataset
-
- NaiveBayes - Class in org.apache.spark.ml.classification
-
Naive Bayes Classifiers.
- NaiveBayes(String) - Constructor for class org.apache.spark.ml.classification.NaiveBayes
-
- NaiveBayes() - Constructor for class org.apache.spark.ml.classification.NaiveBayes
-
- NaiveBayes - Class in org.apache.spark.mllib.classification
-
Trains a Naive Bayes model given an RDD of (label, features) pairs.
- NaiveBayes(double) - Constructor for class org.apache.spark.mllib.classification.NaiveBayes
-
- NaiveBayes() - Constructor for class org.apache.spark.mllib.classification.NaiveBayes
-
- NaiveBayesModel - Class in org.apache.spark.ml.classification
-
Model produced by
NaiveBayes
param: pi log of class priors, whose dimension is C (number of classes)
param: theta log of class conditional probabilities, whose dimension is C (number of classes)
by D (number of features)
- NaiveBayesModel - Class in org.apache.spark.mllib.classification
-
Model for Naive Bayes Classifiers.
- NaiveBayesModel.SaveLoadV1_0$ - Class in org.apache.spark.mllib.classification
-
- NaiveBayesModel.SaveLoadV1_0$() - Constructor for class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0$
-
- NaiveBayesModel.SaveLoadV1_0$.Data - Class in org.apache.spark.mllib.classification
-
Model data for model import/export
- NaiveBayesModel.SaveLoadV1_0$.Data(double[], double[], double[][]) - Constructor for class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0$.Data
-
- NaiveBayesModel.SaveLoadV2_0$ - Class in org.apache.spark.mllib.classification
-
- NaiveBayesModel.SaveLoadV2_0$() - Constructor for class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$
-
- NaiveBayesModel.SaveLoadV2_0$.Data - Class in org.apache.spark.mllib.classification
-
Model data for model import/export
- NaiveBayesModel.SaveLoadV2_0$.Data(double[], double[], double[][], String) - Constructor for class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$.Data
-
- name() - Method in class org.apache.spark.Accumulable
-
Deprecated.
- name() - Static method in class org.apache.spark.Accumulator
-
Deprecated.
- name() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- name() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- name() - Static method in class org.apache.spark.api.java.JavaRDD
-
- name() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
- name() - Static method in class org.apache.spark.api.r.RRDD
-
- name() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- name() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- name() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- name() - Static method in class org.apache.spark.graphx.VertexRDD
-
- name() - Method in class org.apache.spark.ml.attribute.Attribute
-
Name of the attribute.
- name() - Method in class org.apache.spark.ml.attribute.AttributeGroup
-
- NAME() - Static method in class org.apache.spark.ml.attribute.AttributeKeys
-
- name() - Method in class org.apache.spark.ml.attribute.AttributeType
-
- name() - Method in class org.apache.spark.ml.attribute.BinaryAttribute
-
- name() - Method in class org.apache.spark.ml.attribute.NominalAttribute
-
- name() - Method in class org.apache.spark.ml.attribute.NumericAttribute
-
- name() - Static method in class org.apache.spark.ml.attribute.UnresolvedAttribute
-
- name() - Static method in class org.apache.spark.ml.param.DoubleParam
-
- name() - Static method in class org.apache.spark.ml.param.FloatParam
-
- name() - Method in class org.apache.spark.ml.param.Param
-
- name() - Method in class org.apache.spark.mllib.stat.test.ChiSqTest.Method
-
- name() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- name() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- name() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- name() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- name() - Method in class org.apache.spark.rdd.RDD
-
A friendly name for this RDD
- name() - Static method in class org.apache.spark.rdd.UnionRDD
-
- name() - Method in class org.apache.spark.scheduler.AccumulableInfo
-
- name() - Method in class org.apache.spark.scheduler.StageInfo
-
- name() - Method in interface org.apache.spark.SparkStageInfo
-
- name() - Method in class org.apache.spark.SparkStageInfoImpl
-
- name() - Method in class org.apache.spark.sql.catalog.Column
-
- name() - Method in class org.apache.spark.sql.catalog.Database
-
- name() - Method in class org.apache.spark.sql.catalog.Function
-
- name() - Method in class org.apache.spark.sql.catalog.Table
-
- name(String) - Method in class org.apache.spark.sql.Column
-
Gives the column a name (alias).
- name() - Method in interface org.apache.spark.sql.streaming.StreamingQuery
-
Returns the name of the query.
- name() - Method in class org.apache.spark.sql.streaming.StreamingQueryInfo
-
- name(String) - Method in class org.apache.spark.sql.TypedColumn
-
Gives the TypedColumn a name (alias).
- name() - Method in class org.apache.spark.sql.types.StructField
-
- name() - Method in class org.apache.spark.status.api.v1.AccumulableInfo
-
- name() - Method in class org.apache.spark.status.api.v1.ApplicationInfo
-
- name() - Method in class org.apache.spark.status.api.v1.JobData
-
- name() - Method in class org.apache.spark.status.api.v1.RDDStorageInfo
-
- name() - Method in class org.apache.spark.status.api.v1.StageData
-
- name() - Method in class org.apache.spark.storage.BlockId
-
A globally unique identifier for this Block.
- name() - Method in class org.apache.spark.storage.BroadcastBlockId
-
- name() - Method in class org.apache.spark.storage.RDDBlockId
-
- name() - Method in class org.apache.spark.storage.RDDInfo
-
- name() - Method in class org.apache.spark.storage.ShuffleBlockId
-
- name() - Method in class org.apache.spark.storage.ShuffleDataBlockId
-
- name() - Method in class org.apache.spark.storage.ShuffleIndexBlockId
-
- name() - Method in class org.apache.spark.storage.StreamBlockId
-
- name() - Method in class org.apache.spark.storage.TaskResultBlockId
-
- name() - Method in class org.apache.spark.streaming.scheduler.OutputOperationInfo
-
- name() - Method in class org.apache.spark.streaming.scheduler.ReceiverInfo
-
- name() - Method in class org.apache.spark.util.AccumulatorV2
-
Returns the name of this accumulator, can only be called after registration.
- name() - Method in class org.apache.spark.util.MethodIdentifier
-
- name_$eq(String) - Static method in class org.apache.spark.api.r.RRDD
-
- name_$eq(String) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- name_$eq(String) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- name_$eq(String) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- name_$eq(String) - Static method in class org.apache.spark.graphx.VertexRDD
-
- name_$eq(String) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- name_$eq(String) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- name_$eq(String) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- name_$eq(String) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- name_$eq(String) - Static method in class org.apache.spark.rdd.UnionRDD
-
- namedThreadFactory(String) - Static method in class org.apache.spark.util.ThreadUtils
-
Create a thread factory that names threads with a prefix and also sets the threads to daemon.
- names() - Method in class org.apache.spark.ml.feature.VectorSlicer
-
An array of feature names to select features from a vector column.
- nameToObjectMap() - Static method in class org.apache.spark.mllib.stat.correlation.CorrelationNames
-
- nanSafeCompareDoubles(double, double) - Static method in class org.apache.spark.util.Utils
-
NaN-safe version of java.lang.Double.compare() which allows NaN values to be compared
according to semantics where NaN == NaN and NaN > any non-NaN double.
- nanSafeCompareFloats(float, float) - Static method in class org.apache.spark.util.Utils
-
NaN-safe version of java.lang.Float.compare() which allows NaN values to be compared
according to semantics where NaN == NaN and NaN > any non-NaN float.
- nanvl(Column, Column) - Static method in class org.apache.spark.sql.functions
-
Returns col1 if it is not NaN, or col2 if col1 is NaN.
- NarrowDependency<T> - Class in org.apache.spark
-
:: DeveloperApi ::
Base class for dependencies where each partition of the child RDD depends on a small number
of partitions of the parent RDD.
- NarrowDependency(RDD<T>) - Constructor for class org.apache.spark.NarrowDependency
-
- ndcgAt(int) - Method in class org.apache.spark.mllib.evaluation.RankingMetrics
-
Compute the average NDCG value of all the queries, truncated at ranking position k.
- needConversion() - Method in class org.apache.spark.sql.sources.BaseRelation
-
Whether does it need to convert the objects in Row to internal representation, for example:
java.lang.String -> UTF8String
java.lang.Decimal -> Decimal
- negate(Column) - Static method in class org.apache.spark.sql.functions
-
Unary minus, i.e.
- newAPIHadoopFile(String, Class<F>, Class<K>, Class<V>, Configuration) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Get an RDD for a given Hadoop file with an arbitrary new API InputFormat
and extra configuration options to pass to the input format.
- newAPIHadoopFile(String, ClassTag<K>, ClassTag<V>, ClassTag<F>) - Method in class org.apache.spark.SparkContext
-
Get an RDD for a Hadoop file with an arbitrary new API InputFormat.
- newAPIHadoopFile(String, Class<F>, Class<K>, Class<V>, Configuration) - Method in class org.apache.spark.SparkContext
-
Get an RDD for a given Hadoop file with an arbitrary new API InputFormat
and extra configuration options to pass to the input format.
- newAPIHadoopRDD(Configuration, Class<F>, Class<K>, Class<V>) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Get an RDD for a given Hadoop file with an arbitrary new API InputFormat
and extra configuration options to pass to the input format.
- newAPIHadoopRDD(Configuration, Class<F>, Class<K>, Class<V>) - Method in class org.apache.spark.SparkContext
-
Get an RDD for a given Hadoop file with an arbitrary new API InputFormat
and extra configuration options to pass to the input format.
- newBooleanArrayEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newBooleanEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newBooleanSeqEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newBoxedBooleanEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newBoxedByteEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newBoxedDoubleEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newBoxedFloatEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newBoxedIntEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newBoxedLongEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newBoxedShortEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newByteArrayEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newByteEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newByteSeqEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newDaemonCachedThreadPool(String) - Static method in class org.apache.spark.util.ThreadUtils
-
Wrapper over newCachedThreadPool.
- newDaemonCachedThreadPool(String, int, int) - Static method in class org.apache.spark.util.ThreadUtils
-
Create a cached thread pool whose max number of threads is maxThreadNumber.
- newDaemonFixedThreadPool(int, String) - Static method in class org.apache.spark.util.ThreadUtils
-
Wrapper over newFixedThreadPool.
- newDaemonSingleThreadExecutor(String) - Static method in class org.apache.spark.util.ThreadUtils
-
Wrapper over newSingleThreadExecutor.
- newDaemonSingleThreadScheduledExecutor(String) - Static method in class org.apache.spark.util.ThreadUtils
-
Wrapper over ScheduledThreadPoolExecutor.
- newDoubleArrayEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newDoubleEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newDoubleSeqEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newFloatArrayEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newFloatEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newFloatSeqEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newForkJoinPool(String, int) - Static method in class org.apache.spark.util.ThreadUtils
-
Construct a new Scala ForkJoinPool with a specified max parallelism and name prefix.
- NewHadoopRDD<K,V> - Class in org.apache.spark.rdd
-
:: DeveloperApi ::
An RDD that provides core functionality for reading data stored in Hadoop (e.g., files in HDFS,
sources in HBase, or S3), using the new MapReduce API (org.apache.hadoop.mapreduce).
- NewHadoopRDD(SparkContext, Class<? extends InputFormat<K, V>>, Class<K>, Class<V>, Configuration) - Constructor for class org.apache.spark.rdd.NewHadoopRDD
-
- NewHadoopRDD.NewHadoopMapPartitionsWithSplitRDD$ - Class in org.apache.spark.rdd
-
- NewHadoopRDD.NewHadoopMapPartitionsWithSplitRDD$() - Constructor for class org.apache.spark.rdd.NewHadoopRDD.NewHadoopMapPartitionsWithSplitRDD$
-
- newId() - Static method in class org.apache.spark.util.AccumulatorContext
-
- newInstance() - Method in class org.apache.spark.serializer.JavaSerializer
-
- newInstance() - Method in class org.apache.spark.serializer.KryoSerializer
-
- newInstance() - Method in class org.apache.spark.serializer.Serializer
-
- newIntArrayEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newIntEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newIntSeqEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newKryo() - Method in class org.apache.spark.serializer.KryoSerializer
-
- newKryoOutput() - Method in class org.apache.spark.serializer.KryoSerializer
-
- newLongArrayEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newLongEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newLongSeqEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newProductArrayEncoder(TypeTags.TypeTag<A>) - Method in class org.apache.spark.sql.SQLImplicits
-
- newProductEncoder(TypeTags.TypeTag<T>) - Method in class org.apache.spark.sql.SQLImplicits
-
- newProductSeqEncoder(TypeTags.TypeTag<A>) - Method in class org.apache.spark.sql.SQLImplicits
-
- newSession() - Method in class org.apache.spark.sql.hive.HiveContext
-
Deprecated.
Returns a new HiveContext as new session, which will have separated SQLConf, UDF/UDAF,
temporary tables and SessionState, but sharing the same CacheManager, IsolatedClientLoader
and Hive client (both of execution and metadata) with existing HiveContext.
- newSession() - Method in class org.apache.spark.sql.SparkSession
-
Start a new session with isolated SQL configurations, temporary tables, registered
functions are isolated, but sharing the underlying SparkContext and cached data.
- newSession() - Method in class org.apache.spark.sql.SQLContext
-
Returns a
SQLContext as new session, with separated SQL configurations, temporary
tables, registered functions, but sharing the same
SparkContext, cached data and
other things.
- newShortArrayEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newShortEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newShortSeqEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newStringArrayEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newStringEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newStringSeqEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newTemporaryConfiguration(boolean) - Static method in class org.apache.spark.sql.hive.HiveUtils
-
Constructs a configuration for hive, where the metastore is located in a temp directory.
- next() - Method in class org.apache.spark.InterruptibleIterator
-
- next() - Method in interface org.apache.spark.mllib.clustering.LDAOptimizer
-
- next_day(Column, String) - Static method in class org.apache.spark.sql.functions
-
Given a date column, returns the first date which is later than the value of the date column
that is on the specified day of the week.
- nextValue() - Method in class org.apache.spark.mllib.random.ExponentialGenerator
-
- nextValue() - Method in class org.apache.spark.mllib.random.GammaGenerator
-
- nextValue() - Method in class org.apache.spark.mllib.random.LogNormalGenerator
-
- nextValue() - Method in class org.apache.spark.mllib.random.PoissonGenerator
-
- nextValue() - Method in interface org.apache.spark.mllib.random.RandomDataGenerator
-
Returns an i.i.d.
- nextValue() - Method in class org.apache.spark.mllib.random.StandardNormalGenerator
-
- nextValue() - Method in class org.apache.spark.mllib.random.UniformGenerator
-
- nextValue() - Method in class org.apache.spark.mllib.random.WeibullGenerator
-
- NGram - Class in org.apache.spark.ml.feature
-
A feature transformer that converts the input array of strings into an array of n-grams.
- NGram(String) - Constructor for class org.apache.spark.ml.feature.NGram
-
- NGram() - Constructor for class org.apache.spark.ml.feature.NGram
-
- NNLS - Class in org.apache.spark.mllib.optimization
-
Object used to solve nonnegative least squares problems using a modified
projected gradient method.
- NNLS() - Constructor for class org.apache.spark.mllib.optimization.NNLS
-
- NNLS.Workspace - Class in org.apache.spark.mllib.optimization
-
- NNLS.Workspace(int) - Constructor for class org.apache.spark.mllib.optimization.NNLS.Workspace
-
- NO_PREF() - Static method in class org.apache.spark.scheduler.TaskLocality
-
- NO_RESOURCE - Static variable in class org.apache.spark.launcher.SparkLauncher
-
A special value for the resource that tells Spark to not try to process the app resource as a
file.
- Node - Class in org.apache.spark.ml.tree
-
Decision tree node interface.
- Node() - Constructor for class org.apache.spark.ml.tree.Node
-
- Node - Class in org.apache.spark.mllib.tree.model
-
:: DeveloperApi ::
Node in a decision tree.
- Node(int, Predict, double, boolean, Option<Split>, Option<Node>, Option<Node>, Option<InformationGainStats>) - Constructor for class org.apache.spark.mllib.tree.model.Node
-
- NODE_LOCAL() - Static method in class org.apache.spark.scheduler.TaskLocality
-
- nodeData() - Method in class org.apache.spark.ml.tree.EnsembleModelReadWrite.EnsembleNodeData
-
- nodeId() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData
-
- nodeName() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- nodeName() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- nodeName() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- noLocality() - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
-
- Nominal() - Static method in class org.apache.spark.ml.attribute.AttributeType
-
Nominal type.
- NominalAttribute - Class in org.apache.spark.ml.attribute
-
:: DeveloperApi ::
A nominal attribute.
- NONE - Static variable in class org.apache.spark.api.java.StorageLevels
-
- None - Static variable in class org.apache.spark.graphx.TripletFields
-
None of the triplet fields are exposed.
- NONE() - Static method in class org.apache.spark.scheduler.SchedulingMode
-
- NONE() - Static method in class org.apache.spark.storage.StorageLevel
-
- nonEmpty() - Static method in class org.apache.spark.sql.types.StructType
-
- nonLocalPaths(String, boolean) - Static method in class org.apache.spark.util.Utils
-
Return all non-local paths from a comma-separated list of paths.
- nonnegative() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- nonNegativeHash(Object) - Static method in class org.apache.spark.util.Utils
-
- nonNegativeMod(int, int) - Static method in class org.apache.spark.util.Utils
-
- NoopDialect - Class in org.apache.spark.sql.jdbc
-
NOOP dialect object, always returning the neutral element.
- NoopDialect() - Constructor for class org.apache.spark.sql.jdbc.NoopDialect
-
- norm(Vector, double) - Static method in class org.apache.spark.ml.linalg.Vectors
-
Returns the p-norm of this vector.
- norm(Vector, double) - Static method in class org.apache.spark.mllib.linalg.Vectors
-
Returns the p-norm of this vector.
- normalizeDuration(long) - Static method in class org.apache.spark.streaming.ui.UIUtils
-
Find the best TimeUnit for converting milliseconds to a friendly string.
- Normalizer - Class in org.apache.spark.ml.feature
-
Normalize a vector to have unit norm using the given p-norm.
- Normalizer(String) - Constructor for class org.apache.spark.ml.feature.Normalizer
-
- Normalizer() - Constructor for class org.apache.spark.ml.feature.Normalizer
-
- Normalizer - Class in org.apache.spark.mllib.feature
-
Normalizes samples individually to unit L^p^ norm
- Normalizer(double) - Constructor for class org.apache.spark.mllib.feature.Normalizer
-
- Normalizer() - Constructor for class org.apache.spark.mllib.feature.Normalizer
-
- normalizeToProbabilitiesInPlace(DenseVector) - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
Normalize a vector of raw predictions to be a multinomial probability vector, in place.
- normalJavaRDD(JavaSparkContext, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- normalJavaRDD(JavaSparkContext, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- normalJavaRDD(JavaSparkContext, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- normalJavaVectorRDD(JavaSparkContext, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- normalJavaVectorRDD(JavaSparkContext, long, int, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- normalJavaVectorRDD(JavaSparkContext, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- normalRDD(SparkContext, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
Generates an RDD comprised of i.i.d. samples from the standard normal distribution.
- normalVectorRDD(SparkContext, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
Generates an RDD[Vector] with vectors containing i.i.d. samples drawn from the
standard normal distribution.
- normL1() - Method in class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
-
L1 norm of each dimension.
- normL1() - Method in interface org.apache.spark.mllib.stat.MultivariateStatisticalSummary
-
L1 norm of each column
- normL2() - Method in class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
-
L2 (Euclidian) norm of each dimension.
- normL2() - Method in interface org.apache.spark.mllib.stat.MultivariateStatisticalSummary
-
Euclidean magnitude of each column
- normPdf(double, double, double, double) - Static method in class org.apache.spark.mllib.stat.KernelDensity
-
Evaluates the PDF of a normal distribution.
- not(Function0<Parsers.Parser<T>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- not(Column) - Static method in class org.apache.spark.sql.functions
-
Inversion of boolean expression, i.e.
- Not - Class in org.apache.spark.sql.sources
-
A filter that evaluates to true iff child is evaluated to false.
- Not(Filter) - Constructor for class org.apache.spark.sql.sources.Not
-
- notEqual(Object) - Method in class org.apache.spark.sql.Column
-
Inequality test.
- ntile(int) - Static method in class org.apache.spark.sql.functions
-
Window function: returns the ntile group id (from 1 to n inclusive) in an ordered window
partition.
- nullable() - Method in class org.apache.spark.sql.catalog.Column
-
- nullable() - Method in class org.apache.spark.sql.types.StructField
-
- nullDeviance() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
-
The deviance for the null model.
- nullHypothesis() - Method in class org.apache.spark.mllib.stat.test.ChiSqTestResult
-
- nullHypothesis() - Method in class org.apache.spark.mllib.stat.test.KolmogorovSmirnovTestResult
-
- nullHypothesis() - Static method in class org.apache.spark.mllib.stat.test.StudentTTest
-
- nullHypothesis() - Method in interface org.apache.spark.mllib.stat.test.TestResult
-
Null hypothesis of the test.
- nullHypothesis() - Static method in class org.apache.spark.mllib.stat.test.WelchTTest
-
- NullType - Static variable in class org.apache.spark.sql.types.DataTypes
-
Gets the NullType object.
- NullType - Class in org.apache.spark.sql.types
-
:: DeveloperApi ::
The data type representing NULL values.
- NUM_ATTRIBUTES() - Static method in class org.apache.spark.ml.attribute.AttributeKeys
-
- NUM_PARTITIONS() - Static method in class org.apache.spark.ui.UIWorkloadGenerator
-
- NUM_VALUES() - Static method in class org.apache.spark.ml.attribute.AttributeKeys
-
- numAccums() - Static method in class org.apache.spark.util.AccumulatorContext
-
Returns the number of accumulators registered.
- numActives() - Method in class org.apache.spark.ml.linalg.DenseMatrix
-
- numActives() - Method in class org.apache.spark.ml.linalg.DenseVector
-
- numActives() - Method in interface org.apache.spark.ml.linalg.Matrix
-
Find the number of values stored explicitly.
- numActives() - Method in class org.apache.spark.ml.linalg.SparseMatrix
-
- numActives() - Method in class org.apache.spark.ml.linalg.SparseVector
-
- numActives() - Method in interface org.apache.spark.ml.linalg.Vector
-
Number of active entries.
- numActives() - Method in class org.apache.spark.mllib.linalg.DenseMatrix
-
- numActives() - Method in class org.apache.spark.mllib.linalg.DenseVector
-
- numActives() - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Find the number of values stored explicitly.
- numActives() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
-
- numActives() - Method in class org.apache.spark.mllib.linalg.SparseVector
-
- numActives() - Method in interface org.apache.spark.mllib.linalg.Vector
-
Number of active entries.
- numActiveStages() - Method in class org.apache.spark.status.api.v1.JobData
-
- numActiveStages() - Method in class org.apache.spark.ui.jobs.UIData.JobUIData
-
- numActiveTasks() - Method in interface org.apache.spark.SparkStageInfo
-
- numActiveTasks() - Method in class org.apache.spark.SparkStageInfoImpl
-
- numActiveTasks() - Method in class org.apache.spark.status.api.v1.JobData
-
- numActiveTasks() - Method in class org.apache.spark.status.api.v1.StageData
-
- numActiveTasks() - Method in class org.apache.spark.ui.jobs.UIData.JobUIData
-
- numActiveTasks() - Method in class org.apache.spark.ui.jobs.UIData.StageUIData
-
- numAttributes() - Method in class org.apache.spark.ml.attribute.AttributeGroup
-
- numberedTreeString() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- numberedTreeString() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- numberedTreeString() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- numBins() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
-
- numBlocks() - Method in class org.apache.spark.storage.StorageStatus
-
Return the number of blocks stored in this block manager in O(RDDs) time.
- numBuckets() - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- numCachedPartitions() - Method in class org.apache.spark.status.api.v1.RDDStorageInfo
-
- numCachedPartitions() - Method in class org.apache.spark.storage.RDDInfo
-
- numCategories() - Method in class org.apache.spark.ml.tree.CategoricalSplit
-
- numCategories() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.SplitData
-
- numClasses() - Method in class org.apache.spark.ml.classification.ClassificationModel
-
Number of classes (values which the label can take).
- numClasses() - Method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- numClasses() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- numClasses() - Method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- numClasses() - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- numClasses() - Method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- numClasses() - Method in class org.apache.spark.mllib.classification.LogisticRegressionModel
-
- numClasses() - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- numColBlocks() - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
-
- numCols() - Method in class org.apache.spark.ml.linalg.DenseMatrix
-
- numCols() - Method in interface org.apache.spark.ml.linalg.Matrix
-
Number of columns.
- numCols() - Method in class org.apache.spark.ml.linalg.SparseMatrix
-
- numCols() - Method in class org.apache.spark.mllib.linalg.DenseMatrix
-
- numCols() - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
-
- numCols() - Method in class org.apache.spark.mllib.linalg.distributed.CoordinateMatrix
-
Gets or computes the number of columns.
- numCols() - Method in interface org.apache.spark.mllib.linalg.distributed.DistributedMatrix
-
Gets or computes the number of columns.
- numCols() - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
-
- numCols() - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
-
Gets or computes the number of columns.
- numCols() - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Number of columns.
- numCols() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
-
- numCompletedJobs() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- numCompletedStages() - Method in class org.apache.spark.status.api.v1.JobData
-
- numCompletedStages() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- numCompletedTasks() - Method in interface org.apache.spark.SparkStageInfo
-
- numCompletedTasks() - Method in class org.apache.spark.SparkStageInfoImpl
-
- numCompletedTasks() - Method in class org.apache.spark.status.api.v1.JobData
-
- numCompletedTasks() - Method in class org.apache.spark.ui.jobs.UIData.JobUIData
-
- numCompleteTasks() - Method in class org.apache.spark.status.api.v1.StageData
-
- numCompleteTasks() - Method in class org.apache.spark.ui.jobs.UIData.StageUIData
-
- numEdges() - Method in class org.apache.spark.graphx.GraphOps
-
The number of edges in the graph.
- Numeric() - Static method in class org.apache.spark.ml.attribute.AttributeType
-
Numeric type.
- NumericAttribute - Class in org.apache.spark.ml.attribute
-
:: DeveloperApi ::
A numeric attribute with optional summary statistics.
- NumericParser - Class in org.apache.spark.mllib.util
-
Simple parser for a numeric structure consisting of three types:
- NumericParser() - Constructor for class org.apache.spark.mllib.util.NumericParser
-
- numericRDDToDoubleRDDFunctions(RDD<T>, Numeric<T>) - Static method in class org.apache.spark.rdd.RDD
-
- NumericType - Class in org.apache.spark.sql.types
-
:: DeveloperApi ::
Numeric data types.
- NumericType() - Constructor for class org.apache.spark.sql.types.NumericType
-
- numFailedJobs() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- numFailedStages() - Method in class org.apache.spark.status.api.v1.JobData
-
- numFailedStages() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- numFailedStages() - Method in class org.apache.spark.ui.jobs.UIData.JobUIData
-
- numFailedTasks() - Method in interface org.apache.spark.SparkStageInfo
-
- numFailedTasks() - Method in class org.apache.spark.SparkStageInfoImpl
-
- numFailedTasks() - Method in class org.apache.spark.status.api.v1.JobData
-
- numFailedTasks() - Method in class org.apache.spark.status.api.v1.StageData
-
- numFailedTasks() - Method in class org.apache.spark.ui.jobs.UIData.JobUIData
-
- numFailedTasks() - Method in class org.apache.spark.ui.jobs.UIData.StageUIData
-
- numFeatures() - Method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- numFeatures() - Method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- numFeatures() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- numFeatures() - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- numFeatures() - Method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- numFeatures() - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- numFeatures() - Method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- numFeatures() - Method in class org.apache.spark.ml.feature.HashingTF
-
Number of features.
- numFeatures() - Method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- numFeatures() - Method in class org.apache.spark.ml.PredictionModel
-
Returns the number of features the model was trained on.
- numFeatures() - Method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- numFeatures() - Method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- numFeatures() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- numFeatures() - Method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- numFeatures() - Method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- numFeatures() - Method in class org.apache.spark.mllib.classification.LogisticRegressionModel
-
- numFeatures() - Method in class org.apache.spark.mllib.feature.HashingTF
-
- numFolds() - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- numFolds() - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- numInstances() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
-
Number of instances in DataFrame predictions
- numItemBlocks() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- numIterations() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionTrainingSummary
-
- numIterations() - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- numNodes() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- numNodes() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- numNodes() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
-
Get number of nodes in tree, including leaf nodes.
- numNonzeros() - Method in class org.apache.spark.ml.linalg.DenseMatrix
-
- numNonzeros() - Method in class org.apache.spark.ml.linalg.DenseVector
-
- numNonzeros() - Method in interface org.apache.spark.ml.linalg.Matrix
-
Find the number of non-zero active values.
- numNonzeros() - Method in class org.apache.spark.ml.linalg.SparseMatrix
-
- numNonzeros() - Method in class org.apache.spark.ml.linalg.SparseVector
-
- numNonzeros() - Method in interface org.apache.spark.ml.linalg.Vector
-
Number of nonzero elements.
- numNonzeros() - Method in class org.apache.spark.mllib.linalg.DenseMatrix
-
- numNonzeros() - Method in class org.apache.spark.mllib.linalg.DenseVector
-
- numNonzeros() - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Find the number of non-zero active values.
- numNonzeros() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
-
- numNonzeros() - Method in class org.apache.spark.mllib.linalg.SparseVector
-
- numNonzeros() - Method in interface org.apache.spark.mllib.linalg.Vector
-
Number of nonzero elements.
- numNonzeros() - Method in class org.apache.spark.mllib.stat.MultivariateOnlineSummarizer
-
Number of nonzero elements in each dimension.
- numNonzeros() - Method in interface org.apache.spark.mllib.stat.MultivariateStatisticalSummary
-
Number of nonzero elements (including explicitly presented zero values) in each column.
- numPartitions() - Method in class org.apache.spark.HashPartitioner
-
- numPartitions() - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- numPartitions() - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- numPartitions() - Method in class org.apache.spark.Partitioner
-
- numPartitions() - Method in class org.apache.spark.RangePartitioner
-
- numPartitions() - Method in class org.apache.spark.rdd.PartitionGroup
-
- numPartitions() - Method in class org.apache.spark.status.api.v1.RDDStorageInfo
-
- numPartitions() - Method in class org.apache.spark.storage.RDDInfo
-
- numPartitions(int) - Method in class org.apache.spark.streaming.StateSpec
-
Set the number of partitions by which the state RDDs generated by mapWithState
will be partitioned.
- numRddBlocks() - Method in class org.apache.spark.storage.StorageStatus
-
Return the number of RDD blocks stored in this block manager in O(RDDs) time.
- numRddBlocksById(int) - Method in class org.apache.spark.storage.StorageStatus
-
Return the number of blocks that belong to the given RDD in O(1) time.
- numRecords() - Method in class org.apache.spark.streaming.scheduler.BatchInfo
-
The number of recorders received by the receivers in this batch.
- numRecords() - Method in class org.apache.spark.streaming.scheduler.StreamInputInfo
-
- numRetries(SparkConf) - Static method in class org.apache.spark.util.RpcUtils
-
Returns the configured number of times to retry connecting
- numRowBlocks() - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
-
- numRows() - Method in class org.apache.spark.ml.linalg.DenseMatrix
-
- numRows() - Method in interface org.apache.spark.ml.linalg.Matrix
-
Number of rows.
- numRows() - Method in class org.apache.spark.ml.linalg.SparseMatrix
-
- numRows() - Method in class org.apache.spark.mllib.linalg.DenseMatrix
-
- numRows() - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
-
- numRows() - Method in class org.apache.spark.mllib.linalg.distributed.CoordinateMatrix
-
Gets or computes the number of rows.
- numRows() - Method in interface org.apache.spark.mllib.linalg.distributed.DistributedMatrix
-
Gets or computes the number of rows.
- numRows() - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
-
- numRows() - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
-
Gets or computes the number of rows.
- numRows() - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Number of rows.
- numRows() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
-
- numRunningTasks() - Method in interface org.apache.spark.SparkExecutorInfo
-
- numRunningTasks() - Method in class org.apache.spark.SparkExecutorInfoImpl
-
- numSkippedStages() - Method in class org.apache.spark.status.api.v1.JobData
-
- numSkippedStages() - Method in class org.apache.spark.ui.jobs.UIData.JobUIData
-
- numSkippedTasks() - Method in class org.apache.spark.status.api.v1.JobData
-
- numSkippedTasks() - Method in class org.apache.spark.ui.jobs.UIData.JobUIData
-
- numSpilledStages() - Method in class org.apache.spark.SpillListener
-
- numTasks() - Method in class org.apache.spark.scheduler.StageInfo
-
- numTasks() - Method in interface org.apache.spark.SparkStageInfo
-
- numTasks() - Method in class org.apache.spark.SparkStageInfoImpl
-
- numTasks() - Method in class org.apache.spark.status.api.v1.JobData
-
- numTasks() - Method in class org.apache.spark.ui.jobs.UIData.JobUIData
-
- numTopFeatures() - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- numTopFeatures() - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- numTopFeatures() - Method in class org.apache.spark.mllib.feature.ChiSqSelector
-
- numTrees() - Method in class org.apache.spark.ml.classification.GBTClassificationModel
-
Number of trees in ensemble
- numTrees() - Method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
Deprecated.
Use getNumTrees instead. This method will be removed in 2.1.0
- numTrees() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- numTrees() - Method in class org.apache.spark.ml.regression.GBTRegressionModel
-
Number of trees in ensemble
- numTrees() - Method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
Deprecated.
Use getNumTrees instead. This method will be removed in 2.1.0
- numTrees() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- numTrees() - Static method in class org.apache.spark.mllib.tree.model.GradientBoostedTreesModel
-
- numTrees() - Static method in class org.apache.spark.mllib.tree.model.RandomForestModel
-
- numUserBlocks() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- numValues() - Method in class org.apache.spark.ml.attribute.NominalAttribute
-
- numVertices() - Method in class org.apache.spark.graphx.GraphOps
-
The number of vertices in the graph.
- objectFile(String, int) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Load an RDD saved as a SequenceFile containing serialized objects, with NullWritable keys and
BytesWritable values that contain a serialized partition.
- objectFile(String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Load an RDD saved as a SequenceFile containing serialized objects, with NullWritable keys and
BytesWritable values that contain a serialized partition.
- objectFile(String, int, ClassTag<T>) - Method in class org.apache.spark.SparkContext
-
Load an RDD saved as a SequenceFile containing serialized objects, with NullWritable keys and
BytesWritable values that contain a serialized partition.
- objectiveHistory() - Method in class org.apache.spark.ml.classification.BinaryLogisticRegressionTrainingSummary
-
- objectiveHistory() - Method in interface org.apache.spark.ml.classification.LogisticRegressionTrainingSummary
-
objective function (scaled loss + regularization) at each iteration.
- objectiveHistory() - Method in class org.apache.spark.ml.regression.LinearRegressionTrainingSummary
-
- of(T) - Static method in class org.apache.spark.api.java.Optional
-
- of(RDD<Tuple2<Object, Object>>) - Static method in class org.apache.spark.mllib.evaluation.AreaUnderCurve
-
Returns the area under the given curve.
- of(Iterable<Tuple2<Object, Object>>) - Static method in class org.apache.spark.mllib.evaluation.AreaUnderCurve
-
Returns the area under the given curve.
- of(JavaRDD<Tuple2<T, T>>) - Static method in class org.apache.spark.mllib.evaluation.RankingMetrics
-
- OFF_HEAP - Static variable in class org.apache.spark.api.java.StorageLevels
-
- OFF_HEAP() - Static method in class org.apache.spark.storage.StorageLevel
-
- offset() - Method in class org.apache.spark.streaming.kafka.KafkaCluster.LeaderOffset
-
- offsetBytes(String, long, long) - Static method in class org.apache.spark.util.Utils
-
Return a string containing part of a file from byte 'start' to 'end'.
- offsetBytes(Seq<File>, long, long) - Static method in class org.apache.spark.util.Utils
-
Return a string containing data across a set of files.
- offsetDesc() - Method in class org.apache.spark.sql.streaming.SinkStatus
-
- offsetDesc() - Method in class org.apache.spark.sql.streaming.SourceStatus
-
- OffsetRange - Class in org.apache.spark.streaming.kafka
-
Represents a range of offsets from a single Kafka TopicAndPartition.
- offsetRanges() - Method in interface org.apache.spark.streaming.kafka.HasOffsetRanges
-
- ofNullable(T) - Static method in class org.apache.spark.api.java.Optional
-
- ofRows(SparkSession, LogicalPlan) - Static method in class org.apache.spark.sql.Dataset
-
- onApplicationEnd(SparkListenerApplicationEnd) - Method in class org.apache.spark.scheduler.SparkListener
-
- onApplicationEnd(SparkListenerApplicationEnd) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- onApplicationEnd(SparkListenerApplicationEnd) - Method in class org.apache.spark.SparkFirehoseListener
-
- onApplicationEnd(SparkListenerApplicationEnd) - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- onApplicationStart(SparkListenerApplicationStart) - Method in class org.apache.spark.scheduler.SparkListener
-
- onApplicationStart(SparkListenerApplicationStart) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- onApplicationStart(SparkListenerApplicationStart) - Method in class org.apache.spark.SparkFirehoseListener
-
- onApplicationStart(SparkListenerApplicationStart) - Method in class org.apache.spark.ui.exec.ExecutorsListener
-
- onApplicationStart(SparkListenerApplicationStart) - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- onBatchCompleted(StreamingListenerBatchCompleted) - Method in class org.apache.spark.streaming.scheduler.StatsReportListener
-
- onBatchCompleted(StreamingListenerBatchCompleted) - Method in interface org.apache.spark.streaming.scheduler.StreamingListener
-
Called when processing of a batch of jobs has completed.
- onBatchStarted(StreamingListenerBatchStarted) - Static method in class org.apache.spark.streaming.scheduler.StatsReportListener
-
- onBatchStarted(StreamingListenerBatchStarted) - Method in interface org.apache.spark.streaming.scheduler.StreamingListener
-
Called when processing of a batch of jobs has started.
- onBatchSubmitted(StreamingListenerBatchSubmitted) - Static method in class org.apache.spark.streaming.scheduler.StatsReportListener
-
- onBatchSubmitted(StreamingListenerBatchSubmitted) - Method in interface org.apache.spark.streaming.scheduler.StreamingListener
-
Called when a batch of jobs has been submitted for processing.
- onBlockManagerAdded(SparkListenerBlockManagerAdded) - Method in class org.apache.spark.scheduler.SparkListener
-
- onBlockManagerAdded(SparkListenerBlockManagerAdded) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- onBlockManagerAdded(SparkListenerBlockManagerAdded) - Method in class org.apache.spark.SparkFirehoseListener
-
- onBlockManagerAdded(SparkListenerBlockManagerAdded) - Method in class org.apache.spark.storage.StorageStatusListener
-
- onBlockManagerAdded(SparkListenerBlockManagerAdded) - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- onBlockManagerRemoved(SparkListenerBlockManagerRemoved) - Method in class org.apache.spark.scheduler.SparkListener
-
- onBlockManagerRemoved(SparkListenerBlockManagerRemoved) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- onBlockManagerRemoved(SparkListenerBlockManagerRemoved) - Method in class org.apache.spark.SparkFirehoseListener
-
- onBlockManagerRemoved(SparkListenerBlockManagerRemoved) - Method in class org.apache.spark.storage.StorageStatusListener
-
- onBlockManagerRemoved(SparkListenerBlockManagerRemoved) - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- onBlockUpdated(SparkListenerBlockUpdated) - Method in class org.apache.spark.scheduler.SparkListener
-
- onBlockUpdated(SparkListenerBlockUpdated) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- onBlockUpdated(SparkListenerBlockUpdated) - Method in class org.apache.spark.SparkFirehoseListener
-
- onBlockUpdated(SparkListenerBlockUpdated) - Method in class org.apache.spark.storage.StorageStatusListener
-
- onBlockUpdated(SparkListenerBlockUpdated) - Method in class org.apache.spark.ui.storage.StorageListener
-
- OnceParser(Function1<Reader<Object>, Parsers.ParseResult<T>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- onComplete(Function1<Try<T>, U>, ExecutionContext) - Method in class org.apache.spark.ComplexFutureAction
-
- onComplete(Function1<Try<T>, U>, ExecutionContext) - Method in interface org.apache.spark.FutureAction
-
When this action is completed, either through an exception, or a value, applies the provided
function.
- onComplete(Function1<R, BoxedUnit>) - Method in class org.apache.spark.partial.PartialResult
-
Set a handler to be called when this PartialResult completes.
- onComplete(Function1<Try<T>, U>, ExecutionContext) - Method in class org.apache.spark.SimpleFutureAction
-
- OneHotEncoder - Class in org.apache.spark.ml.feature
-
A one-hot encoder that maps a column of category indices to a column of binary vectors, with
at most a single one-value per row that indicates the input category index.
- OneHotEncoder(String) - Constructor for class org.apache.spark.ml.feature.OneHotEncoder
-
- OneHotEncoder() - Constructor for class org.apache.spark.ml.feature.OneHotEncoder
-
- onEnvironmentUpdate(SparkListenerEnvironmentUpdate) - Method in class org.apache.spark.scheduler.SparkListener
-
- onEnvironmentUpdate(SparkListenerEnvironmentUpdate) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- onEnvironmentUpdate(SparkListenerEnvironmentUpdate) - Method in class org.apache.spark.SparkFirehoseListener
-
- onEnvironmentUpdate(SparkListenerEnvironmentUpdate) - Method in class org.apache.spark.ui.env.EnvironmentListener
-
- onEnvironmentUpdate(SparkListenerEnvironmentUpdate) - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- ones(int, int) - Static method in class org.apache.spark.ml.linalg.DenseMatrix
-
Generate a DenseMatrix consisting of ones.
- ones(int, int) - Static method in class org.apache.spark.ml.linalg.Matrices
-
Generate a DenseMatrix consisting of ones.
- ones(int, int) - Static method in class org.apache.spark.mllib.linalg.DenseMatrix
-
Generate a DenseMatrix consisting of ones.
- ones(int, int) - Static method in class org.apache.spark.mllib.linalg.Matrices
-
Generate a DenseMatrix consisting of ones.
- OneSampleTwoSided() - Method in class org.apache.spark.mllib.stat.test.KolmogorovSmirnovTest.NullHypothesis$
-
- OneToOneDependency<T> - Class in org.apache.spark
-
:: DeveloperApi ::
Represents a one-to-one dependency between partitions of the parent and child RDDs.
- OneToOneDependency(RDD<T>) - Constructor for class org.apache.spark.OneToOneDependency
-
- onEvent(SparkListenerEvent) - Method in class org.apache.spark.SparkFirehoseListener
-
- OneVsRest - Class in org.apache.spark.ml.classification
-
Reduction of Multiclass Classification to Binary Classification.
- OneVsRest(String) - Constructor for class org.apache.spark.ml.classification.OneVsRest
-
- OneVsRest() - Constructor for class org.apache.spark.ml.classification.OneVsRest
-
- OneVsRestModel - Class in org.apache.spark.ml.classification
-
- onExecutorAdded(SparkListenerExecutorAdded) - Method in class org.apache.spark.scheduler.SparkListener
-
- onExecutorAdded(SparkListenerExecutorAdded) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- onExecutorAdded(SparkListenerExecutorAdded) - Method in class org.apache.spark.SparkFirehoseListener
-
- onExecutorAdded(SparkListenerExecutorAdded) - Method in class org.apache.spark.ui.exec.ExecutorsListener
-
- onExecutorMetricsUpdate(SparkListenerExecutorMetricsUpdate) - Method in class org.apache.spark.scheduler.SparkListener
-
- onExecutorMetricsUpdate(SparkListenerExecutorMetricsUpdate) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- onExecutorMetricsUpdate(SparkListenerExecutorMetricsUpdate) - Method in class org.apache.spark.SparkFirehoseListener
-
- onExecutorMetricsUpdate(SparkListenerExecutorMetricsUpdate) - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- onExecutorRemoved(SparkListenerExecutorRemoved) - Method in class org.apache.spark.scheduler.SparkListener
-
- onExecutorRemoved(SparkListenerExecutorRemoved) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- onExecutorRemoved(SparkListenerExecutorRemoved) - Method in class org.apache.spark.SparkFirehoseListener
-
- onExecutorRemoved(SparkListenerExecutorRemoved) - Method in class org.apache.spark.ui.exec.ExecutorsListener
-
- onFail(Function1<Exception, BoxedUnit>) - Method in class org.apache.spark.partial.PartialResult
-
Set a handler to be called if this PartialResult's job fails.
- onFailure(String, QueryExecution, Exception) - Method in interface org.apache.spark.sql.util.QueryExecutionListener
-
A callback function that will be called when a query execution failed.
- onJobEnd(SparkListenerJobEnd) - Method in class org.apache.spark.scheduler.SparkListener
-
- onJobEnd(SparkListenerJobEnd) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- onJobEnd(SparkListenerJobEnd) - Method in class org.apache.spark.SparkFirehoseListener
-
- onJobEnd(SparkListenerJobEnd) - Method in class org.apache.spark.SpillListener
-
- onJobEnd(SparkListenerJobEnd) - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- onJobStart(SparkListenerJobStart) - Method in class org.apache.spark.scheduler.SparkListener
-
- onJobStart(SparkListenerJobStart) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- onJobStart(SparkListenerJobStart) - Method in class org.apache.spark.SparkFirehoseListener
-
- onJobStart(SparkListenerJobStart) - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- OnlineLDAOptimizer - Class in org.apache.spark.mllib.clustering
-
:: DeveloperApi ::
- OnlineLDAOptimizer() - Constructor for class org.apache.spark.mllib.clustering.OnlineLDAOptimizer
-
- onOtherEvent(SparkListenerEvent) - Method in class org.apache.spark.scheduler.SparkListener
-
- onOtherEvent(SparkListenerEvent) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- onOtherEvent(SparkListenerEvent) - Method in class org.apache.spark.SparkFirehoseListener
-
- onOutputOperationCompleted(StreamingListenerOutputOperationCompleted) - Static method in class org.apache.spark.streaming.scheduler.StatsReportListener
-
- onOutputOperationCompleted(StreamingListenerOutputOperationCompleted) - Method in interface org.apache.spark.streaming.scheduler.StreamingListener
-
Called when processing of a job of a batch has completed.
- onOutputOperationStarted(StreamingListenerOutputOperationStarted) - Static method in class org.apache.spark.streaming.scheduler.StatsReportListener
-
- onOutputOperationStarted(StreamingListenerOutputOperationStarted) - Method in interface org.apache.spark.streaming.scheduler.StreamingListener
-
Called when processing of a job of a batch has started.
- onQueryProgress(StreamingQueryListener.QueryProgress) - Method in class org.apache.spark.sql.streaming.StreamingQueryListener
-
Called when there is some status update (ingestion rate updated, etc.)
- onQueryStarted(StreamingQueryListener.QueryStarted) - Method in class org.apache.spark.sql.streaming.StreamingQueryListener
-
Called when a query is started.
- onQueryTerminated(StreamingQueryListener.QueryTerminated) - Method in class org.apache.spark.sql.streaming.StreamingQueryListener
-
Called when a query is stopped, with or without error.
- onReceiverError(StreamingListenerReceiverError) - Static method in class org.apache.spark.streaming.scheduler.StatsReportListener
-
- onReceiverError(StreamingListenerReceiverError) - Method in interface org.apache.spark.streaming.scheduler.StreamingListener
-
Called when a receiver has reported an error
- onReceiverStarted(StreamingListenerReceiverStarted) - Static method in class org.apache.spark.streaming.scheduler.StatsReportListener
-
- onReceiverStarted(StreamingListenerReceiverStarted) - Method in interface org.apache.spark.streaming.scheduler.StreamingListener
-
Called when a receiver has been started
- onReceiverStopped(StreamingListenerReceiverStopped) - Static method in class org.apache.spark.streaming.scheduler.StatsReportListener
-
- onReceiverStopped(StreamingListenerReceiverStopped) - Method in interface org.apache.spark.streaming.scheduler.StreamingListener
-
Called when a receiver has been stopped
- onStageCompleted(SparkListenerStageCompleted) - Method in class org.apache.spark.scheduler.SparkListener
-
- onStageCompleted(SparkListenerStageCompleted) - Method in class org.apache.spark.scheduler.StatsReportListener
-
- onStageCompleted(SparkListenerStageCompleted) - Method in class org.apache.spark.SparkFirehoseListener
-
- onStageCompleted(SparkListenerStageCompleted) - Method in class org.apache.spark.SpillListener
-
- onStageCompleted(SparkListenerStageCompleted) - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- onStageCompleted(SparkListenerStageCompleted) - Method in class org.apache.spark.ui.storage.StorageListener
-
- onStageSubmitted(SparkListenerStageSubmitted) - Method in class org.apache.spark.scheduler.SparkListener
-
- onStageSubmitted(SparkListenerStageSubmitted) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- onStageSubmitted(SparkListenerStageSubmitted) - Method in class org.apache.spark.SparkFirehoseListener
-
- onStageSubmitted(SparkListenerStageSubmitted) - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
For FIFO, all stages are contained by "default" pool but "default" pool here is meaningless
- onStageSubmitted(SparkListenerStageSubmitted) - Method in class org.apache.spark.ui.storage.StorageListener
-
- OnStart - Class in org.apache.spark.rpc.netty
-
- OnStart() - Constructor for class org.apache.spark.rpc.netty.OnStart
-
- onStart() - Method in class org.apache.spark.streaming.receiver.Receiver
-
This method is called by the system when the receiver is started.
- OnStop - Class in org.apache.spark.rpc.netty
-
- OnStop() - Constructor for class org.apache.spark.rpc.netty.OnStop
-
- onStop() - Method in class org.apache.spark.streaming.receiver.Receiver
-
This method is called by the system when the receiver is stopped.
- onSuccess(String, QueryExecution, long) - Method in interface org.apache.spark.sql.util.QueryExecutionListener
-
A callback function that will be called when a query executed successfully.
- onTaskCompletion(TaskContext) - Method in interface org.apache.spark.util.TaskCompletionListener
-
- onTaskEnd(SparkListenerTaskEnd) - Method in class org.apache.spark.scheduler.SparkListener
-
- onTaskEnd(SparkListenerTaskEnd) - Method in class org.apache.spark.scheduler.StatsReportListener
-
- onTaskEnd(SparkListenerTaskEnd) - Method in class org.apache.spark.SparkFirehoseListener
-
- onTaskEnd(SparkListenerTaskEnd) - Method in class org.apache.spark.SpillListener
-
- onTaskEnd(SparkListenerTaskEnd) - Method in class org.apache.spark.ui.exec.ExecutorsListener
-
- onTaskEnd(SparkListenerTaskEnd) - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- onTaskFailure(TaskContext, Throwable) - Method in interface org.apache.spark.util.TaskFailureListener
-
- onTaskGettingResult(SparkListenerTaskGettingResult) - Method in class org.apache.spark.scheduler.SparkListener
-
- onTaskGettingResult(SparkListenerTaskGettingResult) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- onTaskGettingResult(SparkListenerTaskGettingResult) - Method in class org.apache.spark.SparkFirehoseListener
-
- onTaskGettingResult(SparkListenerTaskGettingResult) - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- onTaskStart(SparkListenerTaskStart) - Method in class org.apache.spark.scheduler.SparkListener
-
- onTaskStart(SparkListenerTaskStart) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- onTaskStart(SparkListenerTaskStart) - Method in class org.apache.spark.SparkFirehoseListener
-
- onTaskStart(SparkListenerTaskStart) - Method in class org.apache.spark.ui.exec.ExecutorsListener
-
- onTaskStart(SparkListenerTaskStart) - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- onUnpersistRDD(SparkListenerUnpersistRDD) - Method in class org.apache.spark.scheduler.SparkListener
-
- onUnpersistRDD(SparkListenerUnpersistRDD) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- onUnpersistRDD(SparkListenerUnpersistRDD) - Method in class org.apache.spark.SparkFirehoseListener
-
- onUnpersistRDD(SparkListenerUnpersistRDD) - Method in class org.apache.spark.storage.StorageStatusListener
-
- onUnpersistRDD(SparkListenerUnpersistRDD) - Method in class org.apache.spark.ui.storage.StorageListener
-
- OOM() - Static method in class org.apache.spark.util.SparkExitCode
-
The default uncaught exception handler was reached, and the uncaught exception was an
- open() - Method in class org.apache.spark.input.PortableDataStream
-
Create a new DataInputStream from the split and context.
- open(long, long) - Method in class org.apache.spark.sql.ForeachWriter
-
Called when starting to process one partition of new data in the executor.
- ops() - Method in class org.apache.spark.graphx.Graph
-
- ops() - Static method in class org.apache.spark.graphx.impl.GraphImpl
-
- opt(Function0<Parsers.Parser<T>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- optimize(RDD<Tuple2<Object, Vector>>, Vector) - Method in class org.apache.spark.mllib.optimization.GradientDescent
-
:: DeveloperApi ::
Runs gradient descent on the given training data.
- optimize(RDD<Tuple2<Object, Vector>>, Vector) - Method in class org.apache.spark.mllib.optimization.LBFGS
-
- optimize(RDD<Tuple2<Object, Vector>>, Vector) - Method in interface org.apache.spark.mllib.optimization.Optimizer
-
Solve the provided convex optimization problem.
- optimizeDocConcentration() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- optimizeDocConcentration() - Static method in class org.apache.spark.ml.clustering.LDA
-
- optimizeDocConcentration() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- optimizer() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- optimizer() - Static method in class org.apache.spark.ml.clustering.LDA
-
- optimizer() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- optimizer() - Method in class org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS
-
- optimizer() - Method in class org.apache.spark.mllib.classification.LogisticRegressionWithSGD
-
- optimizer() - Method in class org.apache.spark.mllib.classification.SVMWithSGD
-
- Optimizer - Interface in org.apache.spark.mllib.optimization
-
:: DeveloperApi ::
Trait for optimization problem solvers.
- optimizer() - Method in class org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm
-
The optimizer to solve the problem.
- optimizer() - Method in class org.apache.spark.mllib.regression.LassoWithSGD
-
- optimizer() - Method in class org.apache.spark.mllib.regression.LinearRegressionWithSGD
-
- optimizer() - Method in class org.apache.spark.mllib.regression.RidgeRegressionWithSGD
-
- option(String, String) - Method in class org.apache.spark.sql.DataFrameReader
-
Adds an input option for the underlying data source.
- option(String, boolean) - Method in class org.apache.spark.sql.DataFrameReader
-
Adds an input option for the underlying data source.
- option(String, long) - Method in class org.apache.spark.sql.DataFrameReader
-
Adds an input option for the underlying data source.
- option(String, double) - Method in class org.apache.spark.sql.DataFrameReader
-
Adds an input option for the underlying data source.
- option(String, String) - Method in class org.apache.spark.sql.DataFrameWriter
-
Adds an output option for the underlying data source.
- option(String, boolean) - Method in class org.apache.spark.sql.DataFrameWriter
-
Adds an output option for the underlying data source.
- option(String, long) - Method in class org.apache.spark.sql.DataFrameWriter
-
Adds an output option for the underlying data source.
- option(String, double) - Method in class org.apache.spark.sql.DataFrameWriter
-
Adds an output option for the underlying data source.
- option(String, String) - Method in class org.apache.spark.sql.streaming.DataStreamReader
-
:: Experimental ::
Adds an input option for the underlying data source.
- option(String, boolean) - Method in class org.apache.spark.sql.streaming.DataStreamReader
-
:: Experimental ::
Adds an input option for the underlying data source.
- option(String, long) - Method in class org.apache.spark.sql.streaming.DataStreamReader
-
:: Experimental ::
Adds an input option for the underlying data source.
- option(String, double) - Method in class org.apache.spark.sql.streaming.DataStreamReader
-
:: Experimental ::
Adds an input option for the underlying data source.
- option(String, String) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
-
:: Experimental ::
Adds an output option for the underlying data source.
- option(String, boolean) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
-
:: Experimental ::
Adds an output option for the underlying data source.
- option(String, long) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
-
:: Experimental ::
Adds an output option for the underlying data source.
- option(String, double) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
-
:: Experimental ::
Adds an output option for the underlying data source.
- Optional<T> - Class in org.apache.spark.api.java
-
Like java.util.Optional in Java 8, scala.Option in Scala, and
com.google.common.base.Optional in Google Guava, this class represents a
value of a given type that may or may not exist.
- options(Map<String, String>) - Method in class org.apache.spark.sql.DataFrameReader
-
(Scala-specific) Adds input options for the underlying data source.
- options(Map<String, String>) - Method in class org.apache.spark.sql.DataFrameReader
-
Adds input options for the underlying data source.
- options(Map<String, String>) - Method in class org.apache.spark.sql.DataFrameWriter
-
(Scala-specific) Adds output options for the underlying data source.
- options(Map<String, String>) - Method in class org.apache.spark.sql.DataFrameWriter
-
Adds output options for the underlying data source.
- options(Map<String, String>) - Method in class org.apache.spark.sql.streaming.DataStreamReader
-
:: Experimental ::
(Scala-specific) Adds input options for the underlying data source.
- options(Map<String, String>) - Method in class org.apache.spark.sql.streaming.DataStreamReader
-
:: Experimental ::
Adds input options for the underlying data source.
- options(Map<String, String>) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
-
:: Experimental ::
(Scala-specific) Adds output options for the underlying data source.
- options(Map<String, String>) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
-
:: Experimental ::
Adds output options for the underlying data source.
- optionToOptional(Option<T>) - Static method in class org.apache.spark.api.java.JavaUtils
-
- or(T) - Method in class org.apache.spark.api.java.Optional
-
- or(Column) - Method in class org.apache.spark.sql.Column
-
Boolean OR.
- Or - Class in org.apache.spark.sql.sources
-
A filter that evaluates to true iff at least one of left or right evaluates to true.
- Or(Filter, Filter) - Constructor for class org.apache.spark.sql.sources.Or
-
- OracleDialect - Class in org.apache.spark.sql.jdbc
-
- OracleDialect() - Constructor for class org.apache.spark.sql.jdbc.OracleDialect
-
- orc(String...) - Method in class org.apache.spark.sql.DataFrameReader
-
Loads an ORC file and returns the result as a DataFrame.
- orc(String) - Method in class org.apache.spark.sql.DataFrameReader
-
Loads an ORC file and returns the result as a DataFrame.
- orc(Seq<String>) - Method in class org.apache.spark.sql.DataFrameReader
-
Loads an ORC file and returns the result as a DataFrame.
- orc(String) - Method in class org.apache.spark.sql.DataFrameWriter
-
Saves the content of the DataFrame in ORC format at the specified path.
- ORC_COMPRESSION() - Static method in class org.apache.spark.sql.hive.orc.OrcRelation
-
- OrcFileFormat - Class in org.apache.spark.sql.hive.orc
-
FileFormat for reading ORC files.
- OrcFileFormat() - Constructor for class org.apache.spark.sql.hive.orc.OrcFileFormat
-
- OrcFileOperator - Class in org.apache.spark.sql.hive.orc
-
- OrcFileOperator() - Constructor for class org.apache.spark.sql.hive.orc.OrcFileOperator
-
- OrcFilters - Class in org.apache.spark.sql.hive.orc
-
Helper object for building ORC SearchArguments, which are used for ORC predicate push-down.
- OrcFilters() - Constructor for class org.apache.spark.sql.hive.orc.OrcFilters
-
- OrcRelation - Class in org.apache.spark.sql.hive.orc
-
- OrcRelation() - Constructor for class org.apache.spark.sql.hive.orc.OrcRelation
-
- orderBy(String, String...) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset sorted by the given expressions.
- orderBy(Column...) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset sorted by the given expressions.
- orderBy(String, Seq<String>) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset sorted by the given expressions.
- orderBy(Seq<Column>) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset sorted by the given expressions.
- orderBy(String, String...) - Static method in class org.apache.spark.sql.expressions.Window
-
- orderBy(Column...) - Static method in class org.apache.spark.sql.expressions.Window
-
- orderBy(String, Seq<String>) - Static method in class org.apache.spark.sql.expressions.Window
-
- orderBy(Seq<Column>) - Static method in class org.apache.spark.sql.expressions.Window
-
- orderBy(String, String...) - Method in class org.apache.spark.sql.expressions.WindowSpec
-
- orderBy(Column...) - Method in class org.apache.spark.sql.expressions.WindowSpec
-
- orderBy(String, Seq<String>) - Method in class org.apache.spark.sql.expressions.WindowSpec
-
- orderBy(Seq<Column>) - Method in class org.apache.spark.sql.expressions.WindowSpec
-
- OrderedRDDFunctions<K,V,P extends scala.Product2<K,V>> - Class in org.apache.spark.rdd
-
Extra functions available on RDDs of (key, value) pairs where the key is sortable through
an implicit conversion.
- OrderedRDDFunctions(RDD<P>, Ordering<K>, ClassTag<K>, ClassTag<V>, ClassTag<P>) - Constructor for class org.apache.spark.rdd.OrderedRDDFunctions
-
- ordering() - Static method in class org.apache.spark.streaming.Time
-
- ORDINAL() - Static method in class org.apache.spark.ml.attribute.AttributeKeys
-
- orElse(T) - Method in class org.apache.spark.api.java.Optional
-
- orElse(PartialFunction<A1, B1>) - Static method in class org.apache.spark.sql.types.StructType
-
- org.apache.spark - package org.apache.spark
-
Core Spark classes in Scala.
- org.apache.spark.api.java - package org.apache.spark.api.java
-
Spark Java programming APIs.
- org.apache.spark.api.java.function - package org.apache.spark.api.java.function
-
Set of interfaces to represent functions in Spark's Java API.
- org.apache.spark.api.r - package org.apache.spark.api.r
-
- org.apache.spark.broadcast - package org.apache.spark.broadcast
-
Spark's broadcast variables, used to broadcast immutable datasets to all nodes.
- org.apache.spark.graphx - package org.apache.spark.graphx
-
ALPHA COMPONENT
GraphX is a graph processing framework built on top of Spark.
- org.apache.spark.graphx.impl - package org.apache.spark.graphx.impl
-
- org.apache.spark.graphx.lib - package org.apache.spark.graphx.lib
-
Various analytics functions for graphs.
- org.apache.spark.graphx.util - package org.apache.spark.graphx.util
-
Collections of utilities used by graphx.
- org.apache.spark.input - package org.apache.spark.input
-
- org.apache.spark.internal.config - package org.apache.spark.internal.config
-
- org.apache.spark.io - package org.apache.spark.io
-
IO codecs used for compression.
- org.apache.spark.launcher - package org.apache.spark.launcher
-
Library for launching Spark applications.
- org.apache.spark.mapred - package org.apache.spark.mapred
-
- org.apache.spark.metrics.source - package org.apache.spark.metrics.source
-
- org.apache.spark.ml - package org.apache.spark.ml
-
DataFrame-based machine learning APIs to let users quickly assemble and configure practical
machine learning pipelines.
- org.apache.spark.ml.ann - package org.apache.spark.ml.ann
-
- org.apache.spark.ml.attribute - package org.apache.spark.ml.attribute
-
ML attributes
- org.apache.spark.ml.classification - package org.apache.spark.ml.classification
-
- org.apache.spark.ml.clustering - package org.apache.spark.ml.clustering
-
- org.apache.spark.ml.evaluation - package org.apache.spark.ml.evaluation
-
- org.apache.spark.ml.feature - package org.apache.spark.ml.feature
-
Feature transformers
The `ml.feature` package provides common feature transformers that help convert raw data or
features into more suitable forms for model fitting.
- org.apache.spark.ml.impl - package org.apache.spark.ml.impl
-
- org.apache.spark.ml.linalg - package org.apache.spark.ml.linalg
-
- org.apache.spark.ml.param - package org.apache.spark.ml.param
-
- org.apache.spark.ml.param.shared - package org.apache.spark.ml.param.shared
-
- org.apache.spark.ml.r - package org.apache.spark.ml.r
-
- org.apache.spark.ml.recommendation - package org.apache.spark.ml.recommendation
-
- org.apache.spark.ml.regression - package org.apache.spark.ml.regression
-
- org.apache.spark.ml.source.libsvm - package org.apache.spark.ml.source.libsvm
-
- org.apache.spark.ml.stat.distribution - package org.apache.spark.ml.stat.distribution
-
- org.apache.spark.ml.tree - package org.apache.spark.ml.tree
-
- org.apache.spark.ml.tree.impl - package org.apache.spark.ml.tree.impl
-
- org.apache.spark.ml.tuning - package org.apache.spark.ml.tuning
-
- org.apache.spark.ml.util - package org.apache.spark.ml.util
-
- org.apache.spark.mllib - package org.apache.spark.mllib
-
RDD-based machine learning APIs (in maintenance mode).
- org.apache.spark.mllib.classification - package org.apache.spark.mllib.classification
-
- org.apache.spark.mllib.classification.impl - package org.apache.spark.mllib.classification.impl
-
- org.apache.spark.mllib.clustering - package org.apache.spark.mllib.clustering
-
- org.apache.spark.mllib.evaluation - package org.apache.spark.mllib.evaluation
-
- org.apache.spark.mllib.evaluation.binary - package org.apache.spark.mllib.evaluation.binary
-
- org.apache.spark.mllib.feature - package org.apache.spark.mllib.feature
-
- org.apache.spark.mllib.fpm - package org.apache.spark.mllib.fpm
-
- org.apache.spark.mllib.linalg - package org.apache.spark.mllib.linalg
-
- org.apache.spark.mllib.linalg.distributed - package org.apache.spark.mllib.linalg.distributed
-
- org.apache.spark.mllib.optimization - package org.apache.spark.mllib.optimization
-
- org.apache.spark.mllib.pmml - package org.apache.spark.mllib.pmml
-
- org.apache.spark.mllib.pmml.export - package org.apache.spark.mllib.pmml.export
-
- org.apache.spark.mllib.random - package org.apache.spark.mllib.random
-
- org.apache.spark.mllib.rdd - package org.apache.spark.mllib.rdd
-
- org.apache.spark.mllib.recommendation - package org.apache.spark.mllib.recommendation
-
- org.apache.spark.mllib.regression - package org.apache.spark.mllib.regression
-
- org.apache.spark.mllib.regression.impl - package org.apache.spark.mllib.regression.impl
-
- org.apache.spark.mllib.stat - package org.apache.spark.mllib.stat
-
- org.apache.spark.mllib.stat.correlation - package org.apache.spark.mllib.stat.correlation
-
- org.apache.spark.mllib.stat.distribution - package org.apache.spark.mllib.stat.distribution
-
- org.apache.spark.mllib.stat.test - package org.apache.spark.mllib.stat.test
-
- org.apache.spark.mllib.tree - package org.apache.spark.mllib.tree
-
- org.apache.spark.mllib.tree.configuration - package org.apache.spark.mllib.tree.configuration
-
- org.apache.spark.mllib.tree.impurity - package org.apache.spark.mllib.tree.impurity
-
- org.apache.spark.mllib.tree.loss - package org.apache.spark.mllib.tree.loss
-
- org.apache.spark.mllib.tree.model - package org.apache.spark.mllib.tree.model
-
- org.apache.spark.mllib.util - package org.apache.spark.mllib.util
-
- org.apache.spark.partial - package org.apache.spark.partial
-
- org.apache.spark.rdd - package org.apache.spark.rdd
-
Provides implementation's of various RDDs.
- org.apache.spark.rpc.netty - package org.apache.spark.rpc.netty
-
- org.apache.spark.scheduler - package org.apache.spark.scheduler
-
Spark's DAG scheduler.
- org.apache.spark.scheduler.cluster - package org.apache.spark.scheduler.cluster
-
- org.apache.spark.scheduler.cluster.mesos - package org.apache.spark.scheduler.cluster.mesos
-
- org.apache.spark.scheduler.local - package org.apache.spark.scheduler.local
-
- org.apache.spark.security - package org.apache.spark.security
-
- org.apache.spark.serializer - package org.apache.spark.serializer
-
Pluggable serializers for RDD and shuffle data.
- org.apache.spark.sql - package org.apache.spark.sql
-
- org.apache.spark.sql.api.java - package org.apache.spark.sql.api.java
-
Allows the execution of relational queries, including those expressed in SQL using Spark.
- org.apache.spark.sql.api.r - package org.apache.spark.sql.api.r
-
- org.apache.spark.sql.catalog - package org.apache.spark.sql.catalog
-
- org.apache.spark.sql.expressions - package org.apache.spark.sql.expressions
-
- org.apache.spark.sql.expressions.javalang - package org.apache.spark.sql.expressions.javalang
-
- org.apache.spark.sql.expressions.scalalang - package org.apache.spark.sql.expressions.scalalang
-
- org.apache.spark.sql.hive - package org.apache.spark.sql.hive
-
- org.apache.spark.sql.hive.execution - package org.apache.spark.sql.hive.execution
-
- org.apache.spark.sql.hive.orc - package org.apache.spark.sql.hive.orc
-
- org.apache.spark.sql.internal - package org.apache.spark.sql.internal
-
All classes in this package are considered an internal API to Spark and
are subject to change between minor releases.
- org.apache.spark.sql.jdbc - package org.apache.spark.sql.jdbc
-
- org.apache.spark.sql.sources - package org.apache.spark.sql.sources
-
- org.apache.spark.sql.streaming - package org.apache.spark.sql.streaming
-
- org.apache.spark.sql.types - package org.apache.spark.sql.types
-
- org.apache.spark.sql.util - package org.apache.spark.sql.util
-
- org.apache.spark.status.api.v1 - package org.apache.spark.status.api.v1
-
- org.apache.spark.storage - package org.apache.spark.storage
-
- org.apache.spark.storage.memory - package org.apache.spark.storage.memory
-
- org.apache.spark.streaming - package org.apache.spark.streaming
-
- org.apache.spark.streaming.api.java - package org.apache.spark.streaming.api.java
-
Java APIs for spark streaming.
- org.apache.spark.streaming.dstream - package org.apache.spark.streaming.dstream
-
Various implementations of DStreams.
- org.apache.spark.streaming.flume - package org.apache.spark.streaming.flume
-
Spark streaming receiver for Flume.
- org.apache.spark.streaming.kafka - package org.apache.spark.streaming.kafka
-
Kafka receiver for spark streaming.
- org.apache.spark.streaming.kinesis - package org.apache.spark.streaming.kinesis
-
- org.apache.spark.streaming.receiver - package org.apache.spark.streaming.receiver
-
- org.apache.spark.streaming.scheduler - package org.apache.spark.streaming.scheduler
-
- org.apache.spark.streaming.ui - package org.apache.spark.streaming.ui
-
- org.apache.spark.streaming.util - package org.apache.spark.streaming.util
-
- org.apache.spark.ui - package org.apache.spark.ui
-
- org.apache.spark.ui.env - package org.apache.spark.ui.env
-
- org.apache.spark.ui.exec - package org.apache.spark.ui.exec
-
- org.apache.spark.ui.jobs - package org.apache.spark.ui.jobs
-
- org.apache.spark.ui.storage - package org.apache.spark.ui.storage
-
- org.apache.spark.util - package org.apache.spark.util
-
Spark utilities.
- org.apache.spark.util.io - package org.apache.spark.util.io
-
- org.apache.spark.util.random - package org.apache.spark.util.random
-
Utilities for random number generation.
- org.apache.spark.util.sketch - package org.apache.spark.util.sketch
-
- origin() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- origin() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- origin() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- originalMax() - Method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- originalMin() - Method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- orNull() - Method in class org.apache.spark.api.java.Optional
-
- other() - Method in class org.apache.spark.scheduler.RuntimePercentage
-
- otherVertexAttr(long) - Method in class org.apache.spark.graphx.EdgeTriplet
-
Given one vertex in the edge return the other vertex.
- otherVertexId(long) - Method in class org.apache.spark.graphx.Edge
-
Given one vertex in the edge return the other vertex.
- otherwise(Object) - Method in class org.apache.spark.sql.Column
-
Evaluates a list of conditions and returns one of multiple possible result expressions.
- Out() - Static method in class org.apache.spark.graphx.EdgeDirection
-
Edges originating from a vertex.
- outDegrees() - Method in class org.apache.spark.graphx.GraphOps
-
The out-degree of each vertex in the graph.
- outerJoinVertices(RDD<Tuple2<Object, U>>, Function3<Object, VD, Option<U>, VD2>, ClassTag<U>, ClassTag<VD2>, Predef.$eq$colon$eq<VD, VD2>) - Method in class org.apache.spark.graphx.Graph
-
Joins the vertices with entries in the table RDD and merges the results using mapFunc.
- outerJoinVertices(RDD<Tuple2<Object, U>>, Function3<Object, VD, Option<U>, VD2>, ClassTag<U>, ClassTag<VD2>, Predef.$eq$colon$eq<VD, VD2>) - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- outerJoinVertices$default$5(RDD<Tuple2<Object, U>>, Function3<Object, VD, Option<U>, VD2>) - Static method in class org.apache.spark.graphx.impl.GraphImpl
-
- output() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- output() - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- output() - Method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- OUTPUT() - Static method in class org.apache.spark.ui.ToolTips
-
- OUTPUT_METRICS_PREFIX() - Static method in class org.apache.spark.InternalAccumulator
-
- outputBytes() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
-
- outputBytes() - Method in class org.apache.spark.status.api.v1.StageData
-
- outputBytes() - Method in class org.apache.spark.ui.jobs.UIData.ExecutorSummary
-
- outputBytes() - Method in class org.apache.spark.ui.jobs.UIData.StageUIData
-
- outputCol() - Static method in class org.apache.spark.ml.feature.Binarizer
-
- outputCol() - Static method in class org.apache.spark.ml.feature.Bucketizer
-
- outputCol() - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- outputCol() - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- outputCol() - Static method in class org.apache.spark.ml.feature.CountVectorizer
-
- outputCol() - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- outputCol() - Static method in class org.apache.spark.ml.feature.DCT
-
- outputCol() - Static method in class org.apache.spark.ml.feature.ElementwiseProduct
-
- outputCol() - Static method in class org.apache.spark.ml.feature.HashingTF
-
- outputCol() - Static method in class org.apache.spark.ml.feature.IDF
-
- outputCol() - Static method in class org.apache.spark.ml.feature.IDFModel
-
- outputCol() - Static method in class org.apache.spark.ml.feature.IndexToString
-
- outputCol() - Static method in class org.apache.spark.ml.feature.Interaction
-
- outputCol() - Static method in class org.apache.spark.ml.feature.MaxAbsScaler
-
- outputCol() - Static method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- outputCol() - Static method in class org.apache.spark.ml.feature.MinMaxScaler
-
- outputCol() - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- outputCol() - Static method in class org.apache.spark.ml.feature.NGram
-
- outputCol() - Static method in class org.apache.spark.ml.feature.Normalizer
-
- outputCol() - Static method in class org.apache.spark.ml.feature.OneHotEncoder
-
- outputCol() - Static method in class org.apache.spark.ml.feature.PCA
-
- outputCol() - Static method in class org.apache.spark.ml.feature.PCAModel
-
- outputCol() - Static method in class org.apache.spark.ml.feature.PolynomialExpansion
-
- outputCol() - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- outputCol() - Static method in class org.apache.spark.ml.feature.RegexTokenizer
-
- outputCol() - Static method in class org.apache.spark.ml.feature.StandardScaler
-
- outputCol() - Static method in class org.apache.spark.ml.feature.StandardScalerModel
-
- outputCol() - Static method in class org.apache.spark.ml.feature.StopWordsRemover
-
- outputCol() - Static method in class org.apache.spark.ml.feature.StringIndexer
-
- outputCol() - Static method in class org.apache.spark.ml.feature.StringIndexerModel
-
- outputCol() - Static method in class org.apache.spark.ml.feature.Tokenizer
-
- outputCol() - Static method in class org.apache.spark.ml.feature.VectorAssembler
-
- outputCol() - Static method in class org.apache.spark.ml.feature.VectorIndexer
-
- outputCol() - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- outputCol() - Static method in class org.apache.spark.ml.feature.VectorSlicer
-
- outputCol() - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- outputCol() - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- OutputCommitCoordinationMessage - Interface in org.apache.spark.scheduler
-
- outputCommitCoordinator() - Method in class org.apache.spark.SparkEnv
-
- outputEncoder() - Method in class org.apache.spark.sql.expressions.Aggregator
-
Specifies the Encoder for the final ouput value type.
- outputFormat() - Method in class org.apache.spark.sql.internal.HiveSerDe
-
- OutputMetricDistributions - Class in org.apache.spark.status.api.v1
-
- OutputMetrics - Class in org.apache.spark.status.api.v1
-
- outputMetrics() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
-
- outputMetrics() - Method in class org.apache.spark.status.api.v1.TaskMetrics
-
- outputMetrics() - Method in class org.apache.spark.ui.jobs.UIData.TaskMetricsUIData
-
- outputMode(OutputMode) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
-
:: Experimental ::
Specifies how data of a streaming DataFrame/Dataset is written to a streaming sink.
- outputMode(String) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
-
:: Experimental ::
Specifies how data of a streaming DataFrame/Dataset is written to a streaming sink.
- OutputMode - Class in org.apache.spark.sql.streaming
-
:: Experimental ::
OutputMode is used to what data will be written to a streaming sink when there is
new data available in a streaming DataFrame/Dataset.
- OutputMode() - Constructor for class org.apache.spark.sql.streaming.OutputMode
-
- OutputOperationInfo - Class in org.apache.spark.streaming.scheduler
-
:: DeveloperApi ::
Class having information on output operations.
- OutputOperationInfo(Time, int, String, String, Option<Object>, Option<Object>, Option<String>) - Constructor for class org.apache.spark.streaming.scheduler.OutputOperationInfo
-
- outputOperationInfo() - Method in class org.apache.spark.streaming.scheduler.StreamingListenerOutputOperationCompleted
-
- outputOperationInfo() - Method in class org.apache.spark.streaming.scheduler.StreamingListenerOutputOperationStarted
-
- outputOperationInfos() - Method in class org.apache.spark.streaming.scheduler.BatchInfo
-
- outputOrdering() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- outputOrdering() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- outputPartitioning() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- outputPartitioning() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- outputRecords() - Method in class org.apache.spark.status.api.v1.StageData
-
- outputRecords() - Method in class org.apache.spark.ui.jobs.UIData.ExecutorSummary
-
- outputRecords() - Method in class org.apache.spark.ui.jobs.UIData.StageUIData
-
- outputRowFormat() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- outputRowFormatMap() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- outputSerdeClass() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- outputSerdeProps() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- outputSet() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- outputSet() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- outputSet() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- over(WindowSpec) - Method in class org.apache.spark.sql.Column
-
Define a windowing column.
- over() - Method in class org.apache.spark.sql.Column
-
Define a empty analytic clause.
- overwrite() - Method in class org.apache.spark.ml.util.MLWriter
-
Overwrites if the output path already exists.
- overwrite() - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- p() - Method in class org.apache.spark.ml.feature.Normalizer
-
Normalization in L^p^ space.
- padTo(int, B, CanBuildFrom<Repr, B, That>) - Static method in class org.apache.spark.sql.types.StructType
-
- pageRank(double, double) - Method in class org.apache.spark.graphx.GraphOps
-
Run a dynamic version of PageRank returning a graph with vertex attributes containing the
PageRank and edge attributes containing the normalized edge weight.
- PageRank - Class in org.apache.spark.graphx.lib
-
PageRank algorithm implementation.
- PageRank() - Constructor for class org.apache.spark.graphx.lib.PageRank
-
- PairDStreamFunctions<K,V> - Class in org.apache.spark.streaming.dstream
-
Extra functions available on DStream of (key, value) pairs through an implicit conversion.
- PairDStreamFunctions(DStream<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>, Ordering<K>) - Constructor for class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
- PairFlatMapFunction<T,K,V> - Interface in org.apache.spark.api.java.function
-
A function that returns zero or more key-value pair records from each input record.
- PairFunction<T,K,V> - Interface in org.apache.spark.api.java.function
-
A function that returns key-value pairs (Tuple2<K, V>), and can be used to
construct PairRDDs.
- PairRDDFunctions<K,V> - Class in org.apache.spark.rdd
-
Extra functions available on RDDs of (key, value) pairs through an implicit conversion.
- PairRDDFunctions(RDD<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>, Ordering<K>) - Constructor for class org.apache.spark.rdd.PairRDDFunctions
-
- PairwiseRRDD<T> - Class in org.apache.spark.api.r
-
Form an RDD[(Int, Array[Byte])] from key-value pairs returned from R.
- PairwiseRRDD(RDD<T>, int, byte[], String, byte[], Object[], ClassTag<T>) - Constructor for class org.apache.spark.api.r.PairwiseRRDD
-
- par() - Static method in class org.apache.spark.sql.types.StructType
-
- parallelize(List<T>, int) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Distribute a local Scala collection to form an RDD.
- parallelize(List<T>) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Distribute a local Scala collection to form an RDD.
- parallelize(Seq<T>, int, ClassTag<T>) - Method in class org.apache.spark.SparkContext
-
Distribute a local Scala collection to form an RDD.
- parallelizeDoubles(List<Double>, int) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Distribute a local Scala collection to form an RDD.
- parallelizeDoubles(List<Double>) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Distribute a local Scala collection to form an RDD.
- parallelizePairs(List<Tuple2<K, V>>, int) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Distribute a local Scala collection to form an RDD.
- parallelizePairs(List<Tuple2<K, V>>) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Distribute a local Scala collection to form an RDD.
- Param<T> - Class in org.apache.spark.ml.param
-
:: DeveloperApi ::
A param with self-contained documentation and optionally default value.
- Param(String, String, String, Function1<T, Object>) - Constructor for class org.apache.spark.ml.param.Param
-
- Param(Identifiable, String, String, Function1<T, Object>) - Constructor for class org.apache.spark.ml.param.Param
-
- Param(String, String, String) - Constructor for class org.apache.spark.ml.param.Param
-
- Param(Identifiable, String, String) - Constructor for class org.apache.spark.ml.param.Param
-
- param() - Method in class org.apache.spark.ml.param.ParamPair
-
- ParamGridBuilder - Class in org.apache.spark.ml.tuning
-
Builder for a param grid used in grid search-based model selection.
- ParamGridBuilder() - Constructor for class org.apache.spark.ml.tuning.ParamGridBuilder
-
- ParamMap - Class in org.apache.spark.ml.param
-
A param to value map.
- ParamMap() - Constructor for class org.apache.spark.ml.param.ParamMap
-
Creates an empty param map.
- paramMap() - Method in interface org.apache.spark.ml.param.Params
-
Internal param map for user-supplied values.
- ParamPair<T> - Class in org.apache.spark.ml.param
-
A param and its value.
- ParamPair(Param<T>, T) - Constructor for class org.apache.spark.ml.param.ParamPair
-
- params() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- params() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- params() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- params() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- params() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- params() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- params() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- params() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- params() - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- params() - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- params() - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- params() - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- params() - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- params() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- params() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- params() - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- params() - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- params() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- params() - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- params() - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- params() - Static method in class org.apache.spark.ml.clustering.KMeans
-
- params() - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- params() - Static method in class org.apache.spark.ml.clustering.LDA
-
- params() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- params() - Static method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- params() - Static method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
- params() - Static method in class org.apache.spark.ml.evaluation.RegressionEvaluator
-
- params() - Static method in class org.apache.spark.ml.feature.Binarizer
-
- params() - Static method in class org.apache.spark.ml.feature.Bucketizer
-
- params() - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- params() - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- params() - Static method in class org.apache.spark.ml.feature.ColumnPruner
-
- params() - Static method in class org.apache.spark.ml.feature.CountVectorizer
-
- params() - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- params() - Static method in class org.apache.spark.ml.feature.DCT
-
- params() - Static method in class org.apache.spark.ml.feature.ElementwiseProduct
-
- params() - Static method in class org.apache.spark.ml.feature.HashingTF
-
- params() - Static method in class org.apache.spark.ml.feature.IDF
-
- params() - Static method in class org.apache.spark.ml.feature.IDFModel
-
- params() - Static method in class org.apache.spark.ml.feature.IndexToString
-
- params() - Static method in class org.apache.spark.ml.feature.Interaction
-
- params() - Static method in class org.apache.spark.ml.feature.MaxAbsScaler
-
- params() - Static method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- params() - Static method in class org.apache.spark.ml.feature.MinMaxScaler
-
- params() - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- params() - Static method in class org.apache.spark.ml.feature.NGram
-
- params() - Static method in class org.apache.spark.ml.feature.Normalizer
-
- params() - Static method in class org.apache.spark.ml.feature.OneHotEncoder
-
- params() - Static method in class org.apache.spark.ml.feature.PCA
-
- params() - Static method in class org.apache.spark.ml.feature.PCAModel
-
- params() - Static method in class org.apache.spark.ml.feature.PolynomialExpansion
-
- params() - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- params() - Static method in class org.apache.spark.ml.feature.RegexTokenizer
-
- params() - Static method in class org.apache.spark.ml.feature.RFormula
-
- params() - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- params() - Static method in class org.apache.spark.ml.feature.SQLTransformer
-
- params() - Static method in class org.apache.spark.ml.feature.StandardScaler
-
- params() - Static method in class org.apache.spark.ml.feature.StandardScalerModel
-
- params() - Static method in class org.apache.spark.ml.feature.StopWordsRemover
-
- params() - Static method in class org.apache.spark.ml.feature.StringIndexer
-
- params() - Static method in class org.apache.spark.ml.feature.StringIndexerModel
-
- params() - Static method in class org.apache.spark.ml.feature.Tokenizer
-
- params() - Static method in class org.apache.spark.ml.feature.VectorAssembler
-
- params() - Static method in class org.apache.spark.ml.feature.VectorAttributeRewriter
-
- params() - Static method in class org.apache.spark.ml.feature.VectorIndexer
-
- params() - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- params() - Static method in class org.apache.spark.ml.feature.VectorSlicer
-
- params() - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- params() - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- Params - Interface in org.apache.spark.ml.param
-
:: DeveloperApi ::
Trait for components that take parameters.
- params() - Method in interface org.apache.spark.ml.param.Params
-
Returns all params sorted by their names.
- params() - Static method in class org.apache.spark.ml.Pipeline
-
- params() - Static method in class org.apache.spark.ml.PipelineModel
-
- params() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- params() - Static method in class org.apache.spark.ml.recommendation.ALSModel
-
- params() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- params() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- params() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- params() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- params() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- params() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- params() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- params() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- params() - Static method in class org.apache.spark.ml.regression.IsotonicRegression
-
- params() - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- params() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- params() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- params() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- params() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- params() - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- params() - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- params() - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- params() - Static method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
-
- ParamValidators - Class in org.apache.spark.ml.param
-
:: DeveloperApi ::
Factory methods for common validation functions for Param.isValid.
- ParamValidators() - Constructor for class org.apache.spark.ml.param.ParamValidators
-
- parent() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- parent() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- parent() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- parent() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- parent() - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- parent() - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- parent() - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- parent() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- parent() - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- parent() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- parent() - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- parent() - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- parent() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- parent() - Static method in class org.apache.spark.ml.feature.Bucketizer
-
- parent() - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- parent() - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- parent() - Static method in class org.apache.spark.ml.feature.IDFModel
-
- parent() - Static method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- parent() - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- parent() - Static method in class org.apache.spark.ml.feature.PCAModel
-
- parent() - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- parent() - Static method in class org.apache.spark.ml.feature.StandardScalerModel
-
- parent() - Static method in class org.apache.spark.ml.feature.StringIndexerModel
-
- parent() - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- parent() - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- parent() - Method in class org.apache.spark.ml.Model
-
The parent estimator that produced this model.
- parent() - Static method in class org.apache.spark.ml.param.DoubleParam
-
- parent() - Static method in class org.apache.spark.ml.param.FloatParam
-
- parent() - Method in class org.apache.spark.ml.param.Param
-
- parent() - Static method in class org.apache.spark.ml.PipelineModel
-
- parent() - Static method in class org.apache.spark.ml.recommendation.ALSModel
-
- parent() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- parent() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- parent() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- parent() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- parent() - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- parent() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- parent() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- parent() - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- parent() - Static method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.feature.Bucketizer
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.feature.IDFModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.feature.PCAModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.feature.StandardScalerModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.feature.StringIndexerModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.PipelineModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.recommendation.ALSModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- parent_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
-
- parentIds() - Method in class org.apache.spark.scheduler.StageInfo
-
- parentIds() - Method in class org.apache.spark.storage.RDDInfo
-
- parentIndex(int) - Static method in class org.apache.spark.mllib.tree.model.Node
-
Get the parent index of the given node, or 0 if it is the root.
- parquet(String...) - Method in class org.apache.spark.sql.DataFrameReader
-
Loads a Parquet file, returning the result as a DataFrame.
- parquet(String) - Method in class org.apache.spark.sql.DataFrameReader
-
Loads a Parquet file, returning the result as a DataFrame.
- parquet(Seq<String>) - Method in class org.apache.spark.sql.DataFrameReader
-
Loads a Parquet file, returning the result as a DataFrame.
- parquet(String) - Method in class org.apache.spark.sql.DataFrameWriter
-
Saves the content of the DataFrame in Parquet format at the specified path.
- parquet(String) - Method in class org.apache.spark.sql.streaming.DataStreamReader
-
:: Experimental ::
Loads a Parquet file stream, returning the result as a DataFrame.
- parquetFile(String...) - Method in class org.apache.spark.sql.SQLContext
-
Deprecated.
As of 1.4.0, replaced by read().parquet().
- parquetFile(Seq<String>) - Method in class org.apache.spark.sql.SQLContext
-
Deprecated.
Use read.parquet() instead. Since 1.4.0.
- parse(String) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- parse(String) - Static method in class org.apache.spark.mllib.linalg.Vectors
-
Parses a string resulted from
Vector.toString into a
Vector.
- parse(String) - Static method in class org.apache.spark.mllib.regression.LabeledPoint
-
Parses a string resulted from
LabeledPoint#toString into
an
LabeledPoint.
- parse(String) - Static method in class org.apache.spark.mllib.util.NumericParser
-
Parses a string into a Double, an Array[Double], or a Seq[Any].
- parseAll(Parsers.Parser<T>, Reader<Object>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- parseAll(Parsers.Parser<T>, Reader) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- parseAll(Parsers.Parser<T>, CharSequence) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- parseHostPort(String) - Static method in class org.apache.spark.util.Utils
-
- parseIgnoreCase(Class<E>, String) - Static method in class org.apache.spark.util.EnumUtil
-
- parsePortMappingsSpec(String) - Static method in class org.apache.spark.scheduler.cluster.mesos.MesosSchedulerBackendUtil
-
Parse a comma-delimited list of port mapping specs, each of which
takes the form host_port:container_port[:udp|:tcp]
- Parser(Function1<Reader<Object>, Parsers.ParseResult<T>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- parseStandaloneMasterUrls(String) - Static method in class org.apache.spark.util.Utils
-
Split the comma delimited string of master URLs into a list.
- parseVolumesSpec(String) - Static method in class org.apache.spark.scheduler.cluster.mesos.MesosSchedulerBackendUtil
-
Parse a comma-delimited list of volume specs, each of which
takes the form [host-dir:]container-dir[:rw|:ro].
- PartialResult<R> - Class in org.apache.spark.partial
-
- PartialResult(R, boolean) - Constructor for class org.apache.spark.partial.PartialResult
-
- Partition - Interface in org.apache.spark
-
An identifier for a partition in an RDD.
- partition() - Method in class org.apache.spark.scheduler.AskPermissionToCommitOutput
-
- partition() - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- partition(Function1<A, Object>) - Static method in class org.apache.spark.sql.types.StructType
-
- partition() - Method in class org.apache.spark.streaming.kafka.OffsetRange
-
- partitionBy(Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return a copy of the RDD partitioned using the specified partitioner.
- partitionBy(PartitionStrategy) - Method in class org.apache.spark.graphx.Graph
-
Repartitions the edges in the graph according to partitionStrategy.
- partitionBy(PartitionStrategy, int) - Method in class org.apache.spark.graphx.Graph
-
Repartitions the edges in the graph according to partitionStrategy.
- partitionBy(PartitionStrategy) - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- partitionBy(PartitionStrategy, int) - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- partitionBy(Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Return a copy of the RDD partitioned using the specified partitioner.
- partitionBy(String...) - Method in class org.apache.spark.sql.DataFrameWriter
-
Partitions the output by the given columns on the file system.
- partitionBy(Seq<String>) - Method in class org.apache.spark.sql.DataFrameWriter
-
Partitions the output by the given columns on the file system.
- partitionBy(String, String...) - Static method in class org.apache.spark.sql.expressions.Window
-
Creates a
WindowSpec with the partitioning defined.
- partitionBy(Column...) - Static method in class org.apache.spark.sql.expressions.Window
-
Creates a
WindowSpec with the partitioning defined.
- partitionBy(String, Seq<String>) - Static method in class org.apache.spark.sql.expressions.Window
-
Creates a
WindowSpec with the partitioning defined.
- partitionBy(Seq<Column>) - Static method in class org.apache.spark.sql.expressions.Window
-
Creates a
WindowSpec with the partitioning defined.
- partitionBy(String, String...) - Method in class org.apache.spark.sql.expressions.WindowSpec
-
- partitionBy(Column...) - Method in class org.apache.spark.sql.expressions.WindowSpec
-
- partitionBy(String, Seq<String>) - Method in class org.apache.spark.sql.expressions.WindowSpec
-
- partitionBy(Seq<Column>) - Method in class org.apache.spark.sql.expressions.WindowSpec
-
- partitionBy(String...) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
-
Partitions the output by the given columns on the file system.
- partitionBy(Seq<String>) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
-
Partitions the output by the given columns on the file system.
- PartitionCoalescer - Interface in org.apache.spark.rdd
-
::DeveloperApi::
A PartitionCoalescer defines how to coalesce the partitions of a given RDD.
- partitioner() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- partitioner() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- partitioner() - Static method in class org.apache.spark.api.java.JavaRDD
-
- partitioner() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
The partitioner of this RDD.
- partitioner() - Static method in class org.apache.spark.api.r.RRDD
-
- partitioner() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- partitioner() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
If partitionsRDD already has a partitioner, use it.
- partitioner() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- partitioner() - Static method in class org.apache.spark.graphx.VertexRDD
-
- Partitioner - Class in org.apache.spark
-
An object that defines how the elements in a key-value pair RDD are partitioned by key.
- Partitioner() - Constructor for class org.apache.spark.Partitioner
-
- partitioner() - Method in class org.apache.spark.rdd.CoGroupedRDD
-
- partitioner() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- partitioner() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- partitioner() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- partitioner() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- partitioner() - Method in class org.apache.spark.rdd.RDD
-
Optionally overridden by subclasses to specify how they are partitioned.
- partitioner() - Method in class org.apache.spark.rdd.ShuffledRDD
-
- partitioner() - Static method in class org.apache.spark.rdd.UnionRDD
-
- partitioner() - Method in class org.apache.spark.ShuffleDependency
-
- partitioner(Partitioner) - Method in class org.apache.spark.streaming.StateSpec
-
Set the partitioner by which the state RDDs generated by mapWithState will be partitioned.
- PartitionGroup - Class in org.apache.spark.rdd
-
::DeveloperApi::
A group of Partitions
param: prefLoc preferred location for the partition group
- PartitionGroup(Option<String>) - Constructor for class org.apache.spark.rdd.PartitionGroup
-
- partitionID() - Method in class org.apache.spark.TaskCommitDenied
-
- partitionId() - Method in class org.apache.spark.TaskContext
-
The ID of the RDD partition that is computed by this task.
- PartitionPruningRDD<T> - Class in org.apache.spark.rdd
-
:: DeveloperApi ::
A RDD used to prune RDD partitions/partitions so we can avoid launching tasks on
all partitions.
- PartitionPruningRDD(RDD<T>, Function1<Object, Object>, ClassTag<T>) - Constructor for class org.apache.spark.rdd.PartitionPruningRDD
-
- partitions() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- partitions() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- partitions() - Static method in class org.apache.spark.api.java.JavaRDD
-
- partitions() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Set of partitions in this RDD.
- partitions() - Static method in class org.apache.spark.api.r.RRDD
-
- partitions() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- partitions() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- partitions() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- partitions() - Static method in class org.apache.spark.graphx.VertexRDD
-
- partitions() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- partitions() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- partitions() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- partitions() - Method in class org.apache.spark.rdd.PartitionGroup
-
- partitions() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- partitions() - Method in class org.apache.spark.rdd.RDD
-
Get the array of partitions of this RDD, taking into account whether the
RDD is checkpointed or not.
- partitions() - Static method in class org.apache.spark.rdd.UnionRDD
-
- partitions() - Method in class org.apache.spark.status.api.v1.RDDStorageInfo
-
- partitionsRDD() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- partitionsRDD() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- PartitionStrategy - Interface in org.apache.spark.graphx
-
Represents the way edges are assigned to edge partitions based on their source and destination
vertex IDs.
- PartitionStrategy.CanonicalRandomVertexCut$ - Class in org.apache.spark.graphx
-
Assigns edges to partitions by hashing the source and destination vertex IDs in a canonical
direction, resulting in a random vertex cut that colocates all edges between two vertices,
regardless of direction.
- PartitionStrategy.CanonicalRandomVertexCut$() - Constructor for class org.apache.spark.graphx.PartitionStrategy.CanonicalRandomVertexCut$
-
- PartitionStrategy.EdgePartition1D$ - Class in org.apache.spark.graphx
-
Assigns edges to partitions using only the source vertex ID, colocating edges with the same
source.
- PartitionStrategy.EdgePartition1D$() - Constructor for class org.apache.spark.graphx.PartitionStrategy.EdgePartition1D$
-
- PartitionStrategy.EdgePartition2D$ - Class in org.apache.spark.graphx
-
Assigns edges to partitions using a 2D partitioning of the sparse edge adjacency matrix,
guaranteeing a 2 * sqrt(numParts) bound on vertex replication.
- PartitionStrategy.EdgePartition2D$() - Constructor for class org.apache.spark.graphx.PartitionStrategy.EdgePartition2D$
-
- PartitionStrategy.RandomVertexCut$ - Class in org.apache.spark.graphx
-
Assigns edges to partitions by hashing the source and destination vertex IDs, resulting in a
random vertex cut that colocates all same-direction edges between two vertices.
- PartitionStrategy.RandomVertexCut$() - Constructor for class org.apache.spark.graphx.PartitionStrategy.RandomVertexCut$
-
- partsWithLocs() - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer.PartitionLocations
-
- partsWithoutLocs() - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer.PartitionLocations
-
- patch(int, GenSeq<B>, int, CanBuildFrom<Repr, B, That>) - Static method in class org.apache.spark.sql.types.StructType
-
- path() - Method in class org.apache.spark.scheduler.InputFormatInfo
-
- path() - Method in class org.apache.spark.scheduler.SplitInfo
-
- pattern() - Method in class org.apache.spark.ml.feature.RegexTokenizer
-
Regex pattern used to match delimiters if gaps is true or tokens if gaps is false.
- pc() - Method in class org.apache.spark.ml.feature.PCAModel
-
- pc() - Method in class org.apache.spark.mllib.feature.PCAModel
-
- PCA - Class in org.apache.spark.ml.feature
-
PCA trains a model to project vectors to a lower dimensional space of the top PCA!.k
principal components.
- PCA(String) - Constructor for class org.apache.spark.ml.feature.PCA
-
- PCA() - Constructor for class org.apache.spark.ml.feature.PCA
-
- PCA - Class in org.apache.spark.mllib.feature
-
A feature transformer that projects vectors to a low-dimensional space using PCA.
- PCA(int) - Constructor for class org.apache.spark.mllib.feature.PCA
-
- PCAModel - Class in org.apache.spark.ml.feature
-
- PCAModel - Class in org.apache.spark.mllib.feature
-
Model fitted by
PCA that can project vectors to a low-dimensional space using PCA.
- pdf(Vector) - Method in class org.apache.spark.ml.stat.distribution.MultivariateGaussian
-
Returns density of this multivariate Gaussian at given point, x
- pdf(Vector) - Method in class org.apache.spark.mllib.stat.distribution.MultivariateGaussian
-
Returns density of this multivariate Gaussian at given point, x
- PEAK_EXECUTION_MEMORY() - Static method in class org.apache.spark.InternalAccumulator
-
- PEAK_EXECUTION_MEMORY() - Static method in class org.apache.spark.ui.jobs.TaskDetailsClassNames
-
- PEAK_EXECUTION_MEMORY() - Static method in class org.apache.spark.ui.ToolTips
-
- peakExecutionMemory() - Method in class org.apache.spark.ui.jobs.UIData.TaskMetricsUIData
-
- PEARSON() - Static method in class org.apache.spark.mllib.stat.test.ChiSqTest
-
- PearsonCorrelation - Class in org.apache.spark.mllib.stat.correlation
-
Compute Pearson correlation for two RDDs of the type RDD[Double] or the correlation matrix
for an RDD of the type RDD[Vector].
- PearsonCorrelation() - Constructor for class org.apache.spark.mllib.stat.correlation.PearsonCorrelation
-
- pendingStages() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- percent_rank() - Static method in class org.apache.spark.sql.functions
-
Window function: returns the relative rank (i.e.
- percentiles() - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- percentilesHeader() - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- permutations() - Static method in class org.apache.spark.sql.types.StructType
-
- persist(StorageLevel) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Set this RDD's storage level to persist its values across operations after the first time
it is computed.
- persist(StorageLevel) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Set this RDD's storage level to persist its values across operations after the first time
it is computed.
- persist(StorageLevel) - Method in class org.apache.spark.api.java.JavaRDD
-
Set this RDD's storage level to persist its values across operations after the first time
it is computed.
- persist(StorageLevel) - Static method in class org.apache.spark.api.r.RRDD
-
- persist() - Static method in class org.apache.spark.api.r.RRDD
-
- persist(StorageLevel) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- persist() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- persist(StorageLevel) - Method in class org.apache.spark.graphx.Graph
-
Caches the vertices and edges associated with this graph at the specified storage level,
ignoring any target storage levels previously set.
- persist(StorageLevel) - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
Persists the edge partitions at the specified storage level, ignoring any existing target
storage level.
- persist(StorageLevel) - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- persist(StorageLevel) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
Persists the vertex partitions at the specified storage level, ignoring any existing target
storage level.
- persist(StorageLevel) - Static method in class org.apache.spark.graphx.VertexRDD
-
- persist() - Static method in class org.apache.spark.graphx.VertexRDD
-
- persist(StorageLevel) - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
-
Persists the underlying RDD with the specified storage level.
- persist(StorageLevel) - Method in class org.apache.spark.rdd.HadoopRDD
-
- persist(StorageLevel) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- persist() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- persist(StorageLevel) - Method in class org.apache.spark.rdd.NewHadoopRDD
-
- persist(StorageLevel) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- persist() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- persist(StorageLevel) - Method in class org.apache.spark.rdd.RDD
-
Set this RDD's storage level to persist its values across operations after the first time
it is computed.
- persist() - Method in class org.apache.spark.rdd.RDD
-
Persist this RDD with the default storage level (`MEMORY_ONLY`).
- persist(StorageLevel) - Static method in class org.apache.spark.rdd.UnionRDD
-
- persist() - Static method in class org.apache.spark.rdd.UnionRDD
-
- persist() - Method in class org.apache.spark.sql.Dataset
-
Persist this Dataset with the default storage level (MEMORY_AND_DISK).
- persist(StorageLevel) - Method in class org.apache.spark.sql.Dataset
-
Persist this Dataset with the given storage level.
- persist() - Method in class org.apache.spark.streaming.api.java.JavaDStream
-
Persist RDDs of this DStream with the default storage level (MEMORY_ONLY_SER)
- persist(StorageLevel) - Method in class org.apache.spark.streaming.api.java.JavaDStream
-
Persist the RDDs of this DStream with the given storage level
- persist() - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- persist(StorageLevel) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- persist() - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Persist RDDs of this DStream with the default storage level (MEMORY_ONLY_SER)
- persist(StorageLevel) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Persist the RDDs of this DStream with the given storage level
- persist() - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- persist(StorageLevel) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- persist() - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- persist(StorageLevel) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- persist() - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- persist(StorageLevel) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- persist(StorageLevel) - Method in class org.apache.spark.streaming.dstream.DStream
-
Persist the RDDs of this DStream with the given storage level
- persist() - Method in class org.apache.spark.streaming.dstream.DStream
-
Persist RDDs of this DStream with the default storage level (MEMORY_ONLY_SER)
- persist$default$1() - Static method in class org.apache.spark.graphx.impl.GraphImpl
-
- personalizedPageRank(long, double, double) - Method in class org.apache.spark.graphx.GraphOps
-
Run personalized PageRank for a given vertex, such that all random walks
are started relative to the source node.
- phrase(Parsers.Parser<T>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- pi() - Method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- pi() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel
-
- pi() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0$.Data
-
- pi() - Method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$.Data
-
- pickBin(Partition, RDD<?>, double, DefaultPartitionCoalescer.PartitionLocations) - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
-
Takes a parent RDD partition and decides which of the partition groups to put it in
Takes locality into account, but also uses power of 2 choices to load balance
It strikes a balance between the two using the balanceSlack variable
- pickRandomVertex() - Method in class org.apache.spark.graphx.GraphOps
-
Picks a random vertex from the graph and returns its ID.
- pipe(String) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- pipe(List<String>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- pipe(List<String>, Map<String, String>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- pipe(List<String>, Map<String, String>, boolean, int) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- pipe(List<String>, Map<String, String>, boolean, int, String) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- pipe(String) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- pipe(List<String>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- pipe(List<String>, Map<String, String>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- pipe(List<String>, Map<String, String>, boolean, int) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- pipe(List<String>, Map<String, String>, boolean, int, String) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- pipe(String) - Static method in class org.apache.spark.api.java.JavaRDD
-
- pipe(List<String>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- pipe(List<String>, Map<String, String>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- pipe(List<String>, Map<String, String>, boolean, int) - Static method in class org.apache.spark.api.java.JavaRDD
-
- pipe(List<String>, Map<String, String>, boolean, int, String) - Static method in class org.apache.spark.api.java.JavaRDD
-
- pipe(String) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return an RDD created by piping elements to a forked external process.
- pipe(List<String>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return an RDD created by piping elements to a forked external process.
- pipe(List<String>, Map<String, String>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return an RDD created by piping elements to a forked external process.
- pipe(List<String>, Map<String, String>, boolean, int) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return an RDD created by piping elements to a forked external process.
- pipe(List<String>, Map<String, String>, boolean, int, String) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Return an RDD created by piping elements to a forked external process.
- pipe(String) - Static method in class org.apache.spark.api.r.RRDD
-
- pipe(String, Map<String, String>) - Static method in class org.apache.spark.api.r.RRDD
-
- pipe(Seq<String>, Map<String, String>, Function1<Function1<String, BoxedUnit>, BoxedUnit>, Function2<T, Function1<String, BoxedUnit>, BoxedUnit>, boolean, int, String) - Static method in class org.apache.spark.api.r.RRDD
-
- pipe(String) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- pipe(String, Map<String, String>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- pipe(Seq<String>, Map<String, String>, Function1<Function1<String, BoxedUnit>, BoxedUnit>, Function2<T, Function1<String, BoxedUnit>, BoxedUnit>, boolean, int, String) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- pipe(String) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- pipe(String, Map<String, String>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- pipe(Seq<String>, Map<String, String>, Function1<Function1<String, BoxedUnit>, BoxedUnit>, Function2<T, Function1<String, BoxedUnit>, BoxedUnit>, boolean, int, String) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- pipe(String) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- pipe(String, Map<String, String>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- pipe(Seq<String>, Map<String, String>, Function1<Function1<String, BoxedUnit>, BoxedUnit>, Function2<T, Function1<String, BoxedUnit>, BoxedUnit>, boolean, int, String) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- pipe(String) - Static method in class org.apache.spark.graphx.VertexRDD
-
- pipe(String, Map<String, String>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- pipe(Seq<String>, Map<String, String>, Function1<Function1<String, BoxedUnit>, BoxedUnit>, Function2<T, Function1<String, BoxedUnit>, BoxedUnit>, boolean, int, String) - Static method in class org.apache.spark.graphx.VertexRDD
-
- pipe(String) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- pipe(String, Map<String, String>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- pipe(Seq<String>, Map<String, String>, Function1<Function1<String, BoxedUnit>, BoxedUnit>, Function2<T, Function1<String, BoxedUnit>, BoxedUnit>, boolean, int, String) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- pipe(String) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- pipe(String, Map<String, String>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- pipe(Seq<String>, Map<String, String>, Function1<Function1<String, BoxedUnit>, BoxedUnit>, Function2<T, Function1<String, BoxedUnit>, BoxedUnit>, boolean, int, String) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- pipe(String) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- pipe(String, Map<String, String>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- pipe(Seq<String>, Map<String, String>, Function1<Function1<String, BoxedUnit>, BoxedUnit>, Function2<T, Function1<String, BoxedUnit>, BoxedUnit>, boolean, int, String) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- pipe(String) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- pipe(String, Map<String, String>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- pipe(Seq<String>, Map<String, String>, Function1<Function1<String, BoxedUnit>, BoxedUnit>, Function2<T, Function1<String, BoxedUnit>, BoxedUnit>, boolean, int, String) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- pipe(String) - Method in class org.apache.spark.rdd.RDD
-
Return an RDD created by piping elements to a forked external process.
- pipe(String, Map<String, String>) - Method in class org.apache.spark.rdd.RDD
-
Return an RDD created by piping elements to a forked external process.
- pipe(Seq<String>, Map<String, String>, Function1<Function1<String, BoxedUnit>, BoxedUnit>, Function2<T, Function1<String, BoxedUnit>, BoxedUnit>, boolean, int, String) - Method in class org.apache.spark.rdd.RDD
-
Return an RDD created by piping elements to a forked external process.
- pipe(String) - Static method in class org.apache.spark.rdd.UnionRDD
-
- pipe(String, Map<String, String>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- pipe(Seq<String>, Map<String, String>, Function1<Function1<String, BoxedUnit>, BoxedUnit>, Function2<T, Function1<String, BoxedUnit>, BoxedUnit>, boolean, int, String) - Static method in class org.apache.spark.rdd.UnionRDD
-
- pipe$default$2() - Static method in class org.apache.spark.api.r.RRDD
-
- pipe$default$2() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- pipe$default$2() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- pipe$default$2() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- pipe$default$2() - Static method in class org.apache.spark.graphx.VertexRDD
-
- pipe$default$2() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- pipe$default$2() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- pipe$default$2() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- pipe$default$2() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- pipe$default$2() - Static method in class org.apache.spark.rdd.UnionRDD
-
- pipe$default$3() - Static method in class org.apache.spark.api.r.RRDD
-
- pipe$default$3() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- pipe$default$3() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- pipe$default$3() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- pipe$default$3() - Static method in class org.apache.spark.graphx.VertexRDD
-
- pipe$default$3() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- pipe$default$3() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- pipe$default$3() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- pipe$default$3() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- pipe$default$3() - Static method in class org.apache.spark.rdd.UnionRDD
-
- pipe$default$4() - Static method in class org.apache.spark.api.r.RRDD
-
- pipe$default$4() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- pipe$default$4() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- pipe$default$4() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- pipe$default$4() - Static method in class org.apache.spark.graphx.VertexRDD
-
- pipe$default$4() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- pipe$default$4() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- pipe$default$4() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- pipe$default$4() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- pipe$default$4() - Static method in class org.apache.spark.rdd.UnionRDD
-
- pipe$default$5() - Static method in class org.apache.spark.api.r.RRDD
-
- pipe$default$5() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- pipe$default$5() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- pipe$default$5() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- pipe$default$5() - Static method in class org.apache.spark.graphx.VertexRDD
-
- pipe$default$5() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- pipe$default$5() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- pipe$default$5() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- pipe$default$5() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- pipe$default$5() - Static method in class org.apache.spark.rdd.UnionRDD
-
- pipe$default$6() - Static method in class org.apache.spark.api.r.RRDD
-
- pipe$default$6() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- pipe$default$6() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- pipe$default$6() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- pipe$default$6() - Static method in class org.apache.spark.graphx.VertexRDD
-
- pipe$default$6() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- pipe$default$6() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- pipe$default$6() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- pipe$default$6() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- pipe$default$6() - Static method in class org.apache.spark.rdd.UnionRDD
-
- pipe$default$7() - Static method in class org.apache.spark.api.r.RRDD
-
- pipe$default$7() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- pipe$default$7() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- pipe$default$7() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- pipe$default$7() - Static method in class org.apache.spark.graphx.VertexRDD
-
- pipe$default$7() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- pipe$default$7() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- pipe$default$7() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- pipe$default$7() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- pipe$default$7() - Static method in class org.apache.spark.rdd.UnionRDD
-
- Pipeline - Class in org.apache.spark.ml
-
A simple pipeline, which acts as an estimator.
- Pipeline(String) - Constructor for class org.apache.spark.ml.Pipeline
-
- Pipeline() - Constructor for class org.apache.spark.ml.Pipeline
-
- Pipeline.SharedReadWrite$ - Class in org.apache.spark.ml
-
- Pipeline.SharedReadWrite$() - Constructor for class org.apache.spark.ml.Pipeline.SharedReadWrite$
-
- PipelineModel - Class in org.apache.spark.ml
-
Represents a fitted pipeline.
- PipelineStage - Class in org.apache.spark.ml
-
- PipelineStage() - Constructor for class org.apache.spark.ml.PipelineStage
-
- pivot(String) - Method in class org.apache.spark.sql.RelationalGroupedDataset
-
Pivots a column of the current DataFrame and perform the specified aggregation.
- pivot(String, Seq<Object>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
-
Pivots a column of the current DataFrame and perform the specified aggregation.
- pivot(String, List<Object>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
-
Pivots a column of the current DataFrame and perform the specified aggregation.
- plan() - Method in exception org.apache.spark.sql.AnalysisException
-
- plus(Object) - Method in class org.apache.spark.sql.Column
-
Sum of this expression and another expression.
- plus(Duration) - Method in class org.apache.spark.streaming.Duration
-
- plus(Duration) - Method in class org.apache.spark.streaming.Time
-
- PMMLExportable - Interface in org.apache.spark.mllib.pmml
-
:: DeveloperApi ::
Export model to the PMML format
Predictive Model Markup Language (PMML) is an XML-based file format
developed by the Data Mining Group (www.dmg.org).
- PMMLModelExportFactory - Class in org.apache.spark.mllib.pmml.export
-
- PMMLModelExportFactory() - Constructor for class org.apache.spark.mllib.pmml.export.PMMLModelExportFactory
-
- pmod(Column, Column) - Static method in class org.apache.spark.sql.functions
-
Returns the positive value of dividend mod divisor.
- point() - Method in class org.apache.spark.mllib.feature.VocabWord
-
- POINTS() - Static method in class org.apache.spark.mllib.clustering.StreamingKMeans
-
- PoissonBounds - Class in org.apache.spark.util.random
-
Utility functions that help us determine bounds on adjusted sampling rate to guarantee exact
sample sizes with high confidence when sampling with replacement.
- PoissonBounds() - Constructor for class org.apache.spark.util.random.PoissonBounds
-
- PoissonGenerator - Class in org.apache.spark.mllib.random
-
:: DeveloperApi ::
Generates i.i.d.
- PoissonGenerator(double) - Constructor for class org.apache.spark.mllib.random.PoissonGenerator
-
- poissonJavaRDD(JavaSparkContext, double, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- poissonJavaRDD(JavaSparkContext, double, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- poissonJavaRDD(JavaSparkContext, double, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- poissonJavaVectorRDD(JavaSparkContext, double, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- poissonJavaVectorRDD(JavaSparkContext, double, long, int, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- poissonJavaVectorRDD(JavaSparkContext, double, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- poissonRDD(SparkContext, double, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
Generates an RDD comprised of i.i.d. samples from the Poisson distribution with the input
mean.
- PoissonSampler<T> - Class in org.apache.spark.util.random
-
:: DeveloperApi ::
A sampler for sampling with replacement, based on values drawn from Poisson distribution.
- PoissonSampler(double, boolean) - Constructor for class org.apache.spark.util.random.PoissonSampler
-
- PoissonSampler(double) - Constructor for class org.apache.spark.util.random.PoissonSampler
-
- poissonVectorRDD(SparkContext, double, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
Generates an RDD[Vector] with vectors containing i.i.d. samples drawn from the
Poisson distribution with the input mean.
- PolynomialExpansion - Class in org.apache.spark.ml.feature
-
Perform feature expansion in a polynomial space.
- PolynomialExpansion(String) - Constructor for class org.apache.spark.ml.feature.PolynomialExpansion
-
- PolynomialExpansion() - Constructor for class org.apache.spark.ml.feature.PolynomialExpansion
-
- poolToActiveStages() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- port() - Method in interface org.apache.spark.SparkExecutorInfo
-
- port() - Method in class org.apache.spark.SparkExecutorInfoImpl
-
- port() - Method in class org.apache.spark.storage.BlockManagerId
-
- port() - Method in class org.apache.spark.streaming.kafka.Broker
-
Broker's port
- port() - Method in class org.apache.spark.streaming.kafka.KafkaCluster.LeaderOffset
-
- PortableDataStream - Class in org.apache.spark.input
-
A class that allows DataStreams to be serialized and moved around by not creating them
until they need to be read
- PortableDataStream(CombineFileSplit, TaskAttemptContext, Integer) - Constructor for class org.apache.spark.input.PortableDataStream
-
- portMaxRetries(SparkConf) - Static method in class org.apache.spark.util.Utils
-
Maximum number of retries when binding to a port before giving up.
- posexplode(Column) - Static method in class org.apache.spark.sql.functions
-
Creates a new row for each element with position in the given array or map column.
- positioned(Function0<Parsers.Parser<T>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- PostgresDialect - Class in org.apache.spark.sql.jdbc
-
- PostgresDialect() - Constructor for class org.apache.spark.sql.jdbc.PostgresDialect
-
- pow(Column, Column) - Static method in class org.apache.spark.sql.functions
-
Returns the value of the first argument raised to the power of the second argument.
- pow(Column, String) - Static method in class org.apache.spark.sql.functions
-
Returns the value of the first argument raised to the power of the second argument.
- pow(String, Column) - Static method in class org.apache.spark.sql.functions
-
Returns the value of the first argument raised to the power of the second argument.
- pow(String, String) - Static method in class org.apache.spark.sql.functions
-
Returns the value of the first argument raised to the power of the second argument.
- pow(Column, double) - Static method in class org.apache.spark.sql.functions
-
Returns the value of the first argument raised to the power of the second argument.
- pow(String, double) - Static method in class org.apache.spark.sql.functions
-
Returns the value of the first argument raised to the power of the second argument.
- pow(double, Column) - Static method in class org.apache.spark.sql.functions
-
Returns the value of the first argument raised to the power of the second argument.
- pow(double, String) - Static method in class org.apache.spark.sql.functions
-
Returns the value of the first argument raised to the power of the second argument.
- PowerIterationClustering - Class in org.apache.spark.mllib.clustering
-
Power Iteration Clustering (PIC), a scalable graph clustering algorithm developed by
Lin and Cohen.
- PowerIterationClustering() - Constructor for class org.apache.spark.mllib.clustering.PowerIterationClustering
-
Constructs a PIC instance with default parameters: {k: 2, maxIterations: 100,
initMode: "random"}.
- PowerIterationClustering.Assignment - Class in org.apache.spark.mllib.clustering
-
Cluster assignment.
- PowerIterationClustering.Assignment(long, int) - Constructor for class org.apache.spark.mllib.clustering.PowerIterationClustering.Assignment
-
- PowerIterationClustering.Assignment$ - Class in org.apache.spark.mllib.clustering
-
- PowerIterationClustering.Assignment$() - Constructor for class org.apache.spark.mllib.clustering.PowerIterationClustering.Assignment$
-
- PowerIterationClusteringModel - Class in org.apache.spark.mllib.clustering
-
- PowerIterationClusteringModel(int, RDD<PowerIterationClustering.Assignment>) - Constructor for class org.apache.spark.mllib.clustering.PowerIterationClusteringModel
-
- PowerIterationClusteringModel.SaveLoadV1_0$ - Class in org.apache.spark.mllib.clustering
-
- PowerIterationClusteringModel.SaveLoadV1_0$() - Constructor for class org.apache.spark.mllib.clustering.PowerIterationClusteringModel.SaveLoadV1_0$
-
- pr() - Method in class org.apache.spark.ml.classification.BinaryLogisticRegressionSummary
-
Returns the precision-recall curve, which is a Dataframe containing
two fields recall, precision with (0.0, 1.0) prepended to it.
- pr() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
-
Returns the precision-recall curve, which is an RDD of (recall, precision),
NOT (precision, recall), with (0.0, 1.0) prepended to it.
- Precision - Class in org.apache.spark.mllib.evaluation.binary
-
Precision.
- Precision() - Constructor for class org.apache.spark.mllib.evaluation.binary.Precision
-
- precision(double) - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
-
Returns precision for a given label (category)
- precision() - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
-
Deprecated.
Use accuracy. Since 2.0.0.
- precision() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
-
Returns document-based precision averaged by the number of documents
- precision(double) - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
-
Returns precision for a given label (category)
- precision() - Method in class org.apache.spark.sql.types.Decimal
-
- precision() - Method in class org.apache.spark.sql.types.DecimalType
-
- precisionAt(int) - Method in class org.apache.spark.mllib.evaluation.RankingMetrics
-
Compute the average precision of all the queries, truncated at ranking position k.
- precisionByThreshold() - Method in class org.apache.spark.ml.classification.BinaryLogisticRegressionSummary
-
Returns a dataframe with two fields (threshold, precision) curve.
- precisionByThreshold() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
-
Returns the (threshold, precision) curve.
- predict(Vector) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- predict(RDD<Vector>) - Method in interface org.apache.spark.mllib.classification.ClassificationModel
-
Predict values for the given data set using the model trained.
- predict(Vector) - Method in interface org.apache.spark.mllib.classification.ClassificationModel
-
Predict values for a single data point using the model trained.
- predict(JavaRDD<Vector>) - Method in interface org.apache.spark.mllib.classification.ClassificationModel
-
Predict values for examples stored in a JavaRDD.
- predict(RDD<Vector>) - Static method in class org.apache.spark.mllib.classification.LogisticRegressionModel
-
- predict(Vector) - Static method in class org.apache.spark.mllib.classification.LogisticRegressionModel
-
- predict(JavaRDD<Vector>) - Static method in class org.apache.spark.mllib.classification.LogisticRegressionModel
-
- predict(RDD<Vector>) - Method in class org.apache.spark.mllib.classification.NaiveBayesModel
-
- predict(Vector) - Method in class org.apache.spark.mllib.classification.NaiveBayesModel
-
- predict(RDD<Vector>) - Static method in class org.apache.spark.mllib.classification.SVMModel
-
- predict(Vector) - Static method in class org.apache.spark.mllib.classification.SVMModel
-
- predict(JavaRDD<Vector>) - Static method in class org.apache.spark.mllib.classification.SVMModel
-
- predict(Vector) - Method in class org.apache.spark.mllib.clustering.BisectingKMeansModel
-
Predicts the index of the cluster that the input point belongs to.
- predict(RDD<Vector>) - Method in class org.apache.spark.mllib.clustering.BisectingKMeansModel
-
Predicts the indices of the clusters that the input points belong to.
- predict(JavaRDD<Vector>) - Method in class org.apache.spark.mllib.clustering.BisectingKMeansModel
-
Java-friendly version of predict().
- predict(RDD<Vector>) - Method in class org.apache.spark.mllib.clustering.GaussianMixtureModel
-
Maps given points to their cluster indices.
- predict(Vector) - Method in class org.apache.spark.mllib.clustering.GaussianMixtureModel
-
Maps given point to its cluster index.
- predict(JavaRDD<Vector>) - Method in class org.apache.spark.mllib.clustering.GaussianMixtureModel
-
Java-friendly version of predict()
- predict(Vector) - Method in class org.apache.spark.mllib.clustering.KMeansModel
-
Returns the cluster index that a given point belongs to.
- predict(RDD<Vector>) - Method in class org.apache.spark.mllib.clustering.KMeansModel
-
Maps given points to their cluster indices.
- predict(JavaRDD<Vector>) - Method in class org.apache.spark.mllib.clustering.KMeansModel
-
Maps given points to their cluster indices.
- predict(int, int) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
-
Predict the rating of one user for one product.
- predict(RDD<Tuple2<Object, Object>>) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
-
Predict the rating of many users for many products.
- predict(JavaPairRDD<Integer, Integer>) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
-
Java-friendly version of MatrixFactorizationModel.predict.
- predict(RDD<Vector>) - Method in class org.apache.spark.mllib.regression.GeneralizedLinearModel
-
Predict values for the given data set using the model trained.
- predict(Vector) - Method in class org.apache.spark.mllib.regression.GeneralizedLinearModel
-
Predict values for a single data point using the model trained.
- predict(RDD<Object>) - Method in class org.apache.spark.mllib.regression.IsotonicRegressionModel
-
Predict labels for provided features.
- predict(JavaDoubleRDD) - Method in class org.apache.spark.mllib.regression.IsotonicRegressionModel
-
Predict labels for provided features.
- predict(double) - Method in class org.apache.spark.mllib.regression.IsotonicRegressionModel
-
Predict a single label.
- predict(RDD<Vector>) - Static method in class org.apache.spark.mllib.regression.LassoModel
-
- predict(Vector) - Static method in class org.apache.spark.mllib.regression.LassoModel
-
- predict(JavaRDD<Vector>) - Static method in class org.apache.spark.mllib.regression.LassoModel
-
- predict(RDD<Vector>) - Static method in class org.apache.spark.mllib.regression.LinearRegressionModel
-
- predict(Vector) - Static method in class org.apache.spark.mllib.regression.LinearRegressionModel
-
- predict(JavaRDD<Vector>) - Static method in class org.apache.spark.mllib.regression.LinearRegressionModel
-
- predict(RDD<Vector>) - Method in interface org.apache.spark.mllib.regression.RegressionModel
-
Predict values for the given data set using the model trained.
- predict(Vector) - Method in interface org.apache.spark.mllib.regression.RegressionModel
-
Predict values for a single data point using the model trained.
- predict(JavaRDD<Vector>) - Method in interface org.apache.spark.mllib.regression.RegressionModel
-
Predict values for examples stored in a JavaRDD.
- predict(RDD<Vector>) - Static method in class org.apache.spark.mllib.regression.RidgeRegressionModel
-
- predict(Vector) - Static method in class org.apache.spark.mllib.regression.RidgeRegressionModel
-
- predict(JavaRDD<Vector>) - Static method in class org.apache.spark.mllib.regression.RidgeRegressionModel
-
- predict(Vector) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
-
Predict values for a single data point using the model trained.
- predict(RDD<Vector>) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
-
Predict values for the given data set using the model trained.
- predict(JavaRDD<Vector>) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
-
Predict values for the given data set using the model trained.
- predict() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData
-
- predict() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.PredictData
-
- predict(Vector) - Static method in class org.apache.spark.mllib.tree.model.GradientBoostedTreesModel
-
- predict(RDD<Vector>) - Static method in class org.apache.spark.mllib.tree.model.GradientBoostedTreesModel
-
- predict(JavaRDD<Vector>) - Static method in class org.apache.spark.mllib.tree.model.GradientBoostedTreesModel
-
- predict() - Method in class org.apache.spark.mllib.tree.model.Node
-
- predict(Vector) - Method in class org.apache.spark.mllib.tree.model.Node
-
predict value if node is not leaf
- Predict - Class in org.apache.spark.mllib.tree.model
-
:: DeveloperApi ::
Predicted value for a node
param: predict predicted value
param: prob probability of the label (classification only)
- Predict(double, double) - Constructor for class org.apache.spark.mllib.tree.model.Predict
-
- predict() - Method in class org.apache.spark.mllib.tree.model.Predict
-
- predict(Vector) - Static method in class org.apache.spark.mllib.tree.model.RandomForestModel
-
- predict(RDD<Vector>) - Static method in class org.apache.spark.mllib.tree.model.RandomForestModel
-
- predict(JavaRDD<Vector>) - Static method in class org.apache.spark.mllib.tree.model.RandomForestModel
-
- prediction() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData
-
- prediction() - Method in class org.apache.spark.ml.tree.InternalNode
-
- prediction() - Method in class org.apache.spark.ml.tree.LeafNode
-
- prediction() - Method in class org.apache.spark.ml.tree.Node
-
Prediction a leaf node makes, or which an internal node would make if it were a leaf node
- predictionCol() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- predictionCol() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- predictionCol() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- predictionCol() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- predictionCol() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- predictionCol() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- predictionCol() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- predictionCol() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- predictionCol() - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- predictionCol() - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- predictionCol() - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- predictionCol() - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- predictionCol() - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- predictionCol() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- predictionCol() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- predictionCol() - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- predictionCol() - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- predictionCol() - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- predictionCol() - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- predictionCol() - Method in class org.apache.spark.ml.clustering.GaussianMixtureSummary
-
- predictionCol() - Static method in class org.apache.spark.ml.clustering.KMeans
-
- predictionCol() - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- predictionCol() - Method in class org.apache.spark.ml.clustering.KMeansSummary
-
- predictionCol() - Static method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
- predictionCol() - Static method in class org.apache.spark.ml.evaluation.RegressionEvaluator
-
- predictionCol() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- predictionCol() - Static method in class org.apache.spark.ml.recommendation.ALSModel
-
- predictionCol() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- predictionCol() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- predictionCol() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- predictionCol() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- predictionCol() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- predictionCol() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- predictionCol() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- predictionCol() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- predictionCol() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
-
Field in "predictions" which gives the predicted value of each instance.
- predictionCol() - Static method in class org.apache.spark.ml.regression.IsotonicRegression
-
- predictionCol() - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- predictionCol() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- predictionCol() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- predictionCol() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
-
- predictionCol() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- predictionCol() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- PredictionModel<FeaturesType,M extends PredictionModel<FeaturesType,M>> - Class in org.apache.spark.ml
-
:: DeveloperApi ::
Abstraction for a model for prediction tasks (regression and classification).
- PredictionModel() - Constructor for class org.apache.spark.ml.PredictionModel
-
- predictions() - Method in class org.apache.spark.ml.classification.BinaryLogisticRegressionSummary
-
- predictions() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
-
Dataframe output by the model's `transform` method.
- predictions() - Method in class org.apache.spark.ml.clustering.GaussianMixtureSummary
-
- predictions() - Method in class org.apache.spark.ml.clustering.KMeansSummary
-
- predictions() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
-
Predictions output by the model's `transform` method.
- predictions() - Method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
Predictions associated with the boundaries at the same index, monotone because of isotonic
regression.
- predictions() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
-
- predictions() - Method in class org.apache.spark.mllib.regression.IsotonicRegressionModel
-
- predictOn(DStream<Vector>) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
-
Use the clustering model to make predictions on batches of data from a DStream.
- predictOn(JavaDStream<Vector>) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
-
Java-friendly version of predictOn.
- predictOn(DStream<Vector>) - Method in class org.apache.spark.mllib.regression.StreamingLinearAlgorithm
-
Use the model to make predictions on batches of data from a DStream
- predictOn(JavaDStream<Vector>) - Method in class org.apache.spark.mllib.regression.StreamingLinearAlgorithm
-
Java-friendly version of predictOn.
- predictOnValues(DStream<Tuple2<K, Vector>>, ClassTag<K>) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
-
Use the model to make predictions on the values of a DStream and carry over its keys.
- predictOnValues(JavaPairDStream<K, Vector>) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
-
Java-friendly version of predictOnValues.
- predictOnValues(DStream<Tuple2<K, Vector>>, ClassTag<K>) - Method in class org.apache.spark.mllib.regression.StreamingLinearAlgorithm
-
Use the model to make predictions on the values of a DStream and carry over its keys.
- predictOnValues(JavaPairDStream<K, Vector>) - Method in class org.apache.spark.mllib.regression.StreamingLinearAlgorithm
-
Java-friendly version of predictOnValues.
- Predictor<FeaturesType,Learner extends Predictor<FeaturesType,Learner,M>,M extends PredictionModel<FeaturesType,M>> - Class in org.apache.spark.ml
-
:: DeveloperApi ::
Abstraction for prediction problems (regression and classification).
- Predictor() - Constructor for class org.apache.spark.ml.Predictor
-
- predictProbabilities(RDD<Vector>) - Method in class org.apache.spark.mllib.classification.NaiveBayesModel
-
Predict values for the given data set using the model trained.
- predictProbabilities(Vector) - Method in class org.apache.spark.mllib.classification.NaiveBayesModel
-
Predict posterior class probabilities for a single data point using the model trained.
- predictQuantiles(Vector) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- predictSoft(RDD<Vector>) - Method in class org.apache.spark.mllib.clustering.GaussianMixtureModel
-
Given the input vectors, return the membership value of each vector
to all mixture components.
- predictSoft(Vector) - Method in class org.apache.spark.mllib.clustering.GaussianMixtureModel
-
Given the input vector, return the membership values to all mixture components.
- preferredLocation() - Method in class org.apache.spark.streaming.receiver.Receiver
-
Override this to specify a preferred location (hostname).
- preferredLocations(Partition) - Static method in class org.apache.spark.api.r.RRDD
-
- preferredLocations(Partition) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- preferredLocations(Partition) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- preferredLocations(Partition) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- preferredLocations(Partition) - Static method in class org.apache.spark.graphx.VertexRDD
-
- preferredLocations(Partition) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- preferredLocations(Partition) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- preferredLocations(Partition) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- preferredLocations(Partition) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- preferredLocations(Partition) - Method in class org.apache.spark.rdd.RDD
-
Get the preferred locations of a partition, taking into account whether the
RDD is checkpointed.
- preferredLocations(Partition) - Static method in class org.apache.spark.rdd.UnionRDD
-
- prefixesToRewrite() - Method in class org.apache.spark.ml.feature.VectorAttributeRewriter
-
- prefixLength(Function1<A, Object>) - Static method in class org.apache.spark.sql.types.StructType
-
- PrefixSpan - Class in org.apache.spark.mllib.fpm
-
A parallel PrefixSpan algorithm to mine frequent sequential patterns.
- PrefixSpan() - Constructor for class org.apache.spark.mllib.fpm.PrefixSpan
-
Constructs a default instance with default parameters
{minSupport: 0.1, maxPatternLength: 10, maxLocalProjDBSize: 32000000L}.
- PrefixSpan.FreqSequence<Item> - Class in org.apache.spark.mllib.fpm
-
Represents a frequent sequence.
- PrefixSpan.FreqSequence(Object[], long) - Constructor for class org.apache.spark.mllib.fpm.PrefixSpan.FreqSequence
-
- PrefixSpan.Postfix$ - Class in org.apache.spark.mllib.fpm
-
- PrefixSpan.Postfix$() - Constructor for class org.apache.spark.mllib.fpm.PrefixSpan.Postfix$
-
- PrefixSpan.Prefix$ - Class in org.apache.spark.mllib.fpm
-
- PrefixSpan.Prefix$() - Constructor for class org.apache.spark.mllib.fpm.PrefixSpan.Prefix$
-
- PrefixSpanModel<Item> - Class in org.apache.spark.mllib.fpm
-
Model fitted by
PrefixSpan
param: freqSequences frequent sequences
- PrefixSpanModel(RDD<PrefixSpan.FreqSequence<Item>>) - Constructor for class org.apache.spark.mllib.fpm.PrefixSpanModel
-
- PrefixSpanModel.SaveLoadV1_0$ - Class in org.apache.spark.mllib.fpm
-
- PrefixSpanModel.SaveLoadV1_0$() - Constructor for class org.apache.spark.mllib.fpm.PrefixSpanModel.SaveLoadV1_0$
-
- prefLoc() - Method in class org.apache.spark.rdd.PartitionGroup
-
- pregel(A, int, EdgeDirection, Function3<Object, VD, A, VD>, Function1<EdgeTriplet<VD, ED>, Iterator<Tuple2<Object, A>>>, Function2<A, A, A>, ClassTag<A>) - Method in class org.apache.spark.graphx.GraphOps
-
Execute a Pregel-like iterative vertex-parallel abstraction.
- Pregel - Class in org.apache.spark.graphx
-
Implements a Pregel-like bulk-synchronous message-passing API.
- Pregel() - Constructor for class org.apache.spark.graphx.Pregel
-
- prepare() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- prepare() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- prepareWritable(Writable, Seq<Tuple2<String, String>>) - Static method in class org.apache.spark.sql.hive.HiveShim
-
- prepareWrite(SparkSession, Job, Map<String, String>, StructType) - Method in class org.apache.spark.sql.hive.orc.OrcFileFormat
-
- prependBaseUri(String, String) - Static method in class org.apache.spark.ui.UIUtils
-
- prettyJson() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- prettyJson() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- prettyJson() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- prettyJson() - Static method in class org.apache.spark.sql.types.ArrayType
-
- prettyJson() - Static method in class org.apache.spark.sql.types.BinaryType
-
- prettyJson() - Static method in class org.apache.spark.sql.types.BooleanType
-
- prettyJson() - Static method in class org.apache.spark.sql.types.ByteType
-
- prettyJson() - Static method in class org.apache.spark.sql.types.CalendarIntervalType
-
- prettyJson() - Method in class org.apache.spark.sql.types.DataType
-
The pretty (i.e.
- prettyJson() - Static method in class org.apache.spark.sql.types.DateType
-
- prettyJson() - Static method in class org.apache.spark.sql.types.DecimalType
-
- prettyJson() - Static method in class org.apache.spark.sql.types.DoubleType
-
- prettyJson() - Static method in class org.apache.spark.sql.types.FloatType
-
- prettyJson() - Static method in class org.apache.spark.sql.types.IntegerType
-
- prettyJson() - Static method in class org.apache.spark.sql.types.LongType
-
- prettyJson() - Static method in class org.apache.spark.sql.types.MapType
-
- prettyJson() - Static method in class org.apache.spark.sql.types.NullType
-
- prettyJson() - Static method in class org.apache.spark.sql.types.NumericType
-
- prettyJson() - Static method in class org.apache.spark.sql.types.ShortType
-
- prettyJson() - Static method in class org.apache.spark.sql.types.StringType
-
- prettyJson() - Static method in class org.apache.spark.sql.types.StructType
-
- prettyJson() - Static method in class org.apache.spark.sql.types.TimestampType
-
- prettyPrint() - Method in class org.apache.spark.streaming.Duration
-
- prev() - Method in class org.apache.spark.rdd.ShuffledRDD
-
- print() - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- print(int) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- print() - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Print the first ten elements of each RDD generated in this DStream.
- print(int) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Print the first num elements of each RDD generated in this DStream.
- print() - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- print(int) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- print() - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- print(int) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- print() - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- print(int) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- print() - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- print(int) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- print() - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- print(int) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- print() - Method in class org.apache.spark.streaming.dstream.DStream
-
Print the first ten elements of each RDD generated in this DStream.
- print(int) - Method in class org.apache.spark.streaming.dstream.DStream
-
Print the first num elements of each RDD generated in this DStream.
- printSchema() - Method in class org.apache.spark.sql.Dataset
-
Prints the schema to the console in a nice tree format.
- printSchema() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- printSchema() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- printSchema() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- printStackTrace() - Static method in exception org.apache.spark.sql.AnalysisException
-
- printStackTrace(PrintStream) - Static method in exception org.apache.spark.sql.AnalysisException
-
- printStackTrace(PrintWriter) - Static method in exception org.apache.spark.sql.AnalysisException
-
- printStackTrace() - Static method in exception org.apache.spark.sql.streaming.StreamingQueryException
-
- printStackTrace(PrintStream) - Static method in exception org.apache.spark.sql.streaming.StreamingQueryException
-
- printStackTrace(PrintWriter) - Static method in exception org.apache.spark.sql.streaming.StreamingQueryException
-
- printStats() - Method in class org.apache.spark.streaming.scheduler.StatsReportListener
-
- printTreeString() - Method in class org.apache.spark.sql.types.StructType
-
- prob() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.PredictData
-
- prob() - Method in class org.apache.spark.mllib.tree.model.Predict
-
- ProbabilisticClassificationModel<FeaturesType,M extends ProbabilisticClassificationModel<FeaturesType,M>> - Class in org.apache.spark.ml.classification
-
:: DeveloperApi ::
- ProbabilisticClassificationModel() - Constructor for class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- ProbabilisticClassifier<FeaturesType,E extends ProbabilisticClassifier<FeaturesType,E,M>,M extends ProbabilisticClassificationModel<FeaturesType,M>> - Class in org.apache.spark.ml.classification
-
:: DeveloperApi ::
- ProbabilisticClassifier() - Constructor for class org.apache.spark.ml.classification.ProbabilisticClassifier
-
- probabilities() - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- probability() - Method in class org.apache.spark.ml.clustering.GaussianMixtureSummary
-
Probability of each cluster.
- probabilityCol() - Method in class org.apache.spark.ml.classification.BinaryLogisticRegressionSummary
-
- probabilityCol() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- probabilityCol() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- probabilityCol() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- probabilityCol() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- probabilityCol() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
-
Field in "predictions" which gives the probability of each class as a vector.
- probabilityCol() - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- probabilityCol() - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- probabilityCol() - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- probabilityCol() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- probabilityCol() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- probabilityCol() - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- probabilityCol() - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- probabilityCol() - Method in class org.apache.spark.ml.clustering.GaussianMixtureSummary
-
- process(T) - Method in class org.apache.spark.sql.ForeachWriter
-
Called to process the data in the executor side.
- PROCESS_LOCAL() - Static method in class org.apache.spark.scheduler.TaskLocality
-
- processAllAvailable() - Method in interface org.apache.spark.sql.streaming.StreamingQuery
-
Blocks until all available data in the source has been processed and committed to the sink.
- processingDelay() - Method in class org.apache.spark.streaming.scheduler.BatchInfo
-
Time taken for the all jobs of this batch to finish processing from the time they started
processing.
- processingEndTime() - Method in class org.apache.spark.streaming.scheduler.BatchInfo
-
- processingStartTime() - Method in class org.apache.spark.streaming.scheduler.BatchInfo
-
- ProcessingTime - Class in org.apache.spark.sql.streaming
-
:: Experimental ::
A trigger that runs a query periodically based on the processing time.
- ProcessingTime(long) - Constructor for class org.apache.spark.sql.streaming.ProcessingTime
-
- processStreamByLine(String, InputStream, Function1<String, BoxedUnit>) - Static method in class org.apache.spark.util.Utils
-
Return and start a daemon thread that processes the content of the input stream line by line.
- producedAttributes() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- producedAttributes() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- producedAttributes() - Method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- product() - Method in class org.apache.spark.mllib.recommendation.Rating
-
- product(TypeTags.TypeTag<T>) - Static method in class org.apache.spark.sql.Encoders
-
An encoder for Scala's product type (tuples, case classes, etc).
- product(Numeric<B>) - Static method in class org.apache.spark.sql.types.StructType
-
- productArity() - Static method in class org.apache.spark.Aggregator
-
- productArity() - Static method in class org.apache.spark.CleanAccum
-
- productArity() - Static method in class org.apache.spark.CleanBroadcast
-
- productArity() - Static method in class org.apache.spark.CleanCheckpoint
-
- productArity() - Static method in class org.apache.spark.CleanRDD
-
- productArity() - Static method in class org.apache.spark.CleanShuffle
-
- productArity() - Static method in class org.apache.spark.ExceptionFailure
-
- productArity() - Static method in class org.apache.spark.ExecutorLostFailure
-
- productArity() - Static method in class org.apache.spark.ExecutorRegistered
-
- productArity() - Static method in class org.apache.spark.ExecutorRemoved
-
- productArity() - Static method in class org.apache.spark.ExpireDeadHosts
-
- productArity() - Static method in class org.apache.spark.FetchFailed
-
- productArity() - Static method in class org.apache.spark.graphx.Edge
-
- productArity() - Static method in class org.apache.spark.ml.feature.Dot
-
- productArity() - Static method in class org.apache.spark.ml.feature.LabeledPoint
-
- productArity() - Static method in class org.apache.spark.ml.param.ParamPair
-
- productArity() - Static method in class org.apache.spark.mllib.feature.VocabWord
-
- productArity() - Static method in class org.apache.spark.mllib.linalg.distributed.IndexedRow
-
- productArity() - Static method in class org.apache.spark.mllib.linalg.distributed.MatrixEntry
-
- productArity() - Static method in class org.apache.spark.mllib.linalg.QRDecomposition
-
- productArity() - Static method in class org.apache.spark.mllib.linalg.SingularValueDecomposition
-
- productArity() - Static method in class org.apache.spark.mllib.recommendation.Rating
-
- productArity() - Static method in class org.apache.spark.mllib.regression.LabeledPoint
-
- productArity() - Static method in class org.apache.spark.mllib.stat.test.BinarySample
-
- productArity() - Static method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- productArity() - Static method in class org.apache.spark.mllib.tree.model.Split
-
- productArity() - Static method in class org.apache.spark.Resubmitted
-
- productArity() - Static method in class org.apache.spark.rpc.netty.OnStart
-
- productArity() - Static method in class org.apache.spark.rpc.netty.OnStop
-
- productArity() - Static method in class org.apache.spark.scheduler.AccumulableInfo
-
- productArity() - Static method in class org.apache.spark.scheduler.AllJobsCancelled
-
- productArity() - Static method in class org.apache.spark.scheduler.AskPermissionToCommitOutput
-
- productArity() - Static method in class org.apache.spark.scheduler.JobSucceeded
-
- productArity() - Static method in class org.apache.spark.scheduler.local.KillTask
-
- productArity() - Static method in class org.apache.spark.scheduler.local.ReviveOffers
-
- productArity() - Static method in class org.apache.spark.scheduler.local.StatusUpdate
-
- productArity() - Static method in class org.apache.spark.scheduler.local.StopExecutor
-
- productArity() - Static method in class org.apache.spark.scheduler.ResubmitFailedStages
-
- productArity() - Static method in class org.apache.spark.scheduler.RuntimePercentage
-
- productArity() - Static method in class org.apache.spark.scheduler.SparkListenerApplicationEnd
-
- productArity() - Static method in class org.apache.spark.scheduler.SparkListenerApplicationStart
-
- productArity() - Static method in class org.apache.spark.scheduler.SparkListenerBlockManagerAdded
-
- productArity() - Static method in class org.apache.spark.scheduler.SparkListenerBlockManagerRemoved
-
- productArity() - Static method in class org.apache.spark.scheduler.SparkListenerBlockUpdated
-
- productArity() - Static method in class org.apache.spark.scheduler.SparkListenerEnvironmentUpdate
-
- productArity() - Static method in class org.apache.spark.scheduler.SparkListenerExecutorAdded
-
- productArity() - Static method in class org.apache.spark.scheduler.SparkListenerExecutorMetricsUpdate
-
- productArity() - Static method in class org.apache.spark.scheduler.SparkListenerExecutorRemoved
-
- productArity() - Static method in class org.apache.spark.scheduler.SparkListenerJobEnd
-
- productArity() - Static method in class org.apache.spark.scheduler.SparkListenerJobStart
-
- productArity() - Static method in class org.apache.spark.scheduler.SparkListenerStageCompleted
-
- productArity() - Static method in class org.apache.spark.scheduler.SparkListenerStageSubmitted
-
- productArity() - Static method in class org.apache.spark.scheduler.SparkListenerTaskEnd
-
- productArity() - Static method in class org.apache.spark.scheduler.SparkListenerTaskGettingResult
-
- productArity() - Static method in class org.apache.spark.scheduler.SparkListenerTaskStart
-
- productArity() - Static method in class org.apache.spark.scheduler.SparkListenerUnpersistRDD
-
- productArity() - Static method in class org.apache.spark.scheduler.StopCoordinator
-
- productArity() - Static method in class org.apache.spark.sql.DatasetHolder
-
- productArity() - Static method in class org.apache.spark.sql.expressions.UserDefinedFunction
-
- productArity() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- productArity() - Static method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- productArity() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- productArity() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- productArity() - Static method in class org.apache.spark.sql.internal.HiveSerDe
-
- productArity() - Static method in class org.apache.spark.sql.jdbc.JdbcType
-
- productArity() - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
-
- productArity() - Static method in class org.apache.spark.sql.jdbc.OracleDialect
-
- productArity() - Static method in class org.apache.spark.sql.sources.And
-
- productArity() - Static method in class org.apache.spark.sql.sources.EqualNullSafe
-
- productArity() - Static method in class org.apache.spark.sql.sources.EqualTo
-
- productArity() - Static method in class org.apache.spark.sql.sources.GreaterThan
-
- productArity() - Static method in class org.apache.spark.sql.sources.GreaterThanOrEqual
-
- productArity() - Static method in class org.apache.spark.sql.sources.In
-
- productArity() - Static method in class org.apache.spark.sql.sources.IsNotNull
-
- productArity() - Static method in class org.apache.spark.sql.sources.IsNull
-
- productArity() - Static method in class org.apache.spark.sql.sources.LessThan
-
- productArity() - Static method in class org.apache.spark.sql.sources.LessThanOrEqual
-
- productArity() - Static method in class org.apache.spark.sql.sources.Not
-
- productArity() - Static method in class org.apache.spark.sql.sources.Or
-
- productArity() - Static method in class org.apache.spark.sql.sources.StringContains
-
- productArity() - Static method in class org.apache.spark.sql.sources.StringEndsWith
-
- productArity() - Static method in class org.apache.spark.sql.sources.StringStartsWith
-
- productArity() - Static method in class org.apache.spark.sql.streaming.ProcessingTime
-
- productArity() - Static method in class org.apache.spark.sql.types.ArrayType
-
- productArity() - Static method in class org.apache.spark.sql.types.DecimalType
-
- productArity() - Static method in class org.apache.spark.sql.types.MapType
-
- productArity() - Static method in class org.apache.spark.sql.types.StructField
-
- productArity() - Static method in class org.apache.spark.sql.types.StructType
-
- productArity() - Static method in class org.apache.spark.StopMapOutputTracker
-
- productArity() - Static method in class org.apache.spark.storage.BlockStatus
-
- productArity() - Static method in class org.apache.spark.storage.BlockUpdatedInfo
-
- productArity() - Static method in class org.apache.spark.storage.BroadcastBlockId
-
- productArity() - Static method in class org.apache.spark.storage.memory.DeserializedMemoryEntry
-
- productArity() - Static method in class org.apache.spark.storage.memory.SerializedMemoryEntry
-
- productArity() - Static method in class org.apache.spark.storage.RDDBlockId
-
- productArity() - Static method in class org.apache.spark.storage.ShuffleBlockId
-
- productArity() - Static method in class org.apache.spark.storage.ShuffleDataBlockId
-
- productArity() - Static method in class org.apache.spark.storage.ShuffleIndexBlockId
-
- productArity() - Static method in class org.apache.spark.storage.StreamBlockId
-
- productArity() - Static method in class org.apache.spark.storage.TaskResultBlockId
-
- productArity() - Static method in class org.apache.spark.streaming.Duration
-
- productArity() - Static method in class org.apache.spark.streaming.scheduler.AllReceiverIds
-
- productArity() - Static method in class org.apache.spark.streaming.scheduler.BatchInfo
-
- productArity() - Static method in class org.apache.spark.streaming.scheduler.GetAllReceiverInfo
-
- productArity() - Static method in class org.apache.spark.streaming.scheduler.OutputOperationInfo
-
- productArity() - Static method in class org.apache.spark.streaming.scheduler.ReceiverInfo
-
- productArity() - Static method in class org.apache.spark.streaming.scheduler.StopAllReceivers
-
- productArity() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchCompleted
-
- productArity() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchStarted
-
- productArity() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchSubmitted
-
- productArity() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerOutputOperationCompleted
-
- productArity() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerOutputOperationStarted
-
- productArity() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverError
-
- productArity() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStarted
-
- productArity() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStopped
-
- productArity() - Static method in class org.apache.spark.streaming.scheduler.StreamInputInfo
-
- productArity() - Static method in class org.apache.spark.streaming.Time
-
- productArity() - Static method in class org.apache.spark.Success
-
- productArity() - Static method in class org.apache.spark.TaskCommitDenied
-
- productArity() - Static method in class org.apache.spark.TaskKilled
-
- productArity() - Static method in class org.apache.spark.TaskResultLost
-
- productArity() - Static method in class org.apache.spark.TaskSchedulerIsSet
-
- productArity() - Static method in class org.apache.spark.UnknownReason
-
- productArity() - Static method in class org.apache.spark.util.MethodIdentifier
-
- productArity() - Static method in class org.apache.spark.util.MutablePair
-
- productElement(int) - Static method in class org.apache.spark.Aggregator
-
- productElement(int) - Static method in class org.apache.spark.CleanAccum
-
- productElement(int) - Static method in class org.apache.spark.CleanBroadcast
-
- productElement(int) - Static method in class org.apache.spark.CleanCheckpoint
-
- productElement(int) - Static method in class org.apache.spark.CleanRDD
-
- productElement(int) - Static method in class org.apache.spark.CleanShuffle
-
- productElement(int) - Static method in class org.apache.spark.ExceptionFailure
-
- productElement(int) - Static method in class org.apache.spark.ExecutorLostFailure
-
- productElement(int) - Static method in class org.apache.spark.ExecutorRegistered
-
- productElement(int) - Static method in class org.apache.spark.ExecutorRemoved
-
- productElement(int) - Static method in class org.apache.spark.ExpireDeadHosts
-
- productElement(int) - Static method in class org.apache.spark.FetchFailed
-
- productElement(int) - Static method in class org.apache.spark.graphx.Edge
-
- productElement(int) - Static method in class org.apache.spark.ml.feature.Dot
-
- productElement(int) - Static method in class org.apache.spark.ml.feature.LabeledPoint
-
- productElement(int) - Static method in class org.apache.spark.ml.param.ParamPair
-
- productElement(int) - Static method in class org.apache.spark.mllib.feature.VocabWord
-
- productElement(int) - Static method in class org.apache.spark.mllib.linalg.distributed.IndexedRow
-
- productElement(int) - Static method in class org.apache.spark.mllib.linalg.distributed.MatrixEntry
-
- productElement(int) - Static method in class org.apache.spark.mllib.linalg.QRDecomposition
-
- productElement(int) - Static method in class org.apache.spark.mllib.linalg.SingularValueDecomposition
-
- productElement(int) - Static method in class org.apache.spark.mllib.recommendation.Rating
-
- productElement(int) - Static method in class org.apache.spark.mllib.regression.LabeledPoint
-
- productElement(int) - Static method in class org.apache.spark.mllib.stat.test.BinarySample
-
- productElement(int) - Static method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- productElement(int) - Static method in class org.apache.spark.mllib.tree.model.Split
-
- productElement(int) - Static method in class org.apache.spark.Resubmitted
-
- productElement(int) - Static method in class org.apache.spark.rpc.netty.OnStart
-
- productElement(int) - Static method in class org.apache.spark.rpc.netty.OnStop
-
- productElement(int) - Static method in class org.apache.spark.scheduler.AccumulableInfo
-
- productElement(int) - Static method in class org.apache.spark.scheduler.AllJobsCancelled
-
- productElement(int) - Static method in class org.apache.spark.scheduler.AskPermissionToCommitOutput
-
- productElement(int) - Static method in class org.apache.spark.scheduler.JobSucceeded
-
- productElement(int) - Static method in class org.apache.spark.scheduler.local.KillTask
-
- productElement(int) - Static method in class org.apache.spark.scheduler.local.ReviveOffers
-
- productElement(int) - Static method in class org.apache.spark.scheduler.local.StatusUpdate
-
- productElement(int) - Static method in class org.apache.spark.scheduler.local.StopExecutor
-
- productElement(int) - Static method in class org.apache.spark.scheduler.ResubmitFailedStages
-
- productElement(int) - Static method in class org.apache.spark.scheduler.RuntimePercentage
-
- productElement(int) - Static method in class org.apache.spark.scheduler.SparkListenerApplicationEnd
-
- productElement(int) - Static method in class org.apache.spark.scheduler.SparkListenerApplicationStart
-
- productElement(int) - Static method in class org.apache.spark.scheduler.SparkListenerBlockManagerAdded
-
- productElement(int) - Static method in class org.apache.spark.scheduler.SparkListenerBlockManagerRemoved
-
- productElement(int) - Static method in class org.apache.spark.scheduler.SparkListenerBlockUpdated
-
- productElement(int) - Static method in class org.apache.spark.scheduler.SparkListenerEnvironmentUpdate
-
- productElement(int) - Static method in class org.apache.spark.scheduler.SparkListenerExecutorAdded
-
- productElement(int) - Static method in class org.apache.spark.scheduler.SparkListenerExecutorMetricsUpdate
-
- productElement(int) - Static method in class org.apache.spark.scheduler.SparkListenerExecutorRemoved
-
- productElement(int) - Static method in class org.apache.spark.scheduler.SparkListenerJobEnd
-
- productElement(int) - Static method in class org.apache.spark.scheduler.SparkListenerJobStart
-
- productElement(int) - Static method in class org.apache.spark.scheduler.SparkListenerStageCompleted
-
- productElement(int) - Static method in class org.apache.spark.scheduler.SparkListenerStageSubmitted
-
- productElement(int) - Static method in class org.apache.spark.scheduler.SparkListenerTaskEnd
-
- productElement(int) - Static method in class org.apache.spark.scheduler.SparkListenerTaskGettingResult
-
- productElement(int) - Static method in class org.apache.spark.scheduler.SparkListenerTaskStart
-
- productElement(int) - Static method in class org.apache.spark.scheduler.SparkListenerUnpersistRDD
-
- productElement(int) - Static method in class org.apache.spark.scheduler.StopCoordinator
-
- productElement(int) - Static method in class org.apache.spark.sql.DatasetHolder
-
- productElement(int) - Static method in class org.apache.spark.sql.expressions.UserDefinedFunction
-
- productElement(int) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- productElement(int) - Static method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- productElement(int) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- productElement(int) - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- productElement(int) - Static method in class org.apache.spark.sql.internal.HiveSerDe
-
- productElement(int) - Static method in class org.apache.spark.sql.jdbc.JdbcType
-
- productElement(int) - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
-
- productElement(int) - Static method in class org.apache.spark.sql.jdbc.OracleDialect
-
- productElement(int) - Static method in class org.apache.spark.sql.sources.And
-
- productElement(int) - Static method in class org.apache.spark.sql.sources.EqualNullSafe
-
- productElement(int) - Static method in class org.apache.spark.sql.sources.EqualTo
-
- productElement(int) - Static method in class org.apache.spark.sql.sources.GreaterThan
-
- productElement(int) - Static method in class org.apache.spark.sql.sources.GreaterThanOrEqual
-
- productElement(int) - Static method in class org.apache.spark.sql.sources.In
-
- productElement(int) - Static method in class org.apache.spark.sql.sources.IsNotNull
-
- productElement(int) - Static method in class org.apache.spark.sql.sources.IsNull
-
- productElement(int) - Static method in class org.apache.spark.sql.sources.LessThan
-
- productElement(int) - Static method in class org.apache.spark.sql.sources.LessThanOrEqual
-
- productElement(int) - Static method in class org.apache.spark.sql.sources.Not
-
- productElement(int) - Static method in class org.apache.spark.sql.sources.Or
-
- productElement(int) - Static method in class org.apache.spark.sql.sources.StringContains
-
- productElement(int) - Static method in class org.apache.spark.sql.sources.StringEndsWith
-
- productElement(int) - Static method in class org.apache.spark.sql.sources.StringStartsWith
-
- productElement(int) - Static method in class org.apache.spark.sql.streaming.ProcessingTime
-
- productElement(int) - Static method in class org.apache.spark.sql.types.ArrayType
-
- productElement(int) - Static method in class org.apache.spark.sql.types.DecimalType
-
- productElement(int) - Static method in class org.apache.spark.sql.types.MapType
-
- productElement(int) - Static method in class org.apache.spark.sql.types.StructField
-
- productElement(int) - Static method in class org.apache.spark.sql.types.StructType
-
- productElement(int) - Static method in class org.apache.spark.StopMapOutputTracker
-
- productElement(int) - Static method in class org.apache.spark.storage.BlockStatus
-
- productElement(int) - Static method in class org.apache.spark.storage.BlockUpdatedInfo
-
- productElement(int) - Static method in class org.apache.spark.storage.BroadcastBlockId
-
- productElement(int) - Static method in class org.apache.spark.storage.memory.DeserializedMemoryEntry
-
- productElement(int) - Static method in class org.apache.spark.storage.memory.SerializedMemoryEntry
-
- productElement(int) - Static method in class org.apache.spark.storage.RDDBlockId
-
- productElement(int) - Static method in class org.apache.spark.storage.ShuffleBlockId
-
- productElement(int) - Static method in class org.apache.spark.storage.ShuffleDataBlockId
-
- productElement(int) - Static method in class org.apache.spark.storage.ShuffleIndexBlockId
-
- productElement(int) - Static method in class org.apache.spark.storage.StreamBlockId
-
- productElement(int) - Static method in class org.apache.spark.storage.TaskResultBlockId
-
- productElement(int) - Static method in class org.apache.spark.streaming.Duration
-
- productElement(int) - Static method in class org.apache.spark.streaming.scheduler.AllReceiverIds
-
- productElement(int) - Static method in class org.apache.spark.streaming.scheduler.BatchInfo
-
- productElement(int) - Static method in class org.apache.spark.streaming.scheduler.GetAllReceiverInfo
-
- productElement(int) - Static method in class org.apache.spark.streaming.scheduler.OutputOperationInfo
-
- productElement(int) - Static method in class org.apache.spark.streaming.scheduler.ReceiverInfo
-
- productElement(int) - Static method in class org.apache.spark.streaming.scheduler.StopAllReceivers
-
- productElement(int) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchCompleted
-
- productElement(int) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchStarted
-
- productElement(int) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchSubmitted
-
- productElement(int) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerOutputOperationCompleted
-
- productElement(int) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerOutputOperationStarted
-
- productElement(int) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverError
-
- productElement(int) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStarted
-
- productElement(int) - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStopped
-
- productElement(int) - Static method in class org.apache.spark.streaming.scheduler.StreamInputInfo
-
- productElement(int) - Static method in class org.apache.spark.streaming.Time
-
- productElement(int) - Static method in class org.apache.spark.Success
-
- productElement(int) - Static method in class org.apache.spark.TaskCommitDenied
-
- productElement(int) - Static method in class org.apache.spark.TaskKilled
-
- productElement(int) - Static method in class org.apache.spark.TaskResultLost
-
- productElement(int) - Static method in class org.apache.spark.TaskSchedulerIsSet
-
- productElement(int) - Static method in class org.apache.spark.UnknownReason
-
- productElement(int) - Static method in class org.apache.spark.util.MethodIdentifier
-
- productElement(int) - Static method in class org.apache.spark.util.MutablePair
-
- productFeatures() - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
-
- productIterator() - Static method in class org.apache.spark.Aggregator
-
- productIterator() - Static method in class org.apache.spark.CleanAccum
-
- productIterator() - Static method in class org.apache.spark.CleanBroadcast
-
- productIterator() - Static method in class org.apache.spark.CleanCheckpoint
-
- productIterator() - Static method in class org.apache.spark.CleanRDD
-
- productIterator() - Static method in class org.apache.spark.CleanShuffle
-
- productIterator() - Static method in class org.apache.spark.ExceptionFailure
-
- productIterator() - Static method in class org.apache.spark.ExecutorLostFailure
-
- productIterator() - Static method in class org.apache.spark.ExecutorRegistered
-
- productIterator() - Static method in class org.apache.spark.ExecutorRemoved
-
- productIterator() - Static method in class org.apache.spark.ExpireDeadHosts
-
- productIterator() - Static method in class org.apache.spark.FetchFailed
-
- productIterator() - Static method in class org.apache.spark.graphx.Edge
-
- productIterator() - Static method in class org.apache.spark.ml.feature.Dot
-
- productIterator() - Static method in class org.apache.spark.ml.feature.LabeledPoint
-
- productIterator() - Static method in class org.apache.spark.ml.param.ParamPair
-
- productIterator() - Static method in class org.apache.spark.mllib.feature.VocabWord
-
- productIterator() - Static method in class org.apache.spark.mllib.linalg.distributed.IndexedRow
-
- productIterator() - Static method in class org.apache.spark.mllib.linalg.distributed.MatrixEntry
-
- productIterator() - Static method in class org.apache.spark.mllib.linalg.QRDecomposition
-
- productIterator() - Static method in class org.apache.spark.mllib.linalg.SingularValueDecomposition
-
- productIterator() - Static method in class org.apache.spark.mllib.recommendation.Rating
-
- productIterator() - Static method in class org.apache.spark.mllib.regression.LabeledPoint
-
- productIterator() - Static method in class org.apache.spark.mllib.stat.test.BinarySample
-
- productIterator() - Static method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- productIterator() - Static method in class org.apache.spark.mllib.tree.model.Split
-
- productIterator() - Static method in class org.apache.spark.Resubmitted
-
- productIterator() - Static method in class org.apache.spark.rpc.netty.OnStart
-
- productIterator() - Static method in class org.apache.spark.rpc.netty.OnStop
-
- productIterator() - Static method in class org.apache.spark.scheduler.AccumulableInfo
-
- productIterator() - Static method in class org.apache.spark.scheduler.AllJobsCancelled
-
- productIterator() - Static method in class org.apache.spark.scheduler.AskPermissionToCommitOutput
-
- productIterator() - Static method in class org.apache.spark.scheduler.JobSucceeded
-
- productIterator() - Static method in class org.apache.spark.scheduler.local.KillTask
-
- productIterator() - Static method in class org.apache.spark.scheduler.local.ReviveOffers
-
- productIterator() - Static method in class org.apache.spark.scheduler.local.StatusUpdate
-
- productIterator() - Static method in class org.apache.spark.scheduler.local.StopExecutor
-
- productIterator() - Static method in class org.apache.spark.scheduler.ResubmitFailedStages
-
- productIterator() - Static method in class org.apache.spark.scheduler.RuntimePercentage
-
- productIterator() - Static method in class org.apache.spark.scheduler.SparkListenerApplicationEnd
-
- productIterator() - Static method in class org.apache.spark.scheduler.SparkListenerApplicationStart
-
- productIterator() - Static method in class org.apache.spark.scheduler.SparkListenerBlockManagerAdded
-
- productIterator() - Static method in class org.apache.spark.scheduler.SparkListenerBlockManagerRemoved
-
- productIterator() - Static method in class org.apache.spark.scheduler.SparkListenerBlockUpdated
-
- productIterator() - Static method in class org.apache.spark.scheduler.SparkListenerEnvironmentUpdate
-
- productIterator() - Static method in class org.apache.spark.scheduler.SparkListenerExecutorAdded
-
- productIterator() - Static method in class org.apache.spark.scheduler.SparkListenerExecutorMetricsUpdate
-
- productIterator() - Static method in class org.apache.spark.scheduler.SparkListenerExecutorRemoved
-
- productIterator() - Static method in class org.apache.spark.scheduler.SparkListenerJobEnd
-
- productIterator() - Static method in class org.apache.spark.scheduler.SparkListenerJobStart
-
- productIterator() - Static method in class org.apache.spark.scheduler.SparkListenerStageCompleted
-
- productIterator() - Static method in class org.apache.spark.scheduler.SparkListenerStageSubmitted
-
- productIterator() - Static method in class org.apache.spark.scheduler.SparkListenerTaskEnd
-
- productIterator() - Static method in class org.apache.spark.scheduler.SparkListenerTaskGettingResult
-
- productIterator() - Static method in class org.apache.spark.scheduler.SparkListenerTaskStart
-
- productIterator() - Static method in class org.apache.spark.scheduler.SparkListenerUnpersistRDD
-
- productIterator() - Static method in class org.apache.spark.scheduler.StopCoordinator
-
- productIterator() - Static method in class org.apache.spark.sql.DatasetHolder
-
- productIterator() - Static method in class org.apache.spark.sql.expressions.UserDefinedFunction
-
- productIterator() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- productIterator() - Static method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- productIterator() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- productIterator() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- productIterator() - Static method in class org.apache.spark.sql.internal.HiveSerDe
-
- productIterator() - Static method in class org.apache.spark.sql.jdbc.JdbcType
-
- productIterator() - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
-
- productIterator() - Static method in class org.apache.spark.sql.jdbc.OracleDialect
-
- productIterator() - Static method in class org.apache.spark.sql.sources.And
-
- productIterator() - Static method in class org.apache.spark.sql.sources.EqualNullSafe
-
- productIterator() - Static method in class org.apache.spark.sql.sources.EqualTo
-
- productIterator() - Static method in class org.apache.spark.sql.sources.GreaterThan
-
- productIterator() - Static method in class org.apache.spark.sql.sources.GreaterThanOrEqual
-
- productIterator() - Static method in class org.apache.spark.sql.sources.In
-
- productIterator() - Static method in class org.apache.spark.sql.sources.IsNotNull
-
- productIterator() - Static method in class org.apache.spark.sql.sources.IsNull
-
- productIterator() - Static method in class org.apache.spark.sql.sources.LessThan
-
- productIterator() - Static method in class org.apache.spark.sql.sources.LessThanOrEqual
-
- productIterator() - Static method in class org.apache.spark.sql.sources.Not
-
- productIterator() - Static method in class org.apache.spark.sql.sources.Or
-
- productIterator() - Static method in class org.apache.spark.sql.sources.StringContains
-
- productIterator() - Static method in class org.apache.spark.sql.sources.StringEndsWith
-
- productIterator() - Static method in class org.apache.spark.sql.sources.StringStartsWith
-
- productIterator() - Static method in class org.apache.spark.sql.streaming.ProcessingTime
-
- productIterator() - Static method in class org.apache.spark.sql.types.ArrayType
-
- productIterator() - Static method in class org.apache.spark.sql.types.DecimalType
-
- productIterator() - Static method in class org.apache.spark.sql.types.MapType
-
- productIterator() - Static method in class org.apache.spark.sql.types.StructField
-
- productIterator() - Static method in class org.apache.spark.sql.types.StructType
-
- productIterator() - Static method in class org.apache.spark.StopMapOutputTracker
-
- productIterator() - Static method in class org.apache.spark.storage.BlockStatus
-
- productIterator() - Static method in class org.apache.spark.storage.BlockUpdatedInfo
-
- productIterator() - Static method in class org.apache.spark.storage.BroadcastBlockId
-
- productIterator() - Static method in class org.apache.spark.storage.memory.DeserializedMemoryEntry
-
- productIterator() - Static method in class org.apache.spark.storage.memory.SerializedMemoryEntry
-
- productIterator() - Static method in class org.apache.spark.storage.RDDBlockId
-
- productIterator() - Static method in class org.apache.spark.storage.ShuffleBlockId
-
- productIterator() - Static method in class org.apache.spark.storage.ShuffleDataBlockId
-
- productIterator() - Static method in class org.apache.spark.storage.ShuffleIndexBlockId
-
- productIterator() - Static method in class org.apache.spark.storage.StreamBlockId
-
- productIterator() - Static method in class org.apache.spark.storage.TaskResultBlockId
-
- productIterator() - Static method in class org.apache.spark.streaming.Duration
-
- productIterator() - Static method in class org.apache.spark.streaming.scheduler.AllReceiverIds
-
- productIterator() - Static method in class org.apache.spark.streaming.scheduler.BatchInfo
-
- productIterator() - Static method in class org.apache.spark.streaming.scheduler.GetAllReceiverInfo
-
- productIterator() - Static method in class org.apache.spark.streaming.scheduler.OutputOperationInfo
-
- productIterator() - Static method in class org.apache.spark.streaming.scheduler.ReceiverInfo
-
- productIterator() - Static method in class org.apache.spark.streaming.scheduler.StopAllReceivers
-
- productIterator() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchCompleted
-
- productIterator() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchStarted
-
- productIterator() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchSubmitted
-
- productIterator() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerOutputOperationCompleted
-
- productIterator() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerOutputOperationStarted
-
- productIterator() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverError
-
- productIterator() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStarted
-
- productIterator() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStopped
-
- productIterator() - Static method in class org.apache.spark.streaming.scheduler.StreamInputInfo
-
- productIterator() - Static method in class org.apache.spark.streaming.Time
-
- productIterator() - Static method in class org.apache.spark.Success
-
- productIterator() - Static method in class org.apache.spark.TaskCommitDenied
-
- productIterator() - Static method in class org.apache.spark.TaskKilled
-
- productIterator() - Static method in class org.apache.spark.TaskResultLost
-
- productIterator() - Static method in class org.apache.spark.TaskSchedulerIsSet
-
- productIterator() - Static method in class org.apache.spark.UnknownReason
-
- productIterator() - Static method in class org.apache.spark.util.MethodIdentifier
-
- productIterator() - Static method in class org.apache.spark.util.MutablePair
-
- productPrefix() - Static method in class org.apache.spark.Aggregator
-
- productPrefix() - Static method in class org.apache.spark.CleanAccum
-
- productPrefix() - Static method in class org.apache.spark.CleanBroadcast
-
- productPrefix() - Static method in class org.apache.spark.CleanCheckpoint
-
- productPrefix() - Static method in class org.apache.spark.CleanRDD
-
- productPrefix() - Static method in class org.apache.spark.CleanShuffle
-
- productPrefix() - Static method in class org.apache.spark.ExceptionFailure
-
- productPrefix() - Static method in class org.apache.spark.ExecutorLostFailure
-
- productPrefix() - Static method in class org.apache.spark.ExecutorRegistered
-
- productPrefix() - Static method in class org.apache.spark.ExecutorRemoved
-
- productPrefix() - Static method in class org.apache.spark.ExpireDeadHosts
-
- productPrefix() - Static method in class org.apache.spark.FetchFailed
-
- productPrefix() - Static method in class org.apache.spark.graphx.Edge
-
- productPrefix() - Static method in class org.apache.spark.ml.feature.Dot
-
- productPrefix() - Static method in class org.apache.spark.ml.feature.LabeledPoint
-
- productPrefix() - Static method in class org.apache.spark.ml.param.ParamPair
-
- productPrefix() - Static method in class org.apache.spark.mllib.feature.VocabWord
-
- productPrefix() - Static method in class org.apache.spark.mllib.linalg.distributed.IndexedRow
-
- productPrefix() - Static method in class org.apache.spark.mllib.linalg.distributed.MatrixEntry
-
- productPrefix() - Static method in class org.apache.spark.mllib.linalg.QRDecomposition
-
- productPrefix() - Static method in class org.apache.spark.mllib.linalg.SingularValueDecomposition
-
- productPrefix() - Static method in class org.apache.spark.mllib.recommendation.Rating
-
- productPrefix() - Static method in class org.apache.spark.mllib.regression.LabeledPoint
-
- productPrefix() - Static method in class org.apache.spark.mllib.stat.test.BinarySample
-
- productPrefix() - Static method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- productPrefix() - Static method in class org.apache.spark.mllib.tree.model.Split
-
- productPrefix() - Static method in class org.apache.spark.Resubmitted
-
- productPrefix() - Static method in class org.apache.spark.rpc.netty.OnStart
-
- productPrefix() - Static method in class org.apache.spark.rpc.netty.OnStop
-
- productPrefix() - Static method in class org.apache.spark.scheduler.AccumulableInfo
-
- productPrefix() - Static method in class org.apache.spark.scheduler.AllJobsCancelled
-
- productPrefix() - Static method in class org.apache.spark.scheduler.AskPermissionToCommitOutput
-
- productPrefix() - Static method in class org.apache.spark.scheduler.JobSucceeded
-
- productPrefix() - Static method in class org.apache.spark.scheduler.local.KillTask
-
- productPrefix() - Static method in class org.apache.spark.scheduler.local.ReviveOffers
-
- productPrefix() - Static method in class org.apache.spark.scheduler.local.StatusUpdate
-
- productPrefix() - Static method in class org.apache.spark.scheduler.local.StopExecutor
-
- productPrefix() - Static method in class org.apache.spark.scheduler.ResubmitFailedStages
-
- productPrefix() - Static method in class org.apache.spark.scheduler.RuntimePercentage
-
- productPrefix() - Static method in class org.apache.spark.scheduler.SparkListenerApplicationEnd
-
- productPrefix() - Static method in class org.apache.spark.scheduler.SparkListenerApplicationStart
-
- productPrefix() - Static method in class org.apache.spark.scheduler.SparkListenerBlockManagerAdded
-
- productPrefix() - Static method in class org.apache.spark.scheduler.SparkListenerBlockManagerRemoved
-
- productPrefix() - Static method in class org.apache.spark.scheduler.SparkListenerBlockUpdated
-
- productPrefix() - Static method in class org.apache.spark.scheduler.SparkListenerEnvironmentUpdate
-
- productPrefix() - Static method in class org.apache.spark.scheduler.SparkListenerExecutorAdded
-
- productPrefix() - Static method in class org.apache.spark.scheduler.SparkListenerExecutorMetricsUpdate
-
- productPrefix() - Static method in class org.apache.spark.scheduler.SparkListenerExecutorRemoved
-
- productPrefix() - Static method in class org.apache.spark.scheduler.SparkListenerJobEnd
-
- productPrefix() - Static method in class org.apache.spark.scheduler.SparkListenerJobStart
-
- productPrefix() - Static method in class org.apache.spark.scheduler.SparkListenerStageCompleted
-
- productPrefix() - Static method in class org.apache.spark.scheduler.SparkListenerStageSubmitted
-
- productPrefix() - Static method in class org.apache.spark.scheduler.SparkListenerTaskEnd
-
- productPrefix() - Static method in class org.apache.spark.scheduler.SparkListenerTaskGettingResult
-
- productPrefix() - Static method in class org.apache.spark.scheduler.SparkListenerTaskStart
-
- productPrefix() - Static method in class org.apache.spark.scheduler.SparkListenerUnpersistRDD
-
- productPrefix() - Static method in class org.apache.spark.scheduler.StopCoordinator
-
- productPrefix() - Static method in class org.apache.spark.sql.DatasetHolder
-
- productPrefix() - Static method in class org.apache.spark.sql.expressions.UserDefinedFunction
-
- productPrefix() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- productPrefix() - Static method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- productPrefix() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- productPrefix() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- productPrefix() - Static method in class org.apache.spark.sql.internal.HiveSerDe
-
- productPrefix() - Static method in class org.apache.spark.sql.jdbc.JdbcType
-
- productPrefix() - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
-
- productPrefix() - Static method in class org.apache.spark.sql.jdbc.OracleDialect
-
- productPrefix() - Static method in class org.apache.spark.sql.sources.And
-
- productPrefix() - Static method in class org.apache.spark.sql.sources.EqualNullSafe
-
- productPrefix() - Static method in class org.apache.spark.sql.sources.EqualTo
-
- productPrefix() - Static method in class org.apache.spark.sql.sources.GreaterThan
-
- productPrefix() - Static method in class org.apache.spark.sql.sources.GreaterThanOrEqual
-
- productPrefix() - Static method in class org.apache.spark.sql.sources.In
-
- productPrefix() - Static method in class org.apache.spark.sql.sources.IsNotNull
-
- productPrefix() - Static method in class org.apache.spark.sql.sources.IsNull
-
- productPrefix() - Static method in class org.apache.spark.sql.sources.LessThan
-
- productPrefix() - Static method in class org.apache.spark.sql.sources.LessThanOrEqual
-
- productPrefix() - Static method in class org.apache.spark.sql.sources.Not
-
- productPrefix() - Static method in class org.apache.spark.sql.sources.Or
-
- productPrefix() - Static method in class org.apache.spark.sql.sources.StringContains
-
- productPrefix() - Static method in class org.apache.spark.sql.sources.StringEndsWith
-
- productPrefix() - Static method in class org.apache.spark.sql.sources.StringStartsWith
-
- productPrefix() - Static method in class org.apache.spark.sql.streaming.ProcessingTime
-
- productPrefix() - Static method in class org.apache.spark.sql.types.ArrayType
-
- productPrefix() - Static method in class org.apache.spark.sql.types.DecimalType
-
- productPrefix() - Static method in class org.apache.spark.sql.types.MapType
-
- productPrefix() - Static method in class org.apache.spark.sql.types.StructField
-
- productPrefix() - Static method in class org.apache.spark.sql.types.StructType
-
- productPrefix() - Static method in class org.apache.spark.StopMapOutputTracker
-
- productPrefix() - Static method in class org.apache.spark.storage.BlockStatus
-
- productPrefix() - Static method in class org.apache.spark.storage.BlockUpdatedInfo
-
- productPrefix() - Static method in class org.apache.spark.storage.BroadcastBlockId
-
- productPrefix() - Static method in class org.apache.spark.storage.memory.DeserializedMemoryEntry
-
- productPrefix() - Static method in class org.apache.spark.storage.memory.SerializedMemoryEntry
-
- productPrefix() - Static method in class org.apache.spark.storage.RDDBlockId
-
- productPrefix() - Static method in class org.apache.spark.storage.ShuffleBlockId
-
- productPrefix() - Static method in class org.apache.spark.storage.ShuffleDataBlockId
-
- productPrefix() - Static method in class org.apache.spark.storage.ShuffleIndexBlockId
-
- productPrefix() - Static method in class org.apache.spark.storage.StreamBlockId
-
- productPrefix() - Static method in class org.apache.spark.storage.TaskResultBlockId
-
- productPrefix() - Static method in class org.apache.spark.streaming.Duration
-
- productPrefix() - Static method in class org.apache.spark.streaming.scheduler.AllReceiverIds
-
- productPrefix() - Static method in class org.apache.spark.streaming.scheduler.BatchInfo
-
- productPrefix() - Static method in class org.apache.spark.streaming.scheduler.GetAllReceiverInfo
-
- productPrefix() - Static method in class org.apache.spark.streaming.scheduler.OutputOperationInfo
-
- productPrefix() - Static method in class org.apache.spark.streaming.scheduler.ReceiverInfo
-
- productPrefix() - Static method in class org.apache.spark.streaming.scheduler.StopAllReceivers
-
- productPrefix() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchCompleted
-
- productPrefix() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchStarted
-
- productPrefix() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerBatchSubmitted
-
- productPrefix() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerOutputOperationCompleted
-
- productPrefix() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerOutputOperationStarted
-
- productPrefix() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverError
-
- productPrefix() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStarted
-
- productPrefix() - Static method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStopped
-
- productPrefix() - Static method in class org.apache.spark.streaming.scheduler.StreamInputInfo
-
- productPrefix() - Static method in class org.apache.spark.streaming.Time
-
- productPrefix() - Static method in class org.apache.spark.Success
-
- productPrefix() - Static method in class org.apache.spark.TaskCommitDenied
-
- productPrefix() - Static method in class org.apache.spark.TaskKilled
-
- productPrefix() - Static method in class org.apache.spark.TaskResultLost
-
- productPrefix() - Static method in class org.apache.spark.TaskSchedulerIsSet
-
- productPrefix() - Static method in class org.apache.spark.UnknownReason
-
- productPrefix() - Static method in class org.apache.spark.util.MethodIdentifier
-
- productPrefix() - Static method in class org.apache.spark.util.MutablePair
-
- project(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Binomial$
-
- project(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gamma$
-
- project(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gaussian$
-
- project(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Poisson$
-
- properties() - Method in class org.apache.spark.scheduler.SparkListenerJobStart
-
- properties() - Method in class org.apache.spark.scheduler.SparkListenerStageSubmitted
-
- propertiesFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
- propertiesToJson(Properties) - Static method in class org.apache.spark.util.JsonProtocol
-
- proxyBase() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.AddWebUIFilter
-
- PrunedFilteredScan - Interface in org.apache.spark.sql.sources
-
::DeveloperApi::
A BaseRelation that can eliminate unneeded columns and filter using selected
predicates before producing an RDD containing all matching tuples as Row objects.
- PrunedScan - Interface in org.apache.spark.sql.sources
-
::DeveloperApi::
A BaseRelation that can eliminate unneeded columns before producing an RDD
containing all of its tuples as Row objects.
- Pseudorandom - Interface in org.apache.spark.util.random
-
:: DeveloperApi ::
A class with pseudorandom behavior.
- put(Object) - Static method in class org.apache.spark.api.r.JVMObjectTracker
-
- put(ParamPair<?>...) - Method in class org.apache.spark.ml.param.ParamMap
-
Puts a list of param pairs (overwrites if the input params exists).
- put(Param<T>, T) - Method in class org.apache.spark.ml.param.ParamMap
-
Puts a (param, value) pair (overwrites if the input param exists).
- put(Seq<ParamPair<?>>) - Method in class org.apache.spark.ml.param.ParamMap
-
Puts a list of param pairs (overwrites if the input params exists).
- put(Object) - Method in class org.apache.spark.util.sketch.BloomFilter
-
Puts an item into this BloomFilter.
- putBinary(byte[]) - Method in class org.apache.spark.util.sketch.BloomFilter
-
- putBoolean(String, boolean) - Method in class org.apache.spark.sql.types.MetadataBuilder
-
Puts a Boolean.
- putBooleanArray(String, boolean[]) - Method in class org.apache.spark.sql.types.MetadataBuilder
-
Puts a Boolean array.
- putDouble(String, double) - Method in class org.apache.spark.sql.types.MetadataBuilder
-
Puts a Double.
- putDoubleArray(String, double[]) - Method in class org.apache.spark.sql.types.MetadataBuilder
-
Puts a Double array.
- putLong(String, long) - Method in class org.apache.spark.sql.types.MetadataBuilder
-
Puts a Long.
- putLong(long) - Method in class org.apache.spark.util.sketch.BloomFilter
-
- putLongArray(String, long[]) - Method in class org.apache.spark.sql.types.MetadataBuilder
-
Puts a Long array.
- putMetadata(String, Metadata) - Method in class org.apache.spark.sql.types.MetadataBuilder
-
- putMetadataArray(String, Metadata[]) - Method in class org.apache.spark.sql.types.MetadataBuilder
-
- putNull(String) - Method in class org.apache.spark.sql.types.MetadataBuilder
-
Puts a null.
- putString(String, String) - Method in class org.apache.spark.sql.types.MetadataBuilder
-
Puts a String.
- putString(String) - Method in class org.apache.spark.util.sketch.BloomFilter
-
- putStringArray(String, String[]) - Method in class org.apache.spark.sql.types.MetadataBuilder
-
Puts a String array.
- pValue() - Method in class org.apache.spark.mllib.stat.test.ChiSqTestResult
-
- pValue() - Method in class org.apache.spark.mllib.stat.test.KolmogorovSmirnovTestResult
-
- pValue() - Method in interface org.apache.spark.mllib.stat.test.TestResult
-
The probability of obtaining a test statistic result at least as extreme as the one that was
actually observed, assuming that the null hypothesis is true.
- pValues() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionTrainingSummary
-
Two-sided p-value of estimated coefficients and intercept.
- pValues() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
-
Two-sided p-value of estimated coefficients and intercept.
- pyUDT() - Method in class org.apache.spark.mllib.linalg.VectorUDT
-
- R() - Method in class org.apache.spark.mllib.linalg.QRDecomposition
-
- r2() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
-
Returns R^2^, the coefficient of determination.
- r2() - Method in class org.apache.spark.mllib.evaluation.RegressionMetrics
-
Returns R^2^, the unadjusted coefficient of determination.
- RACK_LOCAL() - Static method in class org.apache.spark.scheduler.TaskLocality
-
- rand(int, int, Random) - Static method in class org.apache.spark.ml.linalg.DenseMatrix
-
Generate a DenseMatrix consisting of i.i.d. uniform random numbers.
- rand(int, int, Random) - Static method in class org.apache.spark.ml.linalg.Matrices
-
Generate a DenseMatrix consisting of i.i.d. uniform random numbers.
- rand(int, int, Random) - Static method in class org.apache.spark.mllib.linalg.DenseMatrix
-
Generate a DenseMatrix consisting of i.i.d. uniform random numbers.
- rand(int, int, Random) - Static method in class org.apache.spark.mllib.linalg.Matrices
-
Generate a DenseMatrix consisting of i.i.d. uniform random numbers.
- rand(long) - Static method in class org.apache.spark.sql.functions
-
Generate a random column with i.i.d.
- rand() - Static method in class org.apache.spark.sql.functions
-
Generate a random column with i.i.d.
- randn(int, int, Random) - Static method in class org.apache.spark.ml.linalg.DenseMatrix
-
Generate a DenseMatrix consisting of i.i.d. gaussian random numbers.
- randn(int, int, Random) - Static method in class org.apache.spark.ml.linalg.Matrices
-
Generate a DenseMatrix consisting of i.i.d. gaussian random numbers.
- randn(int, int, Random) - Static method in class org.apache.spark.mllib.linalg.DenseMatrix
-
Generate a DenseMatrix consisting of i.i.d. gaussian random numbers.
- randn(int, int, Random) - Static method in class org.apache.spark.mllib.linalg.Matrices
-
Generate a DenseMatrix consisting of i.i.d. gaussian random numbers.
- randn(long) - Static method in class org.apache.spark.sql.functions
-
Generate a column with i.i.d.
- randn() - Static method in class org.apache.spark.sql.functions
-
Generate a column with i.i.d.
- RANDOM() - Static method in class org.apache.spark.mllib.clustering.KMeans
-
- random() - Static method in class org.apache.spark.util.Utils
-
- RandomDataGenerator<T> - Interface in org.apache.spark.mllib.random
-
:: DeveloperApi ::
Trait for random data generators that generate i.i.d.
- RandomForest - Class in org.apache.spark.ml.tree.impl
-
ALGORITHM
- RandomForest() - Constructor for class org.apache.spark.ml.tree.impl.RandomForest
-
- RandomForest - Class in org.apache.spark.mllib.tree
-
A class that implements a Random Forest
learning algorithm for classification and regression.
- RandomForest(Strategy, int, String, int) - Constructor for class org.apache.spark.mllib.tree.RandomForest
-
- RandomForestClassificationModel - Class in org.apache.spark.ml.classification
-
Random Forest model for classification.
- RandomForestClassifier - Class in org.apache.spark.ml.classification
-
Random Forest learning algorithm for
classification.
- RandomForestClassifier(String) - Constructor for class org.apache.spark.ml.classification.RandomForestClassifier
-
- RandomForestClassifier() - Constructor for class org.apache.spark.ml.classification.RandomForestClassifier
-
- RandomForestModel - Class in org.apache.spark.mllib.tree.model
-
Represents a random forest model.
- RandomForestModel(Enumeration.Value, DecisionTreeModel[]) - Constructor for class org.apache.spark.mllib.tree.model.RandomForestModel
-
- RandomForestRegressionModel - Class in org.apache.spark.ml.regression
-
Random Forest model for regression.
- RandomForestRegressor - Class in org.apache.spark.ml.regression
-
Random Forest learning algorithm for regression.
- RandomForestRegressor(String) - Constructor for class org.apache.spark.ml.regression.RandomForestRegressor
-
- RandomForestRegressor() - Constructor for class org.apache.spark.ml.regression.RandomForestRegressor
-
- randomize(TraversableOnce<T>, ClassTag<T>) - Static method in class org.apache.spark.util.Utils
-
Shuffle the elements of a collection into a random order, returning the
result in a new collection.
- randomizeInPlace(Object, Random) - Static method in class org.apache.spark.util.Utils
-
Shuffle the elements of an array into a random order, modifying the
original array.
- randomJavaRDD(JavaSparkContext, RandomDataGenerator<T>, long, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
:: DeveloperApi ::
Generates an RDD comprised of i.i.d. samples produced by the input RandomDataGenerator.
- randomJavaRDD(JavaSparkContext, RandomDataGenerator<T>, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- randomJavaRDD(JavaSparkContext, RandomDataGenerator<T>, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- randomJavaVectorRDD(JavaSparkContext, RandomDataGenerator<Object>, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- randomJavaVectorRDD(JavaSparkContext, RandomDataGenerator<Object>, long, int, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- randomJavaVectorRDD(JavaSparkContext, RandomDataGenerator<Object>, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
- randomRDD(SparkContext, RandomDataGenerator<T>, long, int, long, ClassTag<T>) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
:: DeveloperApi ::
Generates an RDD comprised of i.i.d. samples produced by the input RandomDataGenerator.
- RandomRDDs - Class in org.apache.spark.mllib.random
-
Generator methods for creating RDDs comprised of i.i.d. samples from some distribution.
- RandomRDDs() - Constructor for class org.apache.spark.mllib.random.RandomRDDs
-
- RandomSampler<T,U> - Interface in org.apache.spark.util.random
-
:: DeveloperApi ::
A pseudorandom sampler.
- randomSplit(double[]) - Method in class org.apache.spark.api.java.JavaRDD
-
Randomly splits this RDD with the provided weights.
- randomSplit(double[], long) - Method in class org.apache.spark.api.java.JavaRDD
-
Randomly splits this RDD with the provided weights.
- randomSplit(double[], long) - Static method in class org.apache.spark.api.r.RRDD
-
- randomSplit(double[], long) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- randomSplit(double[], long) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- randomSplit(double[], long) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- randomSplit(double[], long) - Static method in class org.apache.spark.graphx.VertexRDD
-
- randomSplit(double[], long) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- randomSplit(double[], long) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- randomSplit(double[], long) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- randomSplit(double[], long) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- randomSplit(double[], long) - Method in class org.apache.spark.rdd.RDD
-
Randomly splits this RDD with the provided weights.
- randomSplit(double[], long) - Static method in class org.apache.spark.rdd.UnionRDD
-
- randomSplit(double[], long) - Method in class org.apache.spark.sql.Dataset
-
Randomly splits this Dataset with the provided weights.
- randomSplit(double[]) - Method in class org.apache.spark.sql.Dataset
-
Randomly splits this Dataset with the provided weights.
- randomSplit$default$2() - Static method in class org.apache.spark.api.r.RRDD
-
- randomSplit$default$2() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- randomSplit$default$2() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- randomSplit$default$2() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- randomSplit$default$2() - Static method in class org.apache.spark.graphx.VertexRDD
-
- randomSplit$default$2() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- randomSplit$default$2() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- randomSplit$default$2() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- randomSplit$default$2() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- randomSplit$default$2() - Static method in class org.apache.spark.rdd.UnionRDD
-
- randomSplitAsList(double[], long) - Method in class org.apache.spark.sql.Dataset
-
Returns a Java list that contains randomly split Dataset with the provided weights.
- randomVectorRDD(SparkContext, RandomDataGenerator<Object>, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
:: DeveloperApi ::
Generates an RDD[Vector] with vectors containing i.i.d. samples produced by the
input RandomDataGenerator.
- range(long, long, long, int) - Method in class org.apache.spark.SparkContext
-
Creates a new RDD[Long] containing elements from start to end(exclusive), increased by
step every element.
- range(long) - Method in class org.apache.spark.sql.SparkSession
-
:: Experimental ::
Creates a
Dataset with a single
LongType column named
id, containing elements
in a range from 0 to
end (exclusive) with step value 1.
- range(long, long) - Method in class org.apache.spark.sql.SparkSession
-
:: Experimental ::
Creates a
Dataset with a single
LongType column named
id, containing elements
in a range from
start to
end (exclusive) with step value 1.
- range(long, long, long) - Method in class org.apache.spark.sql.SparkSession
-
:: Experimental ::
Creates a
Dataset with a single
LongType column named
id, containing elements
in a range from
start to
end (exclusive) with a step value.
- range(long, long, long, int) - Method in class org.apache.spark.sql.SparkSession
-
:: Experimental ::
Creates a
Dataset with a single
LongType column named
id, containing elements
in a range from
start to
end (exclusive) with a step value, with partition number
specified.
- range(long) - Method in class org.apache.spark.sql.SQLContext
-
- range(long, long) - Method in class org.apache.spark.sql.SQLContext
-
- range(long, long, long) - Method in class org.apache.spark.sql.SQLContext
-
- range(long, long, long, int) - Method in class org.apache.spark.sql.SQLContext
-
- rangeBetween(long, long) - Method in class org.apache.spark.sql.expressions.WindowSpec
-
Defines the frame boundaries, from start (inclusive) to end (inclusive).
- RangeDependency<T> - Class in org.apache.spark
-
:: DeveloperApi ::
Represents a one-to-one dependency between ranges of partitions in the parent and child RDDs.
- RangeDependency(RDD<T>, int, int, int) - Constructor for class org.apache.spark.RangeDependency
-
- RangePartitioner<K,V> - Class in org.apache.spark
-
A
Partitioner that partitions sortable records by range into roughly
equal ranges.
- RangePartitioner(int, RDD<? extends Product2<K, V>>, boolean, Ordering<K>, ClassTag<K>) - Constructor for class org.apache.spark.RangePartitioner
-
- rank() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
-
- rank() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- rank() - Method in class org.apache.spark.ml.recommendation.ALSModel
-
- rank() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
-
The numeric rank of the fitted linear model.
- rank() - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
-
- rank() - Static method in class org.apache.spark.sql.functions
-
Window function: returns the rank of rows within a window partition.
- RankingMetrics<T> - Class in org.apache.spark.mllib.evaluation
-
Evaluator for ranking algorithms.
- RankingMetrics(RDD<Tuple2<Object, Object>>, ClassTag<T>) - Constructor for class org.apache.spark.mllib.evaluation.RankingMetrics
-
- rating() - Method in class org.apache.spark.ml.recommendation.ALS.Rating
-
- Rating - Class in org.apache.spark.mllib.recommendation
-
A more compact class to represent a rating than Tuple3[Int, Int, Double].
- Rating(int, int, double) - Constructor for class org.apache.spark.mllib.recommendation.Rating
-
- rating() - Method in class org.apache.spark.mllib.recommendation.Rating
-
- ratingCol() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- rawPredictionCol() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- rawPredictionCol() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- rawPredictionCol() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- rawPredictionCol() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- rawPredictionCol() - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- rawPredictionCol() - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- rawPredictionCol() - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- rawPredictionCol() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- rawPredictionCol() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- rawPredictionCol() - Static method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- rawSocketStream(String, int, StorageLevel) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Create an input stream from network source hostname:port, where data is received
as serialized blocks (serialized using the Spark's serializer) that can be directly
pushed into the block manager without deserializing them.
- rawSocketStream(String, int) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Create an input stream from network source hostname:port, where data is received
as serialized blocks (serialized using the Spark's serializer) that can be directly
pushed into the block manager without deserializing them.
- rawSocketStream(String, int, StorageLevel, ClassTag<T>) - Method in class org.apache.spark.streaming.StreamingContext
-
Create an input stream from network source hostname:port, where data is received
as serialized blocks (serialized using the Spark's serializer) that can be directly
pushed into the block manager without deserializing them.
- RawTextHelper - Class in org.apache.spark.streaming.util
-
- RawTextHelper() - Constructor for class org.apache.spark.streaming.util.RawTextHelper
-
- RawTextSender - Class in org.apache.spark.streaming.util
-
A helper program that sends blocks of Kryo-serialized text strings out on a socket at a
specified rate.
- RawTextSender() - Constructor for class org.apache.spark.streaming.util.RawTextSender
-
- rdd() - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
- rdd() - Method in class org.apache.spark.api.java.JavaPairRDD
-
- rdd() - Method in class org.apache.spark.api.java.JavaRDD
-
- rdd() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
- RDD() - Static method in class org.apache.spark.api.r.RRunnerModes
-
- rdd() - Method in class org.apache.spark.Dependency
-
- rdd() - Method in class org.apache.spark.NarrowDependency
-
- RDD<T> - Class in org.apache.spark.rdd
-
A Resilient Distributed Dataset (RDD), the basic abstraction in Spark.
- RDD(SparkContext, Seq<Dependency<?>>, ClassTag<T>) - Constructor for class org.apache.spark.rdd.RDD
-
- RDD(RDD<?>, ClassTag<T>) - Constructor for class org.apache.spark.rdd.RDD
-
Construct an RDD with just a one-to-one dependency on one parent
- rdd() - Method in class org.apache.spark.ShuffleDependency
-
- rdd() - Method in class org.apache.spark.sql.Dataset
-
Represents the content of the Dataset as an RDD of T.
- RDD() - Static method in class org.apache.spark.storage.BlockId
-
- RDDBlockId - Class in org.apache.spark.storage
-
- RDDBlockId(int, int) - Constructor for class org.apache.spark.storage.RDDBlockId
-
- rddBlocks() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
-
- rddBlocks() - Method in class org.apache.spark.storage.StorageStatus
-
Return the RDD blocks stored in this block manager.
- rddBlocksById(int) - Method in class org.apache.spark.storage.StorageStatus
-
Return the blocks that belong to the given RDD stored in this block manager.
- RDDDataDistribution - Class in org.apache.spark.status.api.v1
-
- RDDFunctions<T> - Class in org.apache.spark.mllib.rdd
-
:: DeveloperApi ::
Machine learning specific RDD functions.
- RDDFunctions(RDD<T>, ClassTag<T>) - Constructor for class org.apache.spark.mllib.rdd.RDDFunctions
-
- rddId() - Method in class org.apache.spark.CleanCheckpoint
-
- rddId() - Method in class org.apache.spark.CleanRDD
-
- rddId() - Method in class org.apache.spark.scheduler.SparkListenerUnpersistRDD
-
- rddId() - Method in class org.apache.spark.storage.BlockManagerMessages.RemoveRdd
-
- rddId() - Method in class org.apache.spark.storage.RDDBlockId
-
- RDDInfo - Class in org.apache.spark.storage
-
- RDDInfo(int, String, int, StorageLevel, Seq<Object>, String, Option<org.apache.spark.rdd.RDDOperationScope>) - Constructor for class org.apache.spark.storage.RDDInfo
-
- rddInfoFromJson(JsonAST.JValue) - Static method in class org.apache.spark.util.JsonProtocol
-
- rddInfoList() - Method in class org.apache.spark.ui.storage.StorageListener
-
Filter RDD info to include only those with cached partitions
- rddInfos() - Method in class org.apache.spark.scheduler.StageInfo
-
- rddInfoToJson(RDDInfo) - Static method in class org.apache.spark.util.JsonProtocol
-
- RDDPartitionInfo - Class in org.apache.spark.status.api.v1
-
- rdds() - Method in class org.apache.spark.rdd.CoGroupedRDD
-
- rdds() - Method in class org.apache.spark.rdd.UnionRDD
-
- RDDStorageInfo - Class in org.apache.spark.status.api.v1
-
- rddStorageLevel(int) - Method in class org.apache.spark.storage.StorageStatus
-
Return the storage level, if any, used by the given RDD in this block manager.
- rddToAsyncRDDActions(RDD<T>, ClassTag<T>) - Static method in class org.apache.spark.rdd.RDD
-
- rddToDatasetHolder(RDD<T>, Encoder<T>) - Method in class org.apache.spark.sql.SQLImplicits
-
- rddToOrderedRDDFunctions(RDD<Tuple2<K, V>>, Ordering<K>, ClassTag<K>, ClassTag<V>) - Static method in class org.apache.spark.rdd.RDD
-
- rddToPairRDDFunctions(RDD<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>, Ordering<K>) - Static method in class org.apache.spark.rdd.RDD
-
- rddToSequenceFileRDDFunctions(RDD<Tuple2<K, V>>, ClassTag<K>, ClassTag<V>, <any>, <any>) - Static method in class org.apache.spark.rdd.RDD
-
- read() - Method in class org.apache.spark.io.LZ4BlockInputStream
-
- read(byte[], int, int) - Method in class org.apache.spark.io.LZ4BlockInputStream
-
- read(byte[]) - Method in class org.apache.spark.io.LZ4BlockInputStream
-
- read() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- read() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- read() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- read() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- read() - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- read() - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- read() - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- read() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- read() - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- read() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- read() - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- read() - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- read() - Static method in class org.apache.spark.ml.clustering.LDA
-
- read() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- read() - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- read() - Static method in class org.apache.spark.ml.feature.ColumnPruner
-
- read() - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- read() - Static method in class org.apache.spark.ml.feature.IDFModel
-
- read() - Static method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- read() - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- read() - Static method in class org.apache.spark.ml.feature.PCAModel
-
- read() - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- read() - Static method in class org.apache.spark.ml.feature.StandardScalerModel
-
- read() - Static method in class org.apache.spark.ml.feature.StringIndexerModel
-
- read() - Static method in class org.apache.spark.ml.feature.VectorAttributeRewriter
-
- read() - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- read() - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- read() - Static method in class org.apache.spark.ml.Pipeline
-
- read() - Static method in class org.apache.spark.ml.PipelineModel
-
- read() - Static method in class org.apache.spark.ml.recommendation.ALSModel
-
- read() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- read() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- read() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- read() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- read() - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- read() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- read() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- read() - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- read() - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- read() - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- read() - Static method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
-
- read() - Method in interface org.apache.spark.ml.util.DefaultParamsReadable
-
- read() - Method in interface org.apache.spark.ml.util.MLReadable
-
Returns an
MLReader instance for this class.
- read(Kryo, Input, Class<Iterable<?>>) - Method in class org.apache.spark.serializer.JavaIterableWrapperSerializer
-
- read() - Method in class org.apache.spark.sql.SparkSession
-
Returns a
DataFrameReader that can be used to read non-streaming data in as a
DataFrame.
- read() - Method in class org.apache.spark.sql.SQLContext
-
- read() - Method in class org.apache.spark.storage.BufferReleasingInputStream
-
- read(byte[]) - Method in class org.apache.spark.storage.BufferReleasingInputStream
-
- read(byte[], int, int) - Method in class org.apache.spark.storage.BufferReleasingInputStream
-
- read(String) - Static method in class org.apache.spark.streaming.CheckpointReader
-
Read checkpoint files present in the given checkpoint directory.
- read(String, SparkConf, Configuration, boolean) - Static method in class org.apache.spark.streaming.CheckpointReader
-
Read checkpoint files present in the given checkpoint directory.
- read(WriteAheadLogRecordHandle) - Method in class org.apache.spark.streaming.util.WriteAheadLog
-
Read a written record based on the given record handle.
- read() - Method in class org.apache.spark.util.io.ChunkedByteBufferInputStream
-
- read(byte[], int, int) - Method in class org.apache.spark.util.io.ChunkedByteBufferInputStream
-
- readAll() - Method in class org.apache.spark.streaming.util.WriteAheadLog
-
Read and return an iterator of all the records that have been written but not yet cleaned up.
- readArray(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
-
- readBoolean(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
-
- readBooleanArr(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
-
- readBytes(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
-
- readBytes() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetricDistributions
-
- readBytesArr(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
-
- readDate(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
-
- readDouble(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
-
- readDoubleArr(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
-
- readExternal(ObjectInput) - Method in class org.apache.spark.serializer.JavaSerializer
-
- readExternal(ObjectInput) - Method in class org.apache.spark.storage.BlockManagerId
-
- readExternal(ObjectInput) - Method in class org.apache.spark.storage.BlockManagerMessages.UpdateBlockInfo
-
- readExternal(ObjectInput) - Method in class org.apache.spark.storage.StorageLevel
-
- readExternal(ObjectInput) - Static method in class org.apache.spark.streaming.flume.EventTransformer
-
- readExternal(ObjectInput) - Method in class org.apache.spark.streaming.flume.SparkFlumeEvent
-
- readFrom(SparkConf) - Method in class org.apache.spark.internal.config.ConfigEntryWithDefault
-
- readFrom(SparkConf) - Method in class org.apache.spark.internal.config.FallbackConfigEntry
-
- readFrom(InputStream) - Static method in class org.apache.spark.util.sketch.BloomFilter
-
- readFrom(InputStream) - Static method in class org.apache.spark.util.sketch.CountMinSketch
-
- readInt(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
-
- readIntArr(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
-
- readKey(ClassTag<T>) - Method in class org.apache.spark.serializer.DeserializationStream
-
Reads the object representing the key of a key-value pair.
- readList(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
-
- readMap(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
-
- readObject(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
-
- readObject(ClassTag<T>) - Method in class org.apache.spark.serializer.DeserializationStream
-
The most general-purpose method to read an object.
- readObjectType(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
-
- readRecords() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetricDistributions
-
- readSchema(Seq<String>, Option<Configuration>) - Static method in class org.apache.spark.sql.hive.orc.OrcFileOperator
-
- readSqlObject(DataInputStream, char) - Static method in class org.apache.spark.sql.api.r.SQLUtils
-
- readStream() - Method in class org.apache.spark.sql.SparkSession
-
:: Experimental ::
Returns a DataStreamReader that can be used to read streaming data in as a DataFrame.
- readStream() - Method in class org.apache.spark.sql.SQLContext
-
- readString(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
-
- readStringArr(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
-
- readStringBytes(DataInputStream, int) - Static method in class org.apache.spark.api.r.SerDe
-
- readTime(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
-
- readTypedObject(DataInputStream, char) - Static method in class org.apache.spark.api.r.SerDe
-
- readValue(ClassTag<T>) - Method in class org.apache.spark.serializer.DeserializationStream
-
Reads the object representing the value of a key-value pair.
- ready(Duration, CanAwait) - Method in class org.apache.spark.ComplexFutureAction
-
- ready(Duration, CanAwait) - Method in interface org.apache.spark.FutureAction
-
Blocks until this action completes.
- ready(Duration, CanAwait) - Method in class org.apache.spark.SimpleFutureAction
-
- reason() - Method in class org.apache.spark.ExecutorLostFailure
-
- reason() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RemoveExecutor
-
- reason() - Method in class org.apache.spark.scheduler.SparkListenerExecutorRemoved
-
- reason() - Method in class org.apache.spark.scheduler.SparkListenerTaskEnd
-
- Recall - Class in org.apache.spark.mllib.evaluation.binary
-
Recall.
- Recall() - Constructor for class org.apache.spark.mllib.evaluation.binary.Recall
-
- recall(double) - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
-
Returns recall for a given label (category)
- recall() - Method in class org.apache.spark.mllib.evaluation.MulticlassMetrics
-
Deprecated.
Use accuracy. Since 2.0.0.
- recall() - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
-
Returns document-based recall averaged by the number of documents
- recall(double) - Method in class org.apache.spark.mllib.evaluation.MultilabelMetrics
-
Returns recall for a given label (category)
- recallByThreshold() - Method in class org.apache.spark.ml.classification.BinaryLogisticRegressionSummary
-
Returns a dataframe with two fields (threshold, recall) curve.
- recallByThreshold() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
-
Returns the (threshold, recall) curve.
- Receiver<T> - Class in org.apache.spark.streaming.receiver
-
:: DeveloperApi ::
Abstract class of a receiver that can be run on worker nodes to receive external data.
- Receiver(StorageLevel) - Constructor for class org.apache.spark.streaming.receiver.Receiver
-
- RECEIVER_WAL_CLASS_CONF_KEY() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
-
- RECEIVER_WAL_CLOSE_AFTER_WRITE_CONF_KEY() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
-
- RECEIVER_WAL_ENABLE_CONF_KEY() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
-
- RECEIVER_WAL_MAX_FAILURES_CONF_KEY() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
-
- RECEIVER_WAL_ROLLING_INTERVAL_CONF_KEY() - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
-
- ReceiverInfo - Class in org.apache.spark.streaming.scheduler
-
:: DeveloperApi ::
Class having information about a receiver
- ReceiverInfo(int, String, boolean, String, String, String, String, long) - Constructor for class org.apache.spark.streaming.scheduler.ReceiverInfo
-
- receiverInfo() - Method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverError
-
- receiverInfo() - Method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStarted
-
- receiverInfo() - Method in class org.apache.spark.streaming.scheduler.StreamingListenerReceiverStopped
-
- receiverInputDStream() - Method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- receiverInputDStream() - Method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- ReceiverInputDStream<T> - Class in org.apache.spark.streaming.dstream
-
Abstract class for defining any
InputDStream
that has to start a receiver on worker nodes to receive external data.
- ReceiverInputDStream(StreamingContext, ClassTag<T>) - Constructor for class org.apache.spark.streaming.dstream.ReceiverInputDStream
-
- ReceiverState - Class in org.apache.spark.streaming.scheduler
-
Enumeration to identify current state of a Receiver
- ReceiverState() - Constructor for class org.apache.spark.streaming.scheduler.ReceiverState
-
- receiverStream(Receiver<T>) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Create an input stream with any arbitrary user implemented receiver.
- receiverStream(Receiver<T>, ClassTag<T>) - Method in class org.apache.spark.streaming.StreamingContext
-
Create an input stream with any arbitrary user implemented receiver.
- recommendProducts(int, int) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
-
Recommends products to a user.
- recommendProductsForUsers(int) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
-
Recommends top products for all users.
- recommendUsers(int, int) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
-
Recommends users to a product.
- recommendUsersForProducts(int) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
-
Recommends top users for all products.
- recordReader(InputStream, Configuration) - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- recordReaderClass() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- RECORDS_BETWEEN_BYTES_READ_METRIC_UPDATES() - Static method in class org.apache.spark.rdd.HadoopRDD
-
Update the input bytes read metric each time this number of records has been read
- RECORDS_BETWEEN_BYTES_WRITTEN_METRIC_UPDATES() - Static method in class org.apache.spark.rdd.PairRDDFunctions
-
- RECORDS_READ() - Method in class org.apache.spark.InternalAccumulator.input$
-
- RECORDS_READ() - Method in class org.apache.spark.InternalAccumulator.shuffleRead$
-
- RECORDS_WRITTEN() - Method in class org.apache.spark.InternalAccumulator.output$
-
- RECORDS_WRITTEN() - Method in class org.apache.spark.InternalAccumulator.shuffleWrite$
-
- recordsRead() - Method in class org.apache.spark.status.api.v1.InputMetricDistributions
-
- recordsRead() - Method in class org.apache.spark.status.api.v1.InputMetrics
-
- recordsRead() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetrics
-
- recordsRead() - Method in class org.apache.spark.ui.jobs.UIData.InputMetricsUIData
-
- recordsRead() - Method in class org.apache.spark.ui.jobs.UIData.ShuffleReadMetricsUIData
-
- recordsWritten() - Method in class org.apache.spark.status.api.v1.OutputMetricDistributions
-
- recordsWritten() - Method in class org.apache.spark.status.api.v1.OutputMetrics
-
- recordsWritten() - Method in class org.apache.spark.status.api.v1.ShuffleWriteMetrics
-
- recordsWritten() - Method in class org.apache.spark.ui.jobs.UIData.OutputMetricsUIData
-
- recordsWritten() - Method in class org.apache.spark.ui.jobs.UIData.ShuffleWriteMetricsUIData
-
- recordWriter(OutputStream, Configuration) - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- recordWriterClass() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- reduce(Function2<T, T, T>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- reduce(Function2<T, T, T>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- reduce(Function2<T, T, T>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- reduce(Function2<T, T, T>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Reduces the elements of this RDD using the specified commutative and associative binary
operator.
- reduce(Function2<T, T, T>) - Static method in class org.apache.spark.api.r.RRDD
-
- reduce(Function2<T, T, T>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- reduce(Function2<T, T, T>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- reduce(Function2<T, T, T>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- reduce(Function2<T, T, T>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- reduce(Function2<T, T, T>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- reduce(Function2<T, T, T>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- reduce(Function2<T, T, T>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- reduce(Function2<T, T, T>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- reduce(Function2<T, T, T>) - Method in class org.apache.spark.rdd.RDD
-
Reduces the elements of this RDD using the specified commutative and
associative binary operator.
- reduce(Function2<T, T, T>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- reduce(Function2<T, T, T>) - Method in class org.apache.spark.sql.Dataset
-
:: Experimental ::
(Scala-specific)
Reduces the elements of this Dataset using the specified binary function.
- reduce(ReduceFunction<T>) - Method in class org.apache.spark.sql.Dataset
-
:: Experimental ::
(Java-specific)
Reduces the elements of this Dataset using the specified binary function.
- reduce(BUF, IN) - Method in class org.apache.spark.sql.expressions.Aggregator
-
Combine two values to produce a new value.
- reduce(Function2<A1, A1, A1>) - Static method in class org.apache.spark.sql.types.StructType
-
- reduce(Function2<T, T, T>) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- reduce(Function2<T, T, T>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD has a single element generated by reducing each RDD
of this DStream.
- reduce(Function2<T, T, T>) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- reduce(Function2<T, T, T>) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- reduce(Function2<T, T, T>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- reduce(Function2<T, T, T>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- reduce(Function2<T, T, T>) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- reduce(Function2<T, T, T>) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream in which each RDD has a single element generated by reducing each RDD
of this DStream.
- reduceByKey(Partitioner, Function2<V, V, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Merge the values for each key using an associative and commutative reduce function.
- reduceByKey(Function2<V, V, V>, int) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Merge the values for each key using an associative and commutative reduce function.
- reduceByKey(Function2<V, V, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Merge the values for each key using an associative and commutative reduce function.
- reduceByKey(Partitioner, Function2<V, V, V>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Merge the values for each key using an associative and commutative reduce function.
- reduceByKey(Function2<V, V, V>, int) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Merge the values for each key using an associative and commutative reduce function.
- reduceByKey(Function2<V, V, V>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Merge the values for each key using an associative and commutative reduce function.
- reduceByKey(Function2<V, V, V>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying reduceByKey to each RDD.
- reduceByKey(Function2<V, V, V>, int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying reduceByKey to each RDD.
- reduceByKey(Function2<V, V, V>, Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying reduceByKey to each RDD.
- reduceByKey(Function2<V, V, V>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- reduceByKey(Function2<V, V, V>, int) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- reduceByKey(Function2<V, V, V>, Partitioner) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- reduceByKey(Function2<V, V, V>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- reduceByKey(Function2<V, V, V>, int) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- reduceByKey(Function2<V, V, V>, Partitioner) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- reduceByKey(Function2<V, V, V>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying reduceByKey to each RDD.
- reduceByKey(Function2<V, V, V>, int) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying reduceByKey to each RDD.
- reduceByKey(Function2<V, V, V>, Partitioner) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying reduceByKey to each RDD.
- reduceByKeyAndWindow(Function2<V, V, V>, Duration) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Create a new DStream by applying reduceByKey over a sliding window on this DStream.
- reduceByKeyAndWindow(Function2<V, V, V>, Duration, Duration) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying reduceByKey over a sliding window.
- reduceByKeyAndWindow(Function2<V, V, V>, Duration, Duration, int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying reduceByKey over a sliding window.
- reduceByKeyAndWindow(Function2<V, V, V>, Duration, Duration, Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying reduceByKey over a sliding window.
- reduceByKeyAndWindow(Function2<V, V, V>, Function2<V, V, V>, Duration, Duration) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by reducing over a using incremental computation.
- reduceByKeyAndWindow(Function2<V, V, V>, Function2<V, V, V>, Duration, Duration, int, Function<Tuple2<K, V>, Boolean>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying incremental reduceByKey over a sliding window.
- reduceByKeyAndWindow(Function2<V, V, V>, Function2<V, V, V>, Duration, Duration, Partitioner, Function<Tuple2<K, V>, Boolean>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying incremental reduceByKey over a sliding window.
- reduceByKeyAndWindow(Function2<V, V, V>, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- reduceByKeyAndWindow(Function2<V, V, V>, Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- reduceByKeyAndWindow(Function2<V, V, V>, Duration, Duration, int) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- reduceByKeyAndWindow(Function2<V, V, V>, Duration, Duration, Partitioner) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- reduceByKeyAndWindow(Function2<V, V, V>, Function2<V, V, V>, Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- reduceByKeyAndWindow(Function2<V, V, V>, Function2<V, V, V>, Duration, Duration, int, Function<Tuple2<K, V>, Boolean>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- reduceByKeyAndWindow(Function2<V, V, V>, Function2<V, V, V>, Duration, Duration, Partitioner, Function<Tuple2<K, V>, Boolean>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- reduceByKeyAndWindow(Function2<V, V, V>, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- reduceByKeyAndWindow(Function2<V, V, V>, Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- reduceByKeyAndWindow(Function2<V, V, V>, Duration, Duration, int) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- reduceByKeyAndWindow(Function2<V, V, V>, Duration, Duration, Partitioner) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- reduceByKeyAndWindow(Function2<V, V, V>, Function2<V, V, V>, Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- reduceByKeyAndWindow(Function2<V, V, V>, Function2<V, V, V>, Duration, Duration, int, Function<Tuple2<K, V>, Boolean>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- reduceByKeyAndWindow(Function2<V, V, V>, Function2<V, V, V>, Duration, Duration, Partitioner, Function<Tuple2<K, V>, Boolean>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- reduceByKeyAndWindow(Function2<V, V, V>, Duration) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying reduceByKey over a sliding window on this DStream.
- reduceByKeyAndWindow(Function2<V, V, V>, Duration, Duration) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying reduceByKey over a sliding window.
- reduceByKeyAndWindow(Function2<V, V, V>, Duration, Duration, int) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying reduceByKey over a sliding window.
- reduceByKeyAndWindow(Function2<V, V, V>, Duration, Duration, Partitioner) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying reduceByKey over a sliding window.
- reduceByKeyAndWindow(Function2<V, V, V>, Function2<V, V, V>, Duration, Duration, int, Function1<Tuple2<K, V>, Object>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying incremental reduceByKey over a sliding window.
- reduceByKeyAndWindow(Function2<V, V, V>, Function2<V, V, V>, Duration, Duration, Partitioner, Function1<Tuple2<K, V>, Object>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying incremental reduceByKey over a sliding window.
- reduceByKeyLocally(Function2<V, V, V>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Merge the values for each key using an associative and commutative reduce function, but return
the result immediately to the master as a Map.
- reduceByKeyLocally(Function2<V, V, V>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Merge the values for each key using an associative and commutative reduce function, but return
the results immediately to the master as a Map.
- reduceByWindow(Function2<T, T, T>, Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- reduceByWindow(Function2<T, T, T>, Function2<T, T, T>, Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- reduceByWindow(Function2<T, T, T>, Duration, Duration) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD has a single element generated by reducing all
elements in a sliding window over this DStream.
- reduceByWindow(Function2<T, T, T>, Function2<T, T, T>, Duration, Duration) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return a new DStream in which each RDD has a single element generated by reducing all
elements in a sliding window over this DStream.
- reduceByWindow(Function2<T, T, T>, Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- reduceByWindow(Function2<T, T, T>, Function2<T, T, T>, Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- reduceByWindow(Function2<T, T, T>, Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- reduceByWindow(Function2<T, T, T>, Function2<T, T, T>, Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- reduceByWindow(Function2<T, T, T>, Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- reduceByWindow(Function2<T, T, T>, Function2<T, T, T>, Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- reduceByWindow(Function2<T, T, T>, Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- reduceByWindow(Function2<T, T, T>, Function2<T, T, T>, Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- reduceByWindow(Function2<T, T, T>, Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- reduceByWindow(Function2<T, T, T>, Function2<T, T, T>, Duration, Duration) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- reduceByWindow(Function2<T, T, T>, Duration, Duration) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream in which each RDD has a single element generated by reducing all
elements in a sliding window over this DStream.
- reduceByWindow(Function2<T, T, T>, Function2<T, T, T>, Duration, Duration) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream in which each RDD has a single element generated by reducing all
elements in a sliding window over this DStream.
- ReduceFunction<T> - Interface in org.apache.spark.api.java.function
-
Base interface for function used in Dataset's reduce.
- reduceGroups(Function2<V, V, V>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
-
Reduces the elements of each group of data using the specified binary function.
- reduceGroups(ReduceFunction<V>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
-
Reduces the elements of each group of data using the specified binary function.
- reduceId() - Method in class org.apache.spark.FetchFailed
-
- reduceId() - Method in class org.apache.spark.storage.ShuffleBlockId
-
- reduceId() - Method in class org.apache.spark.storage.ShuffleDataBlockId
-
- reduceId() - Method in class org.apache.spark.storage.ShuffleIndexBlockId
-
- reduceLeft(Function2<B, A, B>) - Static method in class org.apache.spark.sql.types.StructType
-
- reduceLeftOption(Function2<B, A, B>) - Static method in class org.apache.spark.sql.types.StructType
-
- reduceOption(Function2<A1, A1, A1>) - Static method in class org.apache.spark.sql.types.StructType
-
- reduceRight(Function2<A, B, B>) - Static method in class org.apache.spark.sql.types.StructType
-
- reduceRightOption(Function2<A, B, B>) - Static method in class org.apache.spark.sql.types.StructType
-
- references() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- references() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- references() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- refresh() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- refreshByPath(String) - Method in class org.apache.spark.sql.catalog.Catalog
-
Invalidate and refresh all the cached data (and the associated metadata) for any dataframe that
contains the given data source path.
- refreshByPath(String) - Method in class org.apache.spark.sql.internal.CatalogImpl
-
Refresh the cache entry and the associated metadata for all dataframes (if any), that contain
the given data source path.
- refreshTable(String) - Method in class org.apache.spark.sql.catalog.Catalog
-
Invalidate and refresh all the cached metadata of the given table.
- refreshTable(String) - Method in class org.apache.spark.sql.hive.HiveContext
-
Deprecated.
Invalidate and refresh all the cached the metadata of the given table.
- refreshTable(String) - Method in class org.apache.spark.sql.internal.CatalogImpl
-
Refresh the cache entry for a table, if any.
- regex(Regex) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- regexp_extract(Column, String, int) - Static method in class org.apache.spark.sql.functions
-
Extract a specific group matched by a Java regex, from the specified string column.
- regexp_replace(Column, String, String) - Static method in class org.apache.spark.sql.functions
-
Replace all substrings of the specified string value that match regexp with rep.
- RegexTokenizer - Class in org.apache.spark.ml.feature
-
A regex based tokenizer that extracts tokens either by using the provided regex pattern to split
the text (default) or repeatedly matching the regex (if gaps is false).
- RegexTokenizer(String) - Constructor for class org.apache.spark.ml.feature.RegexTokenizer
-
- RegexTokenizer() - Constructor for class org.apache.spark.ml.feature.RegexTokenizer
-
- register(AccumulatorV2<?, ?>) - Method in class org.apache.spark.SparkContext
-
Register the given accumulator.
- register(AccumulatorV2<?, ?>, String) - Method in class org.apache.spark.SparkContext
-
Register the given accumulator with given name.
- register(String, String) - Static method in class org.apache.spark.sql.types.UDTRegistration
-
Registers an UserDefinedType to an user class.
- register(String, UserDefinedAggregateFunction) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a user-defined aggregate function (UDAF).
- register(String, Function0<RT>, TypeTags.TypeTag<RT>) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a Scala closure of 0 arguments as user-defined function (UDF).
- register(String, Function1<A1, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a Scala closure of 1 arguments as user-defined function (UDF).
- register(String, Function2<A1, A2, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a Scala closure of 2 arguments as user-defined function (UDF).
- register(String, Function3<A1, A2, A3, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a Scala closure of 3 arguments as user-defined function (UDF).
- register(String, Function4<A1, A2, A3, A4, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a Scala closure of 4 arguments as user-defined function (UDF).
- register(String, Function5<A1, A2, A3, A4, A5, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a Scala closure of 5 arguments as user-defined function (UDF).
- register(String, Function6<A1, A2, A3, A4, A5, A6, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a Scala closure of 6 arguments as user-defined function (UDF).
- register(String, Function7<A1, A2, A3, A4, A5, A6, A7, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a Scala closure of 7 arguments as user-defined function (UDF).
- register(String, Function8<A1, A2, A3, A4, A5, A6, A7, A8, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a Scala closure of 8 arguments as user-defined function (UDF).
- register(String, Function9<A1, A2, A3, A4, A5, A6, A7, A8, A9, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a Scala closure of 9 arguments as user-defined function (UDF).
- register(String, Function10<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a Scala closure of 10 arguments as user-defined function (UDF).
- register(String, Function11<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>, TypeTags.TypeTag<A11>) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a Scala closure of 11 arguments as user-defined function (UDF).
- register(String, Function12<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>, TypeTags.TypeTag<A11>, TypeTags.TypeTag<A12>) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a Scala closure of 12 arguments as user-defined function (UDF).
- register(String, Function13<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>, TypeTags.TypeTag<A11>, TypeTags.TypeTag<A12>, TypeTags.TypeTag<A13>) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a Scala closure of 13 arguments as user-defined function (UDF).
- register(String, Function14<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>, TypeTags.TypeTag<A11>, TypeTags.TypeTag<A12>, TypeTags.TypeTag<A13>, TypeTags.TypeTag<A14>) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a Scala closure of 14 arguments as user-defined function (UDF).
- register(String, Function15<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>, TypeTags.TypeTag<A11>, TypeTags.TypeTag<A12>, TypeTags.TypeTag<A13>, TypeTags.TypeTag<A14>, TypeTags.TypeTag<A15>) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a Scala closure of 15 arguments as user-defined function (UDF).
- register(String, Function16<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>, TypeTags.TypeTag<A11>, TypeTags.TypeTag<A12>, TypeTags.TypeTag<A13>, TypeTags.TypeTag<A14>, TypeTags.TypeTag<A15>, TypeTags.TypeTag<A16>) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a Scala closure of 16 arguments as user-defined function (UDF).
- register(String, Function17<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>, TypeTags.TypeTag<A11>, TypeTags.TypeTag<A12>, TypeTags.TypeTag<A13>, TypeTags.TypeTag<A14>, TypeTags.TypeTag<A15>, TypeTags.TypeTag<A16>, TypeTags.TypeTag<A17>) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a Scala closure of 17 arguments as user-defined function (UDF).
- register(String, Function18<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, A18, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>, TypeTags.TypeTag<A11>, TypeTags.TypeTag<A12>, TypeTags.TypeTag<A13>, TypeTags.TypeTag<A14>, TypeTags.TypeTag<A15>, TypeTags.TypeTag<A16>, TypeTags.TypeTag<A17>, TypeTags.TypeTag<A18>) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a Scala closure of 18 arguments as user-defined function (UDF).
- register(String, Function19<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, A18, A19, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>, TypeTags.TypeTag<A11>, TypeTags.TypeTag<A12>, TypeTags.TypeTag<A13>, TypeTags.TypeTag<A14>, TypeTags.TypeTag<A15>, TypeTags.TypeTag<A16>, TypeTags.TypeTag<A17>, TypeTags.TypeTag<A18>, TypeTags.TypeTag<A19>) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a Scala closure of 19 arguments as user-defined function (UDF).
- register(String, Function20<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, A18, A19, A20, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>, TypeTags.TypeTag<A11>, TypeTags.TypeTag<A12>, TypeTags.TypeTag<A13>, TypeTags.TypeTag<A14>, TypeTags.TypeTag<A15>, TypeTags.TypeTag<A16>, TypeTags.TypeTag<A17>, TypeTags.TypeTag<A18>, TypeTags.TypeTag<A19>, TypeTags.TypeTag<A20>) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a Scala closure of 20 arguments as user-defined function (UDF).
- register(String, Function21<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, A18, A19, A20, A21, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>, TypeTags.TypeTag<A11>, TypeTags.TypeTag<A12>, TypeTags.TypeTag<A13>, TypeTags.TypeTag<A14>, TypeTags.TypeTag<A15>, TypeTags.TypeTag<A16>, TypeTags.TypeTag<A17>, TypeTags.TypeTag<A18>, TypeTags.TypeTag<A19>, TypeTags.TypeTag<A20>, TypeTags.TypeTag<A21>) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a Scala closure of 21 arguments as user-defined function (UDF).
- register(String, Function22<A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, A11, A12, A13, A14, A15, A16, A17, A18, A19, A20, A21, A22, RT>, TypeTags.TypeTag<RT>, TypeTags.TypeTag<A1>, TypeTags.TypeTag<A2>, TypeTags.TypeTag<A3>, TypeTags.TypeTag<A4>, TypeTags.TypeTag<A5>, TypeTags.TypeTag<A6>, TypeTags.TypeTag<A7>, TypeTags.TypeTag<A8>, TypeTags.TypeTag<A9>, TypeTags.TypeTag<A10>, TypeTags.TypeTag<A11>, TypeTags.TypeTag<A12>, TypeTags.TypeTag<A13>, TypeTags.TypeTag<A14>, TypeTags.TypeTag<A15>, TypeTags.TypeTag<A16>, TypeTags.TypeTag<A17>, TypeTags.TypeTag<A18>, TypeTags.TypeTag<A19>, TypeTags.TypeTag<A20>, TypeTags.TypeTag<A21>, TypeTags.TypeTag<A22>) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a Scala closure of 22 arguments as user-defined function (UDF).
- register(String, UDF1<?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a user-defined function with 1 arguments.
- register(String, UDF2<?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a user-defined function with 2 arguments.
- register(String, UDF3<?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a user-defined function with 3 arguments.
- register(String, UDF4<?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a user-defined function with 4 arguments.
- register(String, UDF5<?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a user-defined function with 5 arguments.
- register(String, UDF6<?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a user-defined function with 6 arguments.
- register(String, UDF7<?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a user-defined function with 7 arguments.
- register(String, UDF8<?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a user-defined function with 8 arguments.
- register(String, UDF9<?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a user-defined function with 9 arguments.
- register(String, UDF10<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a user-defined function with 10 arguments.
- register(String, UDF11<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a user-defined function with 11 arguments.
- register(String, UDF12<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a user-defined function with 12 arguments.
- register(String, UDF13<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a user-defined function with 13 arguments.
- register(String, UDF14<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a user-defined function with 14 arguments.
- register(String, UDF15<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a user-defined function with 15 arguments.
- register(String, UDF16<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a user-defined function with 16 arguments.
- register(String, UDF17<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a user-defined function with 17 arguments.
- register(String, UDF18<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a user-defined function with 18 arguments.
- register(String, UDF19<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a user-defined function with 19 arguments.
- register(String, UDF20<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a user-defined function with 20 arguments.
- register(String, UDF21<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a user-defined function with 21 arguments.
- register(String, UDF22<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a user-defined function with 22 arguments.
- register(QueryExecutionListener) - Method in class org.apache.spark.sql.util.ExecutionListenerManager
-
- register(AccumulatorV2<?, ?>) - Static method in class org.apache.spark.util.AccumulatorContext
-
Registers an
AccumulatorV2 created on the driver such that it can be used on the executors.
- register(String, Function0<Object>) - Static method in class org.apache.spark.util.SignalUtils
-
Adds an action to be run when a given signal is received by this process.
- registerAvroSchemas(Seq<Schema>) - Method in class org.apache.spark.SparkConf
-
Use Kryo serialization and register the given set of Avro schemas so that the generic
record serializer can decrease network IO
- registerClasses(Kryo) - Method in interface org.apache.spark.serializer.KryoRegistrator
-
- registerDialect(JdbcDialect) - Static method in class org.apache.spark.sql.jdbc.JdbcDialects
-
Register a dialect for use on all new matching jdbc org.apache.spark.sql.DataFrame.
- registerKryoClasses(SparkConf) - Static method in class org.apache.spark.graphx.GraphXUtils
-
Registers classes that GraphX uses with Kryo.
- registerKryoClasses(Class<?>[]) - Method in class org.apache.spark.SparkConf
-
Use Kryo serialization and register the given set of classes with Kryo.
- registerLogger(Logger) - Static method in class org.apache.spark.util.SignalUtils
-
Register a signal handler to log signals on UNIX-like systems.
- registerShutdownDeleteDir(File) - Static method in class org.apache.spark.util.ShutdownHookManager
-
- registerSqlSerDe(Tuple2<Function2<DataInputStream, Object, Object>, Function2<DataOutputStream, Object, Object>>) - Static method in class org.apache.spark.api.r.SerDe
-
- registerStream(DStream<BinarySample>) - Method in class org.apache.spark.mllib.stat.test.StreamingTest
-
Register a DStream of values for significance testing.
- registerStream(JavaDStream<BinarySample>) - Method in class org.apache.spark.mllib.stat.test.StreamingTest
-
Register a JavaDStream of values for significance testing.
- registerTempTable(String) - Method in class org.apache.spark.sql.Dataset
-
Deprecated.
Use createOrReplaceTempView(viewName) instead. Since 2.0.0.
- regParam() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- regParam() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- regParam() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- regParam() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- regParam() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- regParam() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- regParam() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- Regression() - Static method in class org.apache.spark.mllib.tree.configuration.Algo
-
- RegressionEvaluator - Class in org.apache.spark.ml.evaluation
-
:: Experimental ::
Evaluator for regression, which expects two input columns: prediction and label.
- RegressionEvaluator(String) - Constructor for class org.apache.spark.ml.evaluation.RegressionEvaluator
-
- RegressionEvaluator() - Constructor for class org.apache.spark.ml.evaluation.RegressionEvaluator
-
- RegressionMetrics - Class in org.apache.spark.mllib.evaluation
-
Evaluator for regression.
- RegressionMetrics(RDD<Tuple2<Object, Object>>, boolean) - Constructor for class org.apache.spark.mllib.evaluation.RegressionMetrics
-
- RegressionMetrics(RDD<Tuple2<Object, Object>>) - Constructor for class org.apache.spark.mllib.evaluation.RegressionMetrics
-
- RegressionModel<FeaturesType,M extends RegressionModel<FeaturesType,M>> - Class in org.apache.spark.ml.regression
-
:: DeveloperApi ::
- RegressionModel() - Constructor for class org.apache.spark.ml.regression.RegressionModel
-
- RegressionModel - Interface in org.apache.spark.mllib.regression
-
- reindex() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- reindex() - Method in class org.apache.spark.graphx.VertexRDD
-
Construct a new VertexRDD that is indexed by only the visible vertices.
- RelationalGroupedDataset - Class in org.apache.spark.sql
-
A set of methods for aggregations on a DataFrame, created by Dataset.groupBy.
- RelationalGroupedDataset.CubeType$ - Class in org.apache.spark.sql
-
To indicate it's the CUBE
- RelationalGroupedDataset.CubeType$() - Constructor for class org.apache.spark.sql.RelationalGroupedDataset.CubeType$
-
- RelationalGroupedDataset.GroupByType$ - Class in org.apache.spark.sql
-
To indicate it's the GroupBy
- RelationalGroupedDataset.GroupByType$() - Constructor for class org.apache.spark.sql.RelationalGroupedDataset.GroupByType$
-
- RelationalGroupedDataset.PivotType$ - Class in org.apache.spark.sql
-
- RelationalGroupedDataset.PivotType$() - Constructor for class org.apache.spark.sql.RelationalGroupedDataset.PivotType$
-
- RelationalGroupedDataset.RollupType$ - Class in org.apache.spark.sql
-
To indicate it's the ROLLUP
- RelationalGroupedDataset.RollupType$() - Constructor for class org.apache.spark.sql.RelationalGroupedDataset.RollupType$
-
- RelationProvider - Interface in org.apache.spark.sql.sources
-
::DeveloperApi::
Implemented by objects that produce relations for a specific kind of data source.
- relativeDirection(long) - Method in class org.apache.spark.graphx.Edge
-
Return the relative direction of the edge to the corresponding
vertex.
- relativeError() - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- relativeError() - Method in class org.apache.spark.util.sketch.CountMinSketch
-
- rem(Decimal, Decimal) - Method in class org.apache.spark.sql.types.Decimal.DecimalAsIfIntegral$
-
- remainder(Decimal) - Method in class org.apache.spark.sql.types.Decimal
-
- remember(Duration) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Sets each DStreams in this context to remember RDDs it generated in the last given duration.
- remember(Duration) - Method in class org.apache.spark.streaming.StreamingContext
-
Set each DStream in this context to remember RDDs it generated in the last given duration.
- REMOTE_BLOCKS_FETCHED() - Method in class org.apache.spark.InternalAccumulator.shuffleRead$
-
- REMOTE_BYTES_READ() - Method in class org.apache.spark.InternalAccumulator.shuffleRead$
-
- remoteBlocksFetched() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetricDistributions
-
- remoteBlocksFetched() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetrics
-
- remoteBlocksFetched() - Method in class org.apache.spark.ui.jobs.UIData.ShuffleReadMetricsUIData
-
- remoteBytesRead() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetricDistributions
-
- remoteBytesRead() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetrics
-
- remoteBytesRead() - Method in class org.apache.spark.ui.jobs.UIData.ShuffleReadMetricsUIData
-
- remove(String) - Static method in class org.apache.spark.api.r.JVMObjectTracker
-
- remove(Param<T>) - Method in class org.apache.spark.ml.param.ParamMap
-
Removes a key from this map and returns its value associated previously as an option.
- remove(String) - Method in class org.apache.spark.SparkConf
-
Remove a parameter from the configuration
- remove(String) - Method in class org.apache.spark.sql.types.MetadataBuilder
-
- remove() - Method in class org.apache.spark.streaming.State
-
Remove the state if it exists.
- remove(long) - Static method in class org.apache.spark.util.AccumulatorContext
-
- removeFromDriver() - Method in class org.apache.spark.storage.BlockManagerMessages.RemoveBroadcast
-
- removeListener(StreamingQueryListener) - Method in class org.apache.spark.sql.streaming.StreamingQueryManager
-
- removeSelfEdges() - Method in class org.apache.spark.graphx.GraphOps
-
Remove self edges.
- removeShutdownDeleteDir(File) - Static method in class org.apache.spark.util.ShutdownHookManager
-
- removeShutdownHook(Object) - Static method in class org.apache.spark.util.ShutdownHookManager
-
Remove a previously installed shutdown hook.
- rep(Function0<Parsers.Parser<T>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- rep1(Function0<Parsers.Parser<T>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- rep1(Function0<Parsers.Parser<T>>, Function0<Parsers.Parser<T>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- rep1sep(Function0<Parsers.Parser<T>>, Function0<Parsers.Parser<Object>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- repartition(int) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Return a new RDD that has exactly numPartitions partitions.
- repartition(int) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return a new RDD that has exactly numPartitions partitions.
- repartition(int) - Method in class org.apache.spark.api.java.JavaRDD
-
Return a new RDD that has exactly numPartitions partitions.
- repartition(int, Ordering<T>) - Static method in class org.apache.spark.api.r.RRDD
-
- repartition(int, Ordering<T>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- repartition(int, Ordering<T>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- repartition(int, Ordering<T>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- repartition(int, Ordering<T>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- repartition(int, Ordering<T>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- repartition(int, Ordering<T>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- repartition(int, Ordering<T>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- repartition(int, Ordering<T>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- repartition(int, Ordering<T>) - Method in class org.apache.spark.rdd.RDD
-
Return a new RDD that has exactly numPartitions partitions.
- repartition(int, Ordering<T>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- repartition(int, Column...) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset partitioned by the given partitioning expressions into
numPartitions.
- repartition(Column...) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset partitioned by the given partitioning expressions, using
spark.sql.shuffle.partitions as number of partitions.
- repartition(int) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset that has exactly numPartitions partitions.
- repartition(int, Seq<Column>) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset partitioned by the given partitioning expressions into
numPartitions.
- repartition(Seq<Column>) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset partitioned by the given partitioning expressions, using
spark.sql.shuffle.partitions as number of partitions.
- repartition(int) - Method in class org.apache.spark.streaming.api.java.JavaDStream
-
Return a new DStream with an increased or decreased level of parallelism.
- repartition(int) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- repartition(int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream with an increased or decreased level of parallelism.
- repartition(int) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- repartition(int) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- repartition(int) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- repartition(int) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return a new DStream with an increased or decreased level of parallelism.
- repartition$default$2(int) - Static method in class org.apache.spark.api.r.RRDD
-
- repartition$default$2(int) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- repartition$default$2(int) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- repartition$default$2(int) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- repartition$default$2(int) - Static method in class org.apache.spark.graphx.VertexRDD
-
- repartition$default$2(int) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- repartition$default$2(int) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- repartition$default$2(int) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- repartition$default$2(int) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- repartition$default$2(int) - Static method in class org.apache.spark.rdd.UnionRDD
-
- repartitionAndSortWithinPartitions(Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Repartition the RDD according to the given partitioner and, within each resulting partition,
sort records by their keys.
- repartitionAndSortWithinPartitions(Partitioner, Comparator<K>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Repartition the RDD according to the given partitioner and, within each resulting partition,
sort records by their keys.
- repartitionAndSortWithinPartitions(Partitioner) - Method in class org.apache.spark.rdd.OrderedRDDFunctions
-
Repartition the RDD according to the given partitioner and, within each resulting partition,
sort records by their keys.
- repeat(Column, int) - Static method in class org.apache.spark.sql.functions
-
Repeats a string column n times, and returns it as a new string column.
- replace(String, Map<T, T>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
Replaces values matching keys in replacement map with the corresponding values.
- replace(String[], Map<T, T>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
Replaces values matching keys in replacement map with the corresponding values.
- replace(String, Map<T, T>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
(Scala-specific) Replaces values matching keys in replacement map.
- replace(Seq<String>, Map<T, T>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
(Scala-specific) Replaces values matching keys in replacement map.
- replicatedVertexView() - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- replication() - Method in class org.apache.spark.storage.StorageLevel
-
- repN(int, Function0<Parsers.Parser<T>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- reportError(String, Throwable) - Method in class org.apache.spark.streaming.receiver.Receiver
-
Report exceptions in receiving data.
- repr() - Static method in class org.apache.spark.sql.types.StructType
-
- repsep(Function0<Parsers.Parser<T>>, Function0<Parsers.Parser<Object>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- requestedTotal() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RequestExecutors
-
- requestExecutors(int) - Method in class org.apache.spark.SparkContext
-
:: DeveloperApi ::
Request an additional number of executors from the cluster manager.
- requestTotalExecutors(int, int, Map<String, Object>) - Method in class org.apache.spark.SparkContext
-
Update the cluster manager on our scheduling needs.
- requiredChildDistribution() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- requiredChildDistribution() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- requiredChildOrdering() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- requiredChildOrdering() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- res() - Method in class org.apache.spark.mllib.optimization.NNLS.Workspace
-
- reservoirSampleAndCount(Iterator<T>, int, long, ClassTag<T>) - Static method in class org.apache.spark.util.random.SamplingUtils
-
Reservoir sampling implementation that also returns the input size.
- reset() - Method in class org.apache.spark.io.LZ4BlockInputStream
-
- reset() - Method in class org.apache.spark.storage.BufferReleasingInputStream
-
- reset() - Method in class org.apache.spark.util.AccumulatorV2
-
Resets this accumulator, which is zero value.
- reset() - Method in class org.apache.spark.util.CollectionAccumulator
-
- reset() - Method in class org.apache.spark.util.DoubleAccumulator
-
- reset() - Method in class org.apache.spark.util.LegacyAccumulatorWrapper
-
- reset() - Method in class org.apache.spark.util.LongAccumulator
-
- resetMetrics() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- resetMetrics() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- resetTerminated() - Method in class org.apache.spark.sql.streaming.StreamingQueryManager
-
Forget about past terminated queries so that awaitAnyTermination() can be used again to
wait for new terminations.
- residualDegreeOfFreedom() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
-
The residual degrees of freedom.
- residualDegreeOfFreedomNull() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
-
The residual degrees of freedom for the null model.
- residuals() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
-
Get the default residuals (deviance residuals) of the fitted model.
- residuals(String) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
-
Get the residuals of the fitted model by type.
- residuals() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
-
Residuals (label - predicted value)
- resolve(StructType, Function2<String, String, Object>) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- resolve(Seq<String>, Function2<String, String, Object>) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- resolveChildren(Seq<String>, Function2<String, String, Object>) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- resolved() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- resolveExpressions(PartialFunction<Expression, Expression>) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- resolveOperators(PartialFunction<LogicalPlan, LogicalPlan>) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- resolveQuoted(String, Function2<String, String, Object>) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- resolveURI(String) - Static method in class org.apache.spark.util.Utils
-
Return a well-formed URI for the file described by a user input string.
- resolveURIs(String) - Static method in class org.apache.spark.util.Utils
-
Resolve a comma-separated list of paths.
- responder() - Method in class org.apache.spark.ui.JettyUtils.ServletParams
-
- responseFromBackup(String) - Static method in class org.apache.spark.util.Utils
-
Return true if the response message is sent from a backup Master on standby.
- restart(String) - Method in class org.apache.spark.streaming.receiver.Receiver
-
Restart the receiver.
- restart(String, Throwable) - Method in class org.apache.spark.streaming.receiver.Receiver
-
Restart the receiver.
- restart(String, Throwable, int) - Method in class org.apache.spark.streaming.receiver.Receiver
-
Restart the receiver.
- ResubmitFailedStages - Class in org.apache.spark.scheduler
-
- ResubmitFailedStages() - Constructor for class org.apache.spark.scheduler.ResubmitFailedStages
-
- Resubmitted - Class in org.apache.spark
-
:: DeveloperApi ::
A ShuffleMapTask that completed successfully earlier, but we
lost the executor before the stage completed.
- Resubmitted() - Constructor for class org.apache.spark.Resubmitted
-
- result(Duration, CanAwait) - Method in class org.apache.spark.ComplexFutureAction
-
- result(Duration, CanAwait) - Method in interface org.apache.spark.FutureAction
-
Awaits and returns the result (of type T) of this action.
- result(Duration, CanAwait) - Method in class org.apache.spark.SimpleFutureAction
-
- RESULT_SERIALIZATION_TIME() - Static method in class org.apache.spark.InternalAccumulator
-
- RESULT_SERIALIZATION_TIME() - Static method in class org.apache.spark.ui.jobs.TaskDetailsClassNames
-
- RESULT_SERIALIZATION_TIME() - Static method in class org.apache.spark.ui.ToolTips
-
- RESULT_SIZE() - Static method in class org.apache.spark.InternalAccumulator
-
- resultSerializationTime() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
-
- resultSerializationTime() - Method in class org.apache.spark.status.api.v1.TaskMetrics
-
- resultSerializationTime() - Method in class org.apache.spark.ui.jobs.UIData.TaskMetricsUIData
-
- resultSetToObjectArray(ResultSet) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- resultSize() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
-
- resultSize() - Method in class org.apache.spark.status.api.v1.TaskMetrics
-
- resultSize() - Method in class org.apache.spark.ui.jobs.UIData.TaskMetricsUIData
-
- retainedJobs() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- retainedStages() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- retainedTasks() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- retryWaitMs(SparkConf) - Static method in class org.apache.spark.util.RpcUtils
-
Returns the configured number of milliseconds to wait on each retry
- ReturnStatementFinder - Class in org.apache.spark.util
-
- ReturnStatementFinder() - Constructor for class org.apache.spark.util.ReturnStatementFinder
-
- reverse() - Method in class org.apache.spark.graphx.EdgeDirection
-
Reverse the direction of an edge.
- reverse() - Method in class org.apache.spark.graphx.EdgeRDD
-
Reverse all the edges in this RDD.
- reverse() - Method in class org.apache.spark.graphx.Graph
-
Reverses all edges in the graph.
- reverse() - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- reverse() - Method in class org.apache.spark.graphx.impl.GraphImpl
-
- reverse(Column) - Static method in class org.apache.spark.sql.functions
-
Reverses the string column and returns it as a new string column.
- reverse() - Static method in class org.apache.spark.sql.types.StructType
-
- reverseIterator() - Static method in class org.apache.spark.sql.types.StructType
-
- reverseMap(Function1<A, B>, CanBuildFrom<Repr, B, That>) - Static method in class org.apache.spark.sql.types.StructType
-
- reverseRoutingTables() - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- reverseRoutingTables() - Method in class org.apache.spark.graphx.VertexRDD
-
Returns a new
VertexRDD reflecting a reversal of all edge directions in the corresponding
EdgeRDD.
- ReviveOffers - Class in org.apache.spark.scheduler.local
-
- ReviveOffers() - Constructor for class org.apache.spark.scheduler.local.ReviveOffers
-
- RFormula - Class in org.apache.spark.ml.feature
-
:: Experimental ::
Implements the transforms required for fitting a dataset against an R model formula.
- RFormula(String) - Constructor for class org.apache.spark.ml.feature.RFormula
-
- RFormula() - Constructor for class org.apache.spark.ml.feature.RFormula
-
- RFormulaModel - Class in org.apache.spark.ml.feature
-
:: Experimental ::
Model fitted by
RFormula.
- RFormulaParser - Class in org.apache.spark.ml.feature
-
Limited implementation of R formula parsing.
- RFormulaParser() - Constructor for class org.apache.spark.ml.feature.RFormulaParser
-
- RidgeRegressionModel - Class in org.apache.spark.mllib.regression
-
Regression model trained using RidgeRegression.
- RidgeRegressionModel(Vector, double) - Constructor for class org.apache.spark.mllib.regression.RidgeRegressionModel
-
- RidgeRegressionWithSGD - Class in org.apache.spark.mllib.regression
-
Train a regression model with L2-regularization using Stochastic Gradient Descent.
- RidgeRegressionWithSGD() - Constructor for class org.apache.spark.mllib.regression.RidgeRegressionWithSGD
-
Deprecated.
Use ml.regression.LinearRegression with elasticNetParam = 0.0. Note the default regParam is 0.01 for RidgeRegressionWithSGD, but is 0.0 for LinearRegression. Since 2.0.0.
- right() - Method in class org.apache.spark.sql.sources.And
-
- right() - Method in class org.apache.spark.sql.sources.Or
-
- rightCategories() - Method in class org.apache.spark.ml.tree.CategoricalSplit
-
Get sorted categories which split to the right
- rightChild() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData
-
- rightChild() - Method in class org.apache.spark.ml.tree.InternalNode
-
- rightChildIndex(int) - Static method in class org.apache.spark.mllib.tree.model.Node
-
Return the index of the right child of this node.
- rightImpurity() - Method in class org.apache.spark.mllib.tree.model.InformationGainStats
-
- rightNode() - Method in class org.apache.spark.mllib.tree.model.Node
-
- rightNodeId() - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.NodeData
-
- rightOuterJoin(JavaPairRDD<K, W>, Partitioner) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Perform a right outer join of this and other.
- rightOuterJoin(JavaPairRDD<K, W>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Perform a right outer join of this and other.
- rightOuterJoin(JavaPairRDD<K, W>, int) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Perform a right outer join of this and other.
- rightOuterJoin(RDD<Tuple2<K, W>>, Partitioner) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Perform a right outer join of this and other.
- rightOuterJoin(RDD<Tuple2<K, W>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Perform a right outer join of this and other.
- rightOuterJoin(RDD<Tuple2<K, W>>, int) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Perform a right outer join of this and other.
- rightOuterJoin(JavaPairDStream<K, W>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying 'right outer join' between RDDs of this DStream and
other DStream.
- rightOuterJoin(JavaPairDStream<K, W>, int) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying 'right outer join' between RDDs of this DStream and
other DStream.
- rightOuterJoin(JavaPairDStream<K, W>, Partitioner) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Return a new DStream by applying 'right outer join' between RDDs of this DStream and
other DStream.
- rightOuterJoin(JavaPairDStream<K, W>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- rightOuterJoin(JavaPairDStream<K, W>, int) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- rightOuterJoin(JavaPairDStream<K, W>, Partitioner) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- rightOuterJoin(JavaPairDStream<K, W>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- rightOuterJoin(JavaPairDStream<K, W>, int) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- rightOuterJoin(JavaPairDStream<K, W>, Partitioner) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- rightOuterJoin(DStream<Tuple2<K, W>>, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying 'right outer join' between RDDs of this DStream and
other DStream.
- rightOuterJoin(DStream<Tuple2<K, W>>, int, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying 'right outer join' between RDDs of this DStream and
other DStream.
- rightOuterJoin(DStream<Tuple2<K, W>>, Partitioner, ClassTag<W>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Return a new DStream by applying 'right outer join' between RDDs of this DStream and
other DStream.
- rightPredict() - Method in class org.apache.spark.mllib.tree.model.InformationGainStats
-
- rint(Column) - Static method in class org.apache.spark.sql.functions
-
Returns the double value that is closest in value to the argument and
is equal to a mathematical integer.
- rint(String) - Static method in class org.apache.spark.sql.functions
-
Returns the double value that is closest in value to the argument and
is equal to a mathematical integer.
- rlike(String) - Method in class org.apache.spark.sql.Column
-
SQL RLIKE expression (LIKE with Regex).
- RMATa() - Static method in class org.apache.spark.graphx.util.GraphGenerators
-
- RMATb() - Static method in class org.apache.spark.graphx.util.GraphGenerators
-
- RMATc() - Static method in class org.apache.spark.graphx.util.GraphGenerators
-
- RMATd() - Static method in class org.apache.spark.graphx.util.GraphGenerators
-
- rmatGraph(SparkContext, int, int) - Static method in class org.apache.spark.graphx.util.GraphGenerators
-
A random graph generator using the R-MAT model, proposed in
"R-MAT: A Recursive Model for Graph Mining" by Chakrabarti et al.
- rnd() - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
-
- roc() - Method in class org.apache.spark.ml.classification.BinaryLogisticRegressionSummary
-
Returns the receiver operating characteristic (ROC) curve,
which is a Dataframe having two fields (FPR, TPR)
with (0.0, 0.0) prepended and (1.0, 1.0) appended to it.
- roc() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
-
Returns the receiver operating characteristic (ROC) curve,
which is an RDD of (false positive rate, true positive rate)
with (0.0, 0.0) prepended and (1.0, 1.0) appended to it.
- rollup(Column...) - Method in class org.apache.spark.sql.Dataset
-
Create a multi-dimensional rollup for the current Dataset using the specified columns,
so we can run aggregation on them.
- rollup(String, String...) - Method in class org.apache.spark.sql.Dataset
-
Create a multi-dimensional rollup for the current Dataset using the specified columns,
so we can run aggregation on them.
- rollup(Seq<Column>) - Method in class org.apache.spark.sql.Dataset
-
Create a multi-dimensional rollup for the current Dataset using the specified columns,
so we can run aggregation on them.
- rollup(String, Seq<String>) - Method in class org.apache.spark.sql.Dataset
-
Create a multi-dimensional rollup for the current Dataset using the specified columns,
so we can run aggregation on them.
- rootMeanSquaredError() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
-
Returns the root mean squared error, which is defined as the square root of
the mean squared error.
- rootMeanSquaredError() - Method in class org.apache.spark.mllib.evaluation.RegressionMetrics
-
Returns the root mean squared error, which is defined as the square root of
the mean squared error.
- rootNode() - Method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- rootNode() - Method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- round(Column) - Static method in class org.apache.spark.sql.functions
-
Returns the value of the column e rounded to 0 decimal places.
- round(Column, int) - Static method in class org.apache.spark.sql.functions
-
Round the value of e to scale decimal places if scale >= 0
or at integral part when scale < 0.
- ROUND_CEILING() - Static method in class org.apache.spark.sql.types.Decimal
-
- ROUND_FLOOR() - Static method in class org.apache.spark.sql.types.Decimal
-
- ROUND_HALF_EVEN() - Static method in class org.apache.spark.sql.types.Decimal
-
- ROUND_HALF_UP() - Static method in class org.apache.spark.sql.types.Decimal
-
- ROW() - Static method in class org.apache.spark.api.r.SerializationFormats
-
- Row - Interface in org.apache.spark.sql
-
Represents one row of output from a relational operator.
- row_number() - Static method in class org.apache.spark.sql.functions
-
Window function: returns a sequential number starting at 1 within a window partition.
- RowFactory - Class in org.apache.spark.sql
-
A factory class used to construct
Row objects.
- RowFactory() - Constructor for class org.apache.spark.sql.RowFactory
-
- rowIndices() - Method in class org.apache.spark.ml.linalg.SparseMatrix
-
- rowIndices() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
-
- rowIter() - Static method in class org.apache.spark.ml.linalg.DenseMatrix
-
- rowIter() - Method in interface org.apache.spark.ml.linalg.Matrix
-
Returns an iterator of row vectors.
- rowIter() - Static method in class org.apache.spark.ml.linalg.SparseMatrix
-
- rowIter() - Static method in class org.apache.spark.mllib.linalg.DenseMatrix
-
- rowIter() - Method in interface org.apache.spark.mllib.linalg.Matrix
-
Returns an iterator of row vectors.
- rowIter() - Static method in class org.apache.spark.mllib.linalg.SparseMatrix
-
- RowMatrix - Class in org.apache.spark.mllib.linalg.distributed
-
Represents a row-oriented distributed Matrix with no meaningful row indices.
- RowMatrix(RDD<Vector>, long, int) - Constructor for class org.apache.spark.mllib.linalg.distributed.RowMatrix
-
- RowMatrix(RDD<Vector>) - Constructor for class org.apache.spark.mllib.linalg.distributed.RowMatrix
-
Alternative constructor leaving matrix dimensions to be determined automatically.
- rows() - Method in class org.apache.spark.mllib.linalg.distributed.IndexedRowMatrix
-
- rows() - Method in class org.apache.spark.mllib.linalg.distributed.RowMatrix
-
- rowsBetween(long, long) - Method in class org.apache.spark.sql.expressions.WindowSpec
-
Defines the frame boundaries, from start (inclusive) to end (inclusive).
- rowsPerBlock() - Method in class org.apache.spark.mllib.linalg.distributed.BlockMatrix
-
- rPackages() - Static method in class org.apache.spark.api.r.RUtils
-
- rpad(Column, int, String) - Static method in class org.apache.spark.sql.functions
-
Right-padded with pad to a length of len.
- RpcUtils - Class in org.apache.spark.util
-
- RpcUtils() - Constructor for class org.apache.spark.util.RpcUtils
-
- RRDD<T> - Class in org.apache.spark.api.r
-
An RDD that stores serialized R objects as Array[Byte].
- RRDD(RDD<T>, byte[], String, String, byte[], Object[], ClassTag<T>) - Constructor for class org.apache.spark.api.r.RRDD
-
- RRunnerModes - Class in org.apache.spark.api.r
-
- RRunnerModes() - Constructor for class org.apache.spark.api.r.RRunnerModes
-
- rtrim(Column) - Static method in class org.apache.spark.sql.functions
-
Trim the spaces from right end for the specified string value.
- run(Graph<VD, ED>, int, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.ConnectedComponents
-
Compute the connected component membership of each vertex and return a graph with the vertex
value containing the lowest vertex id in the connected component containing that vertex.
- run(Graph<VD, ED>, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.ConnectedComponents
-
Compute the connected component membership of each vertex and return a graph with the vertex
value containing the lowest vertex id in the connected component containing that vertex.
- run(Graph<VD, ED>, int, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.LabelPropagation
-
Run static Label Propagation for detecting communities in networks.
- run(Graph<VD, ED>, int, double, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.PageRank
-
Run PageRank for a fixed number of iterations returning a graph
with vertex attributes containing the PageRank and edge
attributes the normalized edge weight.
- run(Graph<VD, ED>, Seq<Object>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.ShortestPaths
-
Computes shortest paths to the given set of landmark vertices.
- run(Graph<VD, ED>, int, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.StronglyConnectedComponents
-
Compute the strongly connected component (SCC) of each vertex and return a graph with the
vertex value containing the lowest vertex id in the SCC containing that vertex.
- run(RDD<Edge<Object>>, SVDPlusPlus.Conf) - Static method in class org.apache.spark.graphx.lib.SVDPlusPlus
-
Implement SVD++ based on "Factorization Meets the Neighborhood:
a Multifaceted Collaborative Filtering Model",
available at http://public.research.att.com/~volinsky/netflix/kdd08koren.pdf.
- run(Graph<VD, ED>, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.TriangleCount
-
- run(RDD<LabeledPoint>, BoostingStrategy, long) - Static method in class org.apache.spark.ml.tree.impl.GradientBoostedTrees
-
Method to train a gradient boosting model
- run(RDD<LabeledPoint>, Strategy, int, String, long, Option<<any>>, Option<String>) - Static method in class org.apache.spark.ml.tree.impl.RandomForest
-
Train a random forest.
- run(RDD<LabeledPoint>) - Method in class org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS
-
Run Logistic Regression with the configured parameters on an input RDD
of LabeledPoint entries.
- run(RDD<LabeledPoint>, Vector) - Method in class org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS
-
Run Logistic Regression with the configured parameters on an input RDD
of LabeledPoint entries starting from the initial weights provided.
- run(RDD<LabeledPoint>) - Static method in class org.apache.spark.mllib.classification.LogisticRegressionWithSGD
-
- run(RDD<LabeledPoint>, Vector) - Static method in class org.apache.spark.mllib.classification.LogisticRegressionWithSGD
-
- run(RDD<LabeledPoint>) - Method in class org.apache.spark.mllib.classification.NaiveBayes
-
Run the algorithm with the configured parameters on an input RDD of LabeledPoint entries.
- run(RDD<LabeledPoint>) - Static method in class org.apache.spark.mllib.classification.SVMWithSGD
-
- run(RDD<LabeledPoint>, Vector) - Static method in class org.apache.spark.mllib.classification.SVMWithSGD
-
- run(RDD<Vector>) - Method in class org.apache.spark.mllib.clustering.BisectingKMeans
-
Runs the bisecting k-means algorithm.
- run(JavaRDD<Vector>) - Method in class org.apache.spark.mllib.clustering.BisectingKMeans
-
Java-friendly version of run().
- run(RDD<Vector>) - Method in class org.apache.spark.mllib.clustering.GaussianMixture
-
Perform expectation maximization
- run(JavaRDD<Vector>) - Method in class org.apache.spark.mllib.clustering.GaussianMixture
-
Java-friendly version of run()
- run(RDD<Vector>) - Method in class org.apache.spark.mllib.clustering.KMeans
-
Train a K-means model on the given set of points; data should be cached for high
performance, because this is an iterative algorithm.
- run(RDD<Tuple2<Object, Vector>>) - Method in class org.apache.spark.mllib.clustering.LDA
-
Learn an LDA model using the given dataset.
- run(JavaPairRDD<Long, Vector>) - Method in class org.apache.spark.mllib.clustering.LDA
-
Java-friendly version of run()
- run(Graph<Object, Object>) - Method in class org.apache.spark.mllib.clustering.PowerIterationClustering
-
Run the PIC algorithm on Graph.
- run(RDD<Tuple3<Object, Object, Object>>) - Method in class org.apache.spark.mllib.clustering.PowerIterationClustering
-
Run the PIC algorithm.
- run(JavaRDD<Tuple3<Long, Long, Double>>) - Method in class org.apache.spark.mllib.clustering.PowerIterationClustering
-
A Java-friendly version of PowerIterationClustering.run.
- run(RDD<FPGrowth.FreqItemset<Item>>, ClassTag<Item>) - Method in class org.apache.spark.mllib.fpm.AssociationRules
-
Computes the association rules with confidence above minConfidence.
- run(JavaRDD<FPGrowth.FreqItemset<Item>>) - Method in class org.apache.spark.mllib.fpm.AssociationRules
-
Java-friendly version of run.
- run(RDD<Object>, ClassTag<Item>) - Method in class org.apache.spark.mllib.fpm.FPGrowth
-
Computes an FP-Growth model that contains frequent itemsets.
- run(JavaRDD<Basket>) - Method in class org.apache.spark.mllib.fpm.FPGrowth
-
Java-friendly version of run.
- run(RDD<Object[]>, ClassTag<Item>) - Method in class org.apache.spark.mllib.fpm.PrefixSpan
-
Finds the complete set of frequent sequential patterns in the input sequences of itemsets.
- run(JavaRDD<Sequence>) - Method in class org.apache.spark.mllib.fpm.PrefixSpan
-
A Java-friendly version of
run() that reads sequences from a
JavaRDD and returns
frequent sequences in a
PrefixSpanModel.
- run(RDD<Rating>) - Method in class org.apache.spark.mllib.recommendation.ALS
-
Run ALS with the configured parameters on an input RDD of
Rating objects.
- run(JavaRDD<Rating>) - Method in class org.apache.spark.mllib.recommendation.ALS
-
Java-friendly version of ALS.run.
- run(RDD<LabeledPoint>) - Method in class org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm
-
Run the algorithm with the configured parameters on an input
RDD of LabeledPoint entries.
- run(RDD<LabeledPoint>, Vector) - Method in class org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm
-
Run the algorithm with the configured parameters on an input RDD
of LabeledPoint entries starting from the initial weights provided.
- run(RDD<Tuple3<Object, Object, Object>>) - Method in class org.apache.spark.mllib.regression.IsotonicRegression
-
Run IsotonicRegression algorithm to obtain isotonic regression model.
- run(JavaRDD<Tuple3<Double, Double, Double>>) - Method in class org.apache.spark.mllib.regression.IsotonicRegression
-
Run pool adjacent violators algorithm to obtain isotonic regression model.
- run(RDD<LabeledPoint>) - Static method in class org.apache.spark.mllib.regression.LassoWithSGD
-
- run(RDD<LabeledPoint>, Vector) - Static method in class org.apache.spark.mllib.regression.LassoWithSGD
-
- run(RDD<LabeledPoint>) - Static method in class org.apache.spark.mllib.regression.LinearRegressionWithSGD
-
- run(RDD<LabeledPoint>, Vector) - Static method in class org.apache.spark.mllib.regression.LinearRegressionWithSGD
-
- run(RDD<LabeledPoint>) - Static method in class org.apache.spark.mllib.regression.RidgeRegressionWithSGD
-
- run(RDD<LabeledPoint>, Vector) - Static method in class org.apache.spark.mllib.regression.RidgeRegressionWithSGD
-
- run(RDD<LabeledPoint>) - Method in class org.apache.spark.mllib.tree.DecisionTree
-
Method to train a decision tree model over an RDD
- run(RDD<LabeledPoint>) - Method in class org.apache.spark.mllib.tree.GradientBoostedTrees
-
Method to train a gradient boosting model
- run(JavaRDD<LabeledPoint>) - Method in class org.apache.spark.mllib.tree.GradientBoostedTrees
-
Java-friendly API for org.apache.spark.mllib.tree.GradientBoostedTrees!#run.
- run(RDD<LabeledPoint>) - Method in class org.apache.spark.mllib.tree.RandomForest
-
Method to train a decision tree model over an RDD
- run(SparkSession) - Method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- run() - Method in class org.apache.spark.sql.hive.execution.ScriptTransformationWriterThread
-
- run() - Method in class org.apache.spark.util.SparkShutdownHook
-
- runApproximateJob(RDD<T>, Function2<TaskContext, Iterator<T>, U>, <any>, long) - Method in class org.apache.spark.SparkContext
-
:: DeveloperApi ::
Run a job that can return approximate results.
- runInNewThread(String, boolean, Function0<T>) - Static method in class org.apache.spark.util.ThreadUtils
-
Run a piece of code in a new thread and return the result.
- runJob(RDD<T>, Function2<TaskContext, Iterator<T>, U>, Seq<Object>, Function2<Object, U, BoxedUnit>, ClassTag<U>) - Method in class org.apache.spark.SparkContext
-
Run a function on a given set of partitions in an RDD and pass the results to the given
handler function.
- runJob(RDD<T>, Function2<TaskContext, Iterator<T>, U>, Seq<Object>, ClassTag<U>) - Method in class org.apache.spark.SparkContext
-
Run a function on a given set of partitions in an RDD and return the results as an array.
- runJob(RDD<T>, Function1<Iterator<T>, U>, Seq<Object>, ClassTag<U>) - Method in class org.apache.spark.SparkContext
-
Run a job on a given set of partitions of an RDD, but take a function of type
Iterator[T] => U instead of (TaskContext, Iterator[T]) => U.
- runJob(RDD<T>, Function2<TaskContext, Iterator<T>, U>, ClassTag<U>) - Method in class org.apache.spark.SparkContext
-
Run a job on all partitions in an RDD and return the results in an array.
- runJob(RDD<T>, Function1<Iterator<T>, U>, ClassTag<U>) - Method in class org.apache.spark.SparkContext
-
Run a job on all partitions in an RDD and return the results in an array.
- runJob(RDD<T>, Function2<TaskContext, Iterator<T>, U>, Function2<Object, U, BoxedUnit>, ClassTag<U>) - Method in class org.apache.spark.SparkContext
-
Run a job on all partitions in an RDD and pass the results to a handler function.
- runJob(RDD<T>, Function1<Iterator<T>, U>, Function2<Object, U, BoxedUnit>, ClassTag<U>) - Method in class org.apache.spark.SparkContext
-
Run a job on all partitions in an RDD and pass the results to a handler function.
- runLBFGS(RDD<Tuple2<Object, Vector>>, Gradient, Updater, int, double, int, double, Vector) - Static method in class org.apache.spark.mllib.optimization.LBFGS
-
Run Limited-memory BFGS (L-BFGS) in parallel.
- runMiniBatchSGD(RDD<Tuple2<Object, Vector>>, Gradient, Updater, double, int, double, double, Vector, double) - Static method in class org.apache.spark.mllib.optimization.GradientDescent
-
Run stochastic gradient descent (SGD) in parallel using mini batches.
- runMiniBatchSGD(RDD<Tuple2<Object, Vector>>, Gradient, Updater, double, int, double, double, Vector) - Static method in class org.apache.spark.mllib.optimization.GradientDescent
-
Alias of runMiniBatchSGD with convergenceTol set to default value of 0.001.
- running() - Method in class org.apache.spark.scheduler.TaskInfo
-
- RUNNING() - Static method in class org.apache.spark.TaskState
-
- runPreCanonicalized(Graph<VD, ED>, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.TriangleCount
-
- RuntimeConfig - Class in org.apache.spark.sql
-
Runtime configuration interface for Spark.
- RuntimePercentage - Class in org.apache.spark.scheduler
-
- RuntimePercentage(double, Option<Object>, double) - Constructor for class org.apache.spark.scheduler.RuntimePercentage
-
- runUntilConvergence(Graph<VD, ED>, double, double, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.PageRank
-
Run a dynamic version of PageRank returning a graph with vertex attributes containing the
PageRank and edge attributes containing the normalized edge weight.
- runUntilConvergenceWithOptions(Graph<VD, ED>, double, double, Option<Object>, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.PageRank
-
Run a dynamic version of PageRank returning a graph with vertex attributes containing the
PageRank and edge attributes containing the normalized edge weight.
- runWith(Function1<B, U>) - Static method in class org.apache.spark.sql.types.StructType
-
- runWithOptions(Graph<VD, ED>, int, double, Option<Object>, ClassTag<VD>, ClassTag<ED>) - Static method in class org.apache.spark.graphx.lib.PageRank
-
Run PageRank for a fixed number of iterations returning a graph
with vertex attributes containing the PageRank and edge
attributes the normalized edge weight.
- runWithValidation(RDD<LabeledPoint>, RDD<LabeledPoint>, BoostingStrategy, long) - Static method in class org.apache.spark.ml.tree.impl.GradientBoostedTrees
-
Method to validate a gradient boosting model
- runWithValidation(RDD<LabeledPoint>, RDD<LabeledPoint>) - Method in class org.apache.spark.mllib.tree.GradientBoostedTrees
-
Method to validate a gradient boosting model
- runWithValidation(JavaRDD<LabeledPoint>, JavaRDD<LabeledPoint>) - Method in class org.apache.spark.mllib.tree.GradientBoostedTrees
-
Java-friendly API for org.apache.spark.mllib.tree.GradientBoostedTrees!#runWithValidation.
- RUtils - Class in org.apache.spark.api.r
-
- RUtils() - Constructor for class org.apache.spark.api.r.RUtils
-
- RWrappers - Class in org.apache.spark.ml.r
-
This is the Scala stub of SparkR read.ml.
- RWrappers() - Constructor for class org.apache.spark.ml.r.RWrappers
-
- s() - Method in class org.apache.spark.mllib.linalg.SingularValueDecomposition
-
- sameElements(GenIterable<B>) - Static method in class org.apache.spark.sql.types.StructType
-
- sameResult(PlanType) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- sameResult(PlanType) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- sameResult(PlanType) - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- sameThread() - Static method in class org.apache.spark.util.ThreadUtils
-
An ExecutionContextExecutor that runs each task in the thread that invokes execute/submit.
- sample(boolean, Double) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Return a sampled subset of this RDD.
- sample(boolean, Double, long) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Return a sampled subset of this RDD.
- sample(boolean, double) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return a sampled subset of this RDD.
- sample(boolean, double, long) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return a sampled subset of this RDD.
- sample(boolean, double) - Method in class org.apache.spark.api.java.JavaRDD
-
Return a sampled subset of this RDD.
- sample(boolean, double, long) - Method in class org.apache.spark.api.java.JavaRDD
-
Return a sampled subset of this RDD.
- sample(boolean, double, long) - Static method in class org.apache.spark.api.r.RRDD
-
- sample(boolean, double, long) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- sample(boolean, double, long) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- sample(boolean, double, long) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- sample(boolean, double, long) - Static method in class org.apache.spark.graphx.VertexRDD
-
- sample(boolean, double, long) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- sample(boolean, double, long) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- sample(boolean, double, long) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- sample(boolean, double, long) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- sample(boolean, double, long) - Method in class org.apache.spark.rdd.RDD
-
Return a sampled subset of this RDD.
- sample(boolean, double, long) - Static method in class org.apache.spark.rdd.UnionRDD
-
- sample(boolean, double, long) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset by sampling a fraction of rows.
- sample(boolean, double) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset by sampling a fraction of rows, using a random seed.
- sample() - Method in class org.apache.spark.util.random.BernoulliCellSampler
-
- sample() - Method in class org.apache.spark.util.random.BernoulliSampler
-
- sample() - Method in class org.apache.spark.util.random.PoissonSampler
-
- sample(Iterator<T>) - Method in class org.apache.spark.util.random.PoissonSampler
-
- sample(Iterator<T>) - Method in interface org.apache.spark.util.random.RandomSampler
-
take a random sample
- sample() - Method in interface org.apache.spark.util.random.RandomSampler
-
Whether to sample the next item or not.
- sample$default$3() - Static method in class org.apache.spark.api.r.RRDD
-
- sample$default$3() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- sample$default$3() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- sample$default$3() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- sample$default$3() - Static method in class org.apache.spark.graphx.VertexRDD
-
- sample$default$3() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- sample$default$3() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- sample$default$3() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- sample$default$3() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- sample$default$3() - Static method in class org.apache.spark.rdd.UnionRDD
-
- sampleBy(String, Map<T, Object>, long) - Method in class org.apache.spark.sql.DataFrameStatFunctions
-
Returns a stratified sample without replacement based on the fraction given on each stratum.
- sampleBy(String, Map<T, Double>, long) - Method in class org.apache.spark.sql.DataFrameStatFunctions
-
Returns a stratified sample without replacement based on the fraction given on each stratum.
- sampleByKey(boolean, Map<K, Double>, long) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return a subset of this RDD sampled by key (via stratified sampling).
- sampleByKey(boolean, Map<K, Double>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return a subset of this RDD sampled by key (via stratified sampling).
- sampleByKey(boolean, Map<K, Object>, long) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Return a subset of this RDD sampled by key (via stratified sampling).
- sampleByKeyExact(boolean, Map<K, Double>, long) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return a subset of this RDD sampled by key (via stratified sampling) containing exactly
math.ceil(numItems * samplingRate) for each stratum (group of pairs with the same key).
- sampleByKeyExact(boolean, Map<K, Double>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Return a subset of this RDD sampled by key (via stratified sampling) containing exactly
math.ceil(numItems * samplingRate) for each stratum (group of pairs with the same key).
- sampleByKeyExact(boolean, Map<K, Object>, long) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Return a subset of this RDD sampled by key (via stratified sampling) containing exactly
math.ceil(numItems * samplingRate) for each stratum (group of pairs with the same key).
- sampleStdev() - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Compute the sample standard deviation of this RDD's elements (which corrects for bias in
estimating the standard deviation by dividing by N-1 instead of N).
- sampleStdev() - Method in class org.apache.spark.rdd.DoubleRDDFunctions
-
Compute the sample standard deviation of this RDD's elements (which corrects for bias in
estimating the standard deviation by dividing by N-1 instead of N).
- sampleStdev() - Method in class org.apache.spark.util.StatCounter
-
Return the sample standard deviation of the values, which corrects for bias in estimating the
variance by dividing by N-1 instead of N.
- sampleVariance() - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Compute the sample variance of this RDD's elements (which corrects for bias in
estimating the standard variance by dividing by N-1 instead of N).
- sampleVariance() - Method in class org.apache.spark.rdd.DoubleRDDFunctions
-
Compute the sample variance of this RDD's elements (which corrects for bias in
estimating the variance by dividing by N-1 instead of N).
- sampleVariance() - Method in class org.apache.spark.util.StatCounter
-
Return the sample variance, which corrects for bias in estimating the variance by dividing
by N-1 instead of N.
- SamplingUtils - Class in org.apache.spark.util.random
-
- SamplingUtils() - Constructor for class org.apache.spark.util.random.SamplingUtils
-
- save(String) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- save(String) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- save(String) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- save(String) - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- save(String) - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- save(String) - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- save(String) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- save(String) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- save(String) - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- save(String) - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- save(String) - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- save(String) - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- save(String) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- save(String) - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- save(String) - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- save(String) - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- save(String) - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- save(String) - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- save(String) - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- save(String) - Static method in class org.apache.spark.ml.clustering.KMeans
-
- save(String) - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- save(String) - Static method in class org.apache.spark.ml.clustering.LDA
-
- save(String) - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- save(String) - Static method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- save(String) - Static method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
- save(String) - Static method in class org.apache.spark.ml.evaluation.RegressionEvaluator
-
- save(String) - Static method in class org.apache.spark.ml.feature.Binarizer
-
- save(String) - Static method in class org.apache.spark.ml.feature.Bucketizer
-
- save(String) - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- save(String) - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- save(String) - Static method in class org.apache.spark.ml.feature.ColumnPruner
-
- save(String) - Static method in class org.apache.spark.ml.feature.CountVectorizer
-
- save(String) - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- save(String) - Static method in class org.apache.spark.ml.feature.DCT
-
- save(String) - Static method in class org.apache.spark.ml.feature.ElementwiseProduct
-
- save(String) - Static method in class org.apache.spark.ml.feature.HashingTF
-
- save(String) - Static method in class org.apache.spark.ml.feature.IDF
-
- save(String) - Static method in class org.apache.spark.ml.feature.IDFModel
-
- save(String) - Static method in class org.apache.spark.ml.feature.IndexToString
-
- save(String) - Static method in class org.apache.spark.ml.feature.Interaction
-
- save(String) - Static method in class org.apache.spark.ml.feature.MaxAbsScaler
-
- save(String) - Static method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- save(String) - Static method in class org.apache.spark.ml.feature.MinMaxScaler
-
- save(String) - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- save(String) - Static method in class org.apache.spark.ml.feature.NGram
-
- save(String) - Static method in class org.apache.spark.ml.feature.Normalizer
-
- save(String) - Static method in class org.apache.spark.ml.feature.OneHotEncoder
-
- save(String) - Static method in class org.apache.spark.ml.feature.PCA
-
- save(String) - Static method in class org.apache.spark.ml.feature.PCAModel
-
- save(String) - Static method in class org.apache.spark.ml.feature.PolynomialExpansion
-
- save(String) - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- save(String) - Static method in class org.apache.spark.ml.feature.RegexTokenizer
-
- save(String) - Static method in class org.apache.spark.ml.feature.RFormula
-
- save(String) - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- save(String) - Static method in class org.apache.spark.ml.feature.SQLTransformer
-
- save(String) - Static method in class org.apache.spark.ml.feature.StandardScaler
-
- save(String) - Static method in class org.apache.spark.ml.feature.StandardScalerModel
-
- save(String) - Static method in class org.apache.spark.ml.feature.StopWordsRemover
-
- save(String) - Static method in class org.apache.spark.ml.feature.StringIndexer
-
- save(String) - Static method in class org.apache.spark.ml.feature.StringIndexerModel
-
- save(String) - Static method in class org.apache.spark.ml.feature.Tokenizer
-
- save(String) - Static method in class org.apache.spark.ml.feature.VectorAssembler
-
- save(String) - Static method in class org.apache.spark.ml.feature.VectorAttributeRewriter
-
- save(String) - Static method in class org.apache.spark.ml.feature.VectorIndexer
-
- save(String) - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- save(String) - Static method in class org.apache.spark.ml.feature.VectorSlicer
-
- save(String) - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- save(String) - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- save(String) - Static method in class org.apache.spark.ml.Pipeline
-
- save(String) - Static method in class org.apache.spark.ml.PipelineModel
-
- save(String) - Static method in class org.apache.spark.ml.recommendation.ALS
-
- save(String) - Static method in class org.apache.spark.ml.recommendation.ALSModel
-
- save(String) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- save(String) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- save(String) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- save(String) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- save(String) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- save(String) - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- save(String) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- save(String) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- save(String) - Static method in class org.apache.spark.ml.regression.IsotonicRegression
-
- save(String) - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- save(String) - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- save(String) - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- save(String) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- save(String) - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- save(String) - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- save(String) - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- save(String) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- save(String) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
-
- save(String) - Method in interface org.apache.spark.ml.util.MLWritable
-
Saves this ML instance to the input path, a shortcut of write.save(path).
- save(String) - Method in class org.apache.spark.ml.util.MLWriter
-
Saves the ML instances to the input path.
- save(SparkContext, String, String, int, int, Vector, double, Option<Object>) - Method in class org.apache.spark.mllib.classification.impl.GLMClassificationModel.SaveLoadV1_0$
-
Helper method for saving GLM classification model metadata and data.
- save(SparkContext, String) - Method in class org.apache.spark.mllib.classification.LogisticRegressionModel
-
- save(SparkContext, String) - Method in class org.apache.spark.mllib.classification.NaiveBayesModel
-
- save(SparkContext, String, org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0.Data) - Method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0$
-
- save(SparkContext, String, org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0.Data) - Method in class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$
-
- save(SparkContext, String) - Method in class org.apache.spark.mllib.classification.SVMModel
-
- save(SparkContext, String) - Method in class org.apache.spark.mllib.clustering.BisectingKMeansModel
-
- save(SparkContext, BisectingKMeansModel, String) - Method in class org.apache.spark.mllib.clustering.BisectingKMeansModel.SaveLoadV1_0$
-
- save(SparkContext, String) - Method in class org.apache.spark.mllib.clustering.DistributedLDAModel
-
- save(SparkContext, String) - Method in class org.apache.spark.mllib.clustering.GaussianMixtureModel
-
- save(SparkContext, String) - Method in class org.apache.spark.mllib.clustering.KMeansModel
-
- save(SparkContext, KMeansModel, String) - Method in class org.apache.spark.mllib.clustering.KMeansModel.SaveLoadV1_0$
-
- save(SparkContext, String) - Method in class org.apache.spark.mllib.clustering.LocalLDAModel
-
- save(SparkContext, String) - Method in class org.apache.spark.mllib.clustering.PowerIterationClusteringModel
-
- save(SparkContext, PowerIterationClusteringModel, String) - Method in class org.apache.spark.mllib.clustering.PowerIterationClusteringModel.SaveLoadV1_0$
-
- save(SparkContext, String) - Method in class org.apache.spark.mllib.feature.ChiSqSelectorModel
-
- save(SparkContext, ChiSqSelectorModel, String) - Method in class org.apache.spark.mllib.feature.ChiSqSelectorModel.SaveLoadV1_0$
-
- save(SparkContext, String) - Method in class org.apache.spark.mllib.feature.Word2VecModel
-
- save(SparkContext, String) - Method in class org.apache.spark.mllib.fpm.FPGrowthModel
-
Save this model to the given path.
- save(FPGrowthModel<?>, String) - Method in class org.apache.spark.mllib.fpm.FPGrowthModel.SaveLoadV1_0$
-
- save(SparkContext, String) - Method in class org.apache.spark.mllib.fpm.PrefixSpanModel
-
Save this model to the given path.
- save(PrefixSpanModel<?>, String) - Method in class org.apache.spark.mllib.fpm.PrefixSpanModel.SaveLoadV1_0$
-
- save(SparkContext, String) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel
-
Save this model to the given path.
- save(MatrixFactorizationModel, String) - Method in class org.apache.spark.mllib.recommendation.MatrixFactorizationModel.SaveLoadV1_0$
-
Saves a
MatrixFactorizationModel, where user features are saved under
data/users and
product features are saved under
data/products.
- save(SparkContext, String, String, Vector, double) - Method in class org.apache.spark.mllib.regression.impl.GLMRegressionModel.SaveLoadV1_0$
-
Helper method for saving GLM regression model metadata and data.
- save(SparkContext, String) - Method in class org.apache.spark.mllib.regression.IsotonicRegressionModel
-
- save(SparkContext, String) - Method in class org.apache.spark.mllib.regression.LassoModel
-
- save(SparkContext, String) - Method in class org.apache.spark.mllib.regression.LinearRegressionModel
-
- save(SparkContext, String) - Method in class org.apache.spark.mllib.regression.RidgeRegressionModel
-
- save(SparkContext, String) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel
-
- save(SparkContext, String, DecisionTreeModel) - Method in class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$
-
- save(SparkContext, String) - Method in class org.apache.spark.mllib.tree.model.GradientBoostedTreesModel
-
- save(SparkContext, String) - Method in class org.apache.spark.mllib.tree.model.RandomForestModel
-
- save(SparkContext, String) - Method in interface org.apache.spark.mllib.util.Saveable
-
Save this model to the given path.
- save(String) - Method in class org.apache.spark.sql.DataFrameWriter
-
Saves the content of the DataFrame at the specified path.
- save() - Method in class org.apache.spark.sql.DataFrameWriter
-
Saves the content of the DataFrame as the specified table.
- Saveable - Interface in org.apache.spark.mllib.util
-
:: DeveloperApi ::
- saveAsHadoopDataset(JobConf) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Output the RDD to any Hadoop-supported storage system, using a Hadoop JobConf object for
that storage system.
- saveAsHadoopDataset(JobConf) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Output the RDD to any Hadoop-supported storage system, using a Hadoop JobConf object for
that storage system.
- saveAsHadoopFile(String, Class<?>, Class<?>, Class<F>, JobConf) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Output the RDD to any Hadoop-supported file system.
- saveAsHadoopFile(String, Class<?>, Class<?>, Class<F>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Output the RDD to any Hadoop-supported file system.
- saveAsHadoopFile(String, Class<?>, Class<?>, Class<F>, Class<? extends CompressionCodec>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Output the RDD to any Hadoop-supported file system, compressing with the supplied codec.
- saveAsHadoopFile(String, ClassTag<F>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Output the RDD to any Hadoop-supported file system, using a Hadoop OutputFormat class
supporting the key and value types K and V in this RDD.
- saveAsHadoopFile(String, Class<? extends CompressionCodec>, ClassTag<F>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Output the RDD to any Hadoop-supported file system, using a Hadoop OutputFormat class
supporting the key and value types K and V in this RDD.
- saveAsHadoopFile(String, Class<?>, Class<?>, Class<? extends OutputFormat<?, ?>>, Class<? extends CompressionCodec>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Output the RDD to any Hadoop-supported file system, using a Hadoop OutputFormat class
supporting the key and value types K and V in this RDD.
- saveAsHadoopFile(String, Class<?>, Class<?>, Class<? extends OutputFormat<?, ?>>, JobConf, Option<Class<? extends CompressionCodec>>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Output the RDD to any Hadoop-supported file system, using a Hadoop OutputFormat class
supporting the key and value types K and V in this RDD.
- saveAsHadoopFiles(String, String) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Save each RDD in this DStream as a Hadoop file.
- saveAsHadoopFiles(String, String, Class<?>, Class<?>, Class<F>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Save each RDD in this DStream as a Hadoop file.
- saveAsHadoopFiles(String, String, Class<?>, Class<?>, Class<F>, JobConf) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Save each RDD in this DStream as a Hadoop file.
- saveAsHadoopFiles(String, String) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- saveAsHadoopFiles(String, String, Class<?>, Class<?>, Class<F>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- saveAsHadoopFiles(String, String, Class<?>, Class<?>, Class<F>, JobConf) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- saveAsHadoopFiles(String, String) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- saveAsHadoopFiles(String, String, Class<?>, Class<?>, Class<F>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- saveAsHadoopFiles(String, String, Class<?>, Class<?>, Class<F>, JobConf) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- saveAsHadoopFiles(String, String, ClassTag<F>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Save each RDD in this DStream as a Hadoop file.
- saveAsHadoopFiles(String, String, Class<?>, Class<?>, Class<? extends OutputFormat<?, ?>>, JobConf) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Save each RDD in this DStream as a Hadoop file.
- saveAsLibSVMFile(RDD<LabeledPoint>, String) - Static method in class org.apache.spark.mllib.util.MLUtils
-
Save labeled data in LIBSVM format.
- saveAsNewAPIHadoopDataset(Configuration) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Output the RDD to any Hadoop-supported storage system, using
a Configuration object for that storage system.
- saveAsNewAPIHadoopDataset(Configuration) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Output the RDD to any Hadoop-supported storage system with new Hadoop API, using a Hadoop
Configuration object for that storage system.
- saveAsNewAPIHadoopFile(String, Class<?>, Class<?>, Class<F>, Configuration) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Output the RDD to any Hadoop-supported file system.
- saveAsNewAPIHadoopFile(String, Class<?>, Class<?>, Class<F>) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Output the RDD to any Hadoop-supported file system.
- saveAsNewAPIHadoopFile(String, ClassTag<F>) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Output the RDD to any Hadoop-supported file system, using a new Hadoop API OutputFormat
(mapreduce.OutputFormat) object supporting the key and value types K and V in this RDD.
- saveAsNewAPIHadoopFile(String, Class<?>, Class<?>, Class<? extends OutputFormat<?, ?>>, Configuration) - Method in class org.apache.spark.rdd.PairRDDFunctions
-
Output the RDD to any Hadoop-supported file system, using a new Hadoop API OutputFormat
(mapreduce.OutputFormat) object supporting the key and value types K and V in this RDD.
- saveAsNewAPIHadoopFiles(String, String) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Save each RDD in this DStream as a Hadoop file.
- saveAsNewAPIHadoopFiles(String, String, Class<?>, Class<?>, Class<F>) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Save each RDD in this DStream as a Hadoop file.
- saveAsNewAPIHadoopFiles(String, String, Class<?>, Class<?>, Class<F>, Configuration) - Method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
Save each RDD in this DStream as a Hadoop file.
- saveAsNewAPIHadoopFiles(String, String) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- saveAsNewAPIHadoopFiles(String, String, Class<?>, Class<?>, Class<F>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- saveAsNewAPIHadoopFiles(String, String, Class<?>, Class<?>, Class<F>, Configuration) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- saveAsNewAPIHadoopFiles(String, String) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- saveAsNewAPIHadoopFiles(String, String, Class<?>, Class<?>, Class<F>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- saveAsNewAPIHadoopFiles(String, String, Class<?>, Class<?>, Class<F>, Configuration) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- saveAsNewAPIHadoopFiles(String, String, ClassTag<F>) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Save each RDD in this DStream as a Hadoop file.
- saveAsNewAPIHadoopFiles(String, String, Class<?>, Class<?>, Class<? extends OutputFormat<?, ?>>, Configuration) - Method in class org.apache.spark.streaming.dstream.PairDStreamFunctions
-
Save each RDD in this DStream as a Hadoop file.
- saveAsNewAPIHadoopFiles$default$6() - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- saveAsNewAPIHadoopFiles$default$6() - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- saveAsObjectFile(String) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- saveAsObjectFile(String) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- saveAsObjectFile(String) - Static method in class org.apache.spark.api.java.JavaRDD
-
- saveAsObjectFile(String) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Save this RDD as a SequenceFile of serialized objects.
- saveAsObjectFile(String) - Static method in class org.apache.spark.api.r.RRDD
-
- saveAsObjectFile(String) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- saveAsObjectFile(String) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- saveAsObjectFile(String) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- saveAsObjectFile(String) - Static method in class org.apache.spark.graphx.VertexRDD
-
- saveAsObjectFile(String) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- saveAsObjectFile(String) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- saveAsObjectFile(String) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- saveAsObjectFile(String) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- saveAsObjectFile(String) - Method in class org.apache.spark.rdd.RDD
-
Save this RDD as a SequenceFile of serialized objects.
- saveAsObjectFile(String) - Static method in class org.apache.spark.rdd.UnionRDD
-
- saveAsObjectFiles(String, String) - Method in class org.apache.spark.streaming.dstream.DStream
-
Save each RDD in this DStream as a Sequence file of serialized objects.
- saveAsSequenceFile(String, Option<Class<? extends CompressionCodec>>) - Method in class org.apache.spark.rdd.SequenceFileRDDFunctions
-
Output the RDD as a Hadoop SequenceFile using the Writable types we infer from the RDD's key
and value types.
- saveAsTable(String) - Method in class org.apache.spark.sql.DataFrameWriter
-
Saves the content of the DataFrame as the specified table.
- saveAsTextFile(String) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- saveAsTextFile(String, Class<? extends CompressionCodec>) - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- saveAsTextFile(String) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- saveAsTextFile(String, Class<? extends CompressionCodec>) - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- saveAsTextFile(String) - Static method in class org.apache.spark.api.java.JavaRDD
-
- saveAsTextFile(String, Class<? extends CompressionCodec>) - Static method in class org.apache.spark.api.java.JavaRDD
-
- saveAsTextFile(String) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Save this RDD as a text file, using string representations of elements.
- saveAsTextFile(String, Class<? extends CompressionCodec>) - Method in interface org.apache.spark.api.java.JavaRDDLike
-
Save this RDD as a compressed text file, using string representations of elements.
- saveAsTextFile(String) - Static method in class org.apache.spark.api.r.RRDD
-
- saveAsTextFile(String, Class<? extends CompressionCodec>) - Static method in class org.apache.spark.api.r.RRDD
-
- saveAsTextFile(String) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- saveAsTextFile(String, Class<? extends CompressionCodec>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- saveAsTextFile(String) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- saveAsTextFile(String, Class<? extends CompressionCodec>) - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- saveAsTextFile(String) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- saveAsTextFile(String, Class<? extends CompressionCodec>) - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- saveAsTextFile(String) - Static method in class org.apache.spark.graphx.VertexRDD
-
- saveAsTextFile(String, Class<? extends CompressionCodec>) - Static method in class org.apache.spark.graphx.VertexRDD
-
- saveAsTextFile(String) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- saveAsTextFile(String, Class<? extends CompressionCodec>) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- saveAsTextFile(String) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- saveAsTextFile(String, Class<? extends CompressionCodec>) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- saveAsTextFile(String) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- saveAsTextFile(String, Class<? extends CompressionCodec>) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- saveAsTextFile(String) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- saveAsTextFile(String, Class<? extends CompressionCodec>) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- saveAsTextFile(String) - Method in class org.apache.spark.rdd.RDD
-
Save this RDD as a text file, using string representations of elements.
- saveAsTextFile(String, Class<? extends CompressionCodec>) - Method in class org.apache.spark.rdd.RDD
-
Save this RDD as a compressed text file, using string representations of elements.
- saveAsTextFile(String) - Static method in class org.apache.spark.rdd.UnionRDD
-
- saveAsTextFile(String, Class<? extends CompressionCodec>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- saveAsTextFiles(String, String) - Method in class org.apache.spark.streaming.dstream.DStream
-
Save each RDD in this DStream as at text file, using string representation
of elements.
- saveImpl(Params, PipelineStage[], SparkContext, String) - Method in class org.apache.spark.ml.Pipeline.SharedReadWrite$
-
Save metadata and stages for a
Pipeline or
PipelineModel
- save metadata to path/metadata
- save stages to stages/IDX_UID
- saveImpl(M, String, SparkSession, JsonAST.JObject) - Static method in class org.apache.spark.ml.tree.EnsembleModelReadWrite
-
Helper method for saving a tree ensemble to disk.
- saveMode(String) - Static method in class org.apache.spark.sql.api.r.SQLUtils
-
- SaveMode - Enum in org.apache.spark.sql
-
SaveMode is used to specify the expected behavior of saving a DataFrame to a data source.
- sc() - Method in class org.apache.spark.api.java.JavaSparkContext
-
- sc() - Method in class org.apache.spark.sql.SQLImplicits.StringToColumn
-
- scal(double, Vector) - Static method in class org.apache.spark.ml.linalg.BLAS
-
x = a * x
- scal(double, Vector) - Static method in class org.apache.spark.mllib.linalg.BLAS
-
x = a * x
- scalaBoolean() - Static method in class org.apache.spark.sql.Encoders
-
An encoder for Scala's primitive boolean type.
- scalaByte() - Static method in class org.apache.spark.sql.Encoders
-
An encoder for Scala's primitive byte type.
- scalaDouble() - Static method in class org.apache.spark.sql.Encoders
-
An encoder for Scala's primitive double type.
- scalaFloat() - Static method in class org.apache.spark.sql.Encoders
-
An encoder for Scala's primitive float type.
- scalaInt() - Static method in class org.apache.spark.sql.Encoders
-
An encoder for Scala's primitive int type.
- scalaIntToJavaLong(DStream<Object>) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- scalaIntToJavaLong(DStream<Object>) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
- scalaIntToJavaLong(DStream<Object>) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- scalaIntToJavaLong(DStream<Object>) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- scalaIntToJavaLong(DStream<Object>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- scalaIntToJavaLong(DStream<Object>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- scalaIntToJavaLong(DStream<Object>) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- scalaLong() - Static method in class org.apache.spark.sql.Encoders
-
An encoder for Scala's primitive long type.
- scalaShort() - Static method in class org.apache.spark.sql.Encoders
-
An encoder for Scala's primitive short type.
- scalaToJavaLong(JavaPairDStream<K, Object>, ClassTag<K>) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- scale() - Method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- scale() - Method in class org.apache.spark.mllib.random.GammaGenerator
-
- scale() - Method in class org.apache.spark.sql.types.Decimal
-
- scale() - Method in class org.apache.spark.sql.types.DecimalType
-
- scalingVec() - Method in class org.apache.spark.ml.feature.ElementwiseProduct
-
the vector to multiply with input vectors
- scalingVec() - Method in class org.apache.spark.mllib.feature.ElementwiseProduct
-
- scan(B, Function2<B, B, B>, CanBuildFrom<Repr, B, That>) - Static method in class org.apache.spark.sql.types.StructType
-
- scanLeft(B, Function2<B, A, B>, CanBuildFrom<Repr, B, That>) - Static method in class org.apache.spark.sql.types.StructType
-
- scanRight(B, Function2<A, B, B>, CanBuildFrom<Repr, B, That>) - Static method in class org.apache.spark.sql.types.StructType
-
- SCHEDULED() - Static method in class org.apache.spark.streaming.scheduler.ReceiverState
-
- SCHEDULER_DELAY() - Static method in class org.apache.spark.ui.jobs.TaskDetailsClassNames
-
- SCHEDULER_DELAY() - Static method in class org.apache.spark.ui.ToolTips
-
- schedulingDelay() - Method in class org.apache.spark.streaming.scheduler.BatchInfo
-
Time taken for the first job of this batch to start processing from the time this batch
was submitted to the streaming scheduler.
- SchedulingMode - Class in org.apache.spark.scheduler
-
"FAIR" and "FIFO" determines which policy is used
to order tasks amongst a Schedulable's sub-queues
"NONE" is used when the a Schedulable has no sub-queues.
- SchedulingMode() - Constructor for class org.apache.spark.scheduler.SchedulingMode
-
- schedulingMode() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- schedulingPool() - Method in class org.apache.spark.status.api.v1.StageData
-
- schedulingPool() - Method in class org.apache.spark.ui.jobs.UIData.StageUIData
-
- schema(StructType) - Method in class org.apache.spark.sql.DataFrameReader
-
Specifies the input schema.
- schema() - Method in class org.apache.spark.sql.Dataset
-
Returns the schema of this Dataset.
- schema() - Method in interface org.apache.spark.sql.Encoder
-
Returns the schema of encoding this type of object as a Row.
- schema() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- schema() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- schema() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- schema() - Method in interface org.apache.spark.sql.Row
-
Schema for the row.
- schema() - Method in class org.apache.spark.sql.sources.BaseRelation
-
- schema(StructType) - Method in class org.apache.spark.sql.streaming.DataStreamReader
-
:: Experimental ::
Specifies the input schema.
- schemaLess() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- SchemaRelationProvider - Interface in org.apache.spark.sql.sources
-
::DeveloperApi::
Implemented by objects that produce relations for a specific kind of data source
with a given schema.
- schemaString() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- schemaString() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- schemaString() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- SchemaUtils - Class in org.apache.spark.ml.util
-
Utils for handling schemas.
- SchemaUtils() - Constructor for class org.apache.spark.ml.util.SchemaUtils
-
- scope() - Method in class org.apache.spark.storage.RDDInfo
-
- scoreAndLabels() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
-
- scratch() - Method in class org.apache.spark.mllib.optimization.NNLS.Workspace
-
- script() - Method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- ScriptTransformation - Class in org.apache.spark.sql.hive.execution
-
Transforms the input by forking and running the specified script.
- ScriptTransformation(Seq<Expression>, String, Seq<Attribute>, SparkPlan, HiveScriptIOSchema) - Constructor for class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- ScriptTransformationWriterThread - Class in org.apache.spark.sql.hive.execution
-
- ScriptTransformationWriterThread(Iterator<InternalRow>, Seq<DataType>, org.apache.spark.sql.catalyst.expressions.Projection, AbstractSerDe, ObjectInspector, HiveScriptIOSchema, OutputStream, Process, org.apache.spark.util.CircularBuffer, TaskContext, Configuration) - Constructor for class org.apache.spark.sql.hive.execution.ScriptTransformationWriterThread
-
- second(Column) - Static method in class org.apache.spark.sql.functions
-
Extracts the seconds as an integer from a given date/timestamp/string.
- seconds() - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- seconds(long) - Static method in class org.apache.spark.streaming.Durations
-
- Seconds - Class in org.apache.spark.streaming
-
Helper object that creates instance of
Duration representing
a given number of seconds.
- Seconds() - Constructor for class org.apache.spark.streaming.Seconds
-
- securityManager() - Method in class org.apache.spark.SparkEnv
-
- seed() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- seed() - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- seed() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- seed() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- seed() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- seed() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- seed() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- seed() - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- seed() - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- seed() - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- seed() - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- seed() - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- seed() - Static method in class org.apache.spark.ml.clustering.KMeans
-
- seed() - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- seed() - Static method in class org.apache.spark.ml.clustering.LDA
-
- seed() - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- seed() - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- seed() - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- seed() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- seed() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- seed() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- seed() - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- seed() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- seed() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- seed() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- seed() - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- seed() - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- seed() - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- seed() - Static method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
-
- seedBrokers() - Method in class org.apache.spark.streaming.kafka.KafkaCluster.SimpleConsumerConfig
-
- segmentLength(Function1<A, Object>, int) - Static method in class org.apache.spark.sql.types.StructType
-
- select(Column...) - Method in class org.apache.spark.sql.Dataset
-
Selects a set of column based expressions.
- select(String, String...) - Method in class org.apache.spark.sql.Dataset
-
Selects a set of columns.
- select(Seq<Column>) - Method in class org.apache.spark.sql.Dataset
-
Selects a set of column based expressions.
- select(String, Seq<String>) - Method in class org.apache.spark.sql.Dataset
-
Selects a set of columns.
- select(TypedColumn<T, U1>, Encoder<U1>) - Method in class org.apache.spark.sql.Dataset
-
:: Experimental ::
Returns a new Dataset by computing the given
Column expression for each element.
- select(TypedColumn<T, U1>, TypedColumn<T, U2>) - Method in class org.apache.spark.sql.Dataset
-
:: Experimental ::
Returns a new Dataset by computing the given
Column expressions for each element.
- select(TypedColumn<T, U1>, TypedColumn<T, U2>, TypedColumn<T, U3>) - Method in class org.apache.spark.sql.Dataset
-
:: Experimental ::
Returns a new Dataset by computing the given
Column expressions for each element.
- select(TypedColumn<T, U1>, TypedColumn<T, U2>, TypedColumn<T, U3>, TypedColumn<T, U4>) - Method in class org.apache.spark.sql.Dataset
-
:: Experimental ::
Returns a new Dataset by computing the given
Column expressions for each element.
- select(TypedColumn<T, U1>, TypedColumn<T, U2>, TypedColumn<T, U3>, TypedColumn<T, U4>, TypedColumn<T, U5>) - Method in class org.apache.spark.sql.Dataset
-
:: Experimental ::
Returns a new Dataset by computing the given
Column expressions for each element.
- selectedFeatures() - Method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
list of indices to select (filter).
- selectedFeatures() - Method in class org.apache.spark.mllib.feature.ChiSqSelectorModel
-
- selectExpr(String...) - Method in class org.apache.spark.sql.Dataset
-
Selects a set of SQL expressions.
- selectExpr(Seq<String>) - Method in class org.apache.spark.sql.Dataset
-
Selects a set of SQL expressions.
- sender() - Method in class org.apache.spark.storage.BlockManagerMessages.RegisterBlockManager
-
- sendToDst(A) - Method in class org.apache.spark.graphx.EdgeContext
-
Sends a message to the destination vertex.
- sendToDst(A) - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
-
- sendToSrc(A) - Method in class org.apache.spark.graphx.EdgeContext
-
Sends a message to the source vertex.
- sendToSrc(A) - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
-
- seq() - Static method in class org.apache.spark.sql.types.StructType
-
- seqToString(Seq<T>, Function1<T, String>) - Static method in class org.apache.spark.internal.config.ConfigHelpers
-
- sequence() - Method in class org.apache.spark.mllib.fpm.PrefixSpan.FreqSequence
-
- sequenceFile(String, Class<K>, Class<V>, int) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Get an RDD for a Hadoop SequenceFile with given key and value types.
- sequenceFile(String, Class<K>, Class<V>) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Get an RDD for a Hadoop SequenceFile.
- sequenceFile(String, Class<K>, Class<V>, int) - Method in class org.apache.spark.SparkContext
-
Get an RDD for a Hadoop SequenceFile with given key and value types.
- sequenceFile(String, Class<K>, Class<V>) - Method in class org.apache.spark.SparkContext
-
Get an RDD for a Hadoop SequenceFile with given key and value types.
- sequenceFile(String, int, ClassTag<K>, ClassTag<V>, Function0<WritableConverter<K>>, Function0<WritableConverter<V>>) - Method in class org.apache.spark.SparkContext
-
Version of sequenceFile() for types implicitly convertible to Writables through a
WritableConverter.
- SequenceFileRDDFunctions<K,V> - Class in org.apache.spark.rdd
-
Extra functions available on RDDs of (key, value) pairs to create a Hadoop SequenceFile,
through an implicit conversion.
- SequenceFileRDDFunctions(RDD<Tuple2<K, V>>, Class<? extends Writable>, Class<? extends Writable>, Function1<K, Writable>, ClassTag<K>, Function1<V, Writable>, ClassTag<V>) - Constructor for class org.apache.spark.rdd.SequenceFileRDDFunctions
-
- SerDe - Class in org.apache.spark.api.r
-
Utility functions to serialize, deserialize objects to / from R
- SerDe() - Constructor for class org.apache.spark.api.r.SerDe
-
- serde() - Method in class org.apache.spark.sql.internal.HiveSerDe
-
- SerializableWritable<T extends org.apache.hadoop.io.Writable> - Class in org.apache.spark
-
- SerializableWritable(T) - Constructor for class org.apache.spark.SerializableWritable
-
- SerializationDebugger - Class in org.apache.spark.serializer
-
- SerializationDebugger() - Constructor for class org.apache.spark.serializer.SerializationDebugger
-
- SerializationDebugger.ObjectStreamClassMethods - Class in org.apache.spark.serializer
-
An implicit class that allows us to call private methods of ObjectStreamClass.
- SerializationDebugger.ObjectStreamClassMethods(ObjectStreamClass) - Constructor for class org.apache.spark.serializer.SerializationDebugger.ObjectStreamClassMethods
-
- SerializationDebugger.ObjectStreamClassMethods$ - Class in org.apache.spark.serializer
-
- SerializationDebugger.ObjectStreamClassMethods$() - Constructor for class org.apache.spark.serializer.SerializationDebugger.ObjectStreamClassMethods$
-
- SerializationFormats - Class in org.apache.spark.api.r
-
- SerializationFormats() - Constructor for class org.apache.spark.api.r.SerializationFormats
-
- SerializationStream - Class in org.apache.spark.serializer
-
:: DeveloperApi ::
A stream for writing serialized objects.
- SerializationStream() - Constructor for class org.apache.spark.serializer.SerializationStream
-
- serialize(Vector) - Method in class org.apache.spark.mllib.linalg.VectorUDT
-
- serialize(T, ClassTag<T>) - Method in class org.apache.spark.serializer.DummySerializerInstance
-
- serialize(T, ClassTag<T>) - Method in class org.apache.spark.serializer.SerializerInstance
-
- serialize(T) - Static method in class org.apache.spark.util.Utils
-
Serialize an object using Java serialization
- SERIALIZED_R_DATA_SCHEMA() - Static method in class org.apache.spark.sql.api.r.SQLUtils
-
- serializedData() - Method in class org.apache.spark.scheduler.local.StatusUpdate
-
- SerializedMemoryEntry<T> - Class in org.apache.spark.storage.memory
-
- SerializedMemoryEntry(org.apache.spark.util.io.ChunkedByteBuffer, MemoryMode, ClassTag<T>) - Constructor for class org.apache.spark.storage.memory.SerializedMemoryEntry
-
- Serializer - Class in org.apache.spark.serializer
-
:: DeveloperApi ::
A serializer.
- Serializer() - Constructor for class org.apache.spark.serializer.Serializer
-
- serializer() - Method in class org.apache.spark.ShuffleDependency
-
- serializer() - Method in class org.apache.spark.SparkEnv
-
- SerializerInstance - Class in org.apache.spark.serializer
-
:: DeveloperApi ::
An instance of a serializer, for use by one thread at a time.
- SerializerInstance() - Constructor for class org.apache.spark.serializer.SerializerInstance
-
- serializerManager() - Method in class org.apache.spark.SparkEnv
-
- serializeStream(OutputStream) - Method in class org.apache.spark.serializer.DummySerializerInstance
-
- serializeStream(OutputStream) - Method in class org.apache.spark.serializer.SerializerInstance
-
- serializeViaNestedStream(OutputStream, SerializerInstance, Function1<SerializationStream, BoxedUnit>) - Static method in class org.apache.spark.util.Utils
-
Serialize via nested stream using specific serializer
- session(SparkSession) - Static method in class org.apache.spark.ml.r.RWrappers
-
- session(SparkSession) - Method in class org.apache.spark.ml.util.MLReader
-
- session(SparkSession) - Method in class org.apache.spark.ml.util.MLWriter
-
- set(long, long, int, int, VD, VD, ED) - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.clustering.KMeans
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.clustering.LDA
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.evaluation.RegressionEvaluator
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.Binarizer
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.Bucketizer
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.ColumnPruner
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.CountVectorizer
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.DCT
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.ElementwiseProduct
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.HashingTF
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.IDF
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.IDFModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.IndexToString
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.Interaction
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.MaxAbsScaler
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.MinMaxScaler
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.NGram
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.Normalizer
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.OneHotEncoder
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.PCA
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.PCAModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.PolynomialExpansion
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.RegexTokenizer
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.RFormula
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.SQLTransformer
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.StandardScaler
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.StandardScalerModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.StopWordsRemover
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.StringIndexer
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.StringIndexerModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.Tokenizer
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.VectorAssembler
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.VectorAttributeRewriter
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.VectorIndexer
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.VectorSlicer
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- set(Param<T>, T) - Method in interface org.apache.spark.ml.param.Params
-
Sets a parameter in the embedded param map.
- set(String, Object) - Method in interface org.apache.spark.ml.param.Params
-
Sets a parameter (by name) in the embedded param map.
- set(ParamPair<?>) - Method in interface org.apache.spark.ml.param.Params
-
Sets a parameter in the embedded param map.
- set(Param<T>, T) - Static method in class org.apache.spark.ml.Pipeline
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.PipelineModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.recommendation.ALS
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.recommendation.ALSModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.regression.IsotonicRegression
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- set(Param<T>, T) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
-
- set(String, String) - Method in class org.apache.spark.SparkConf
-
Set a configuration variable.
- set(SparkEnv) - Static method in class org.apache.spark.SparkEnv
-
- set(String, String) - Method in class org.apache.spark.sql.RuntimeConfig
-
Sets the given Spark runtime configuration property.
- set(String, boolean) - Method in class org.apache.spark.sql.RuntimeConfig
-
Sets the given Spark runtime configuration property.
- set(String, long) - Method in class org.apache.spark.sql.RuntimeConfig
-
Sets the given Spark runtime configuration property.
- set(long) - Method in class org.apache.spark.sql.types.Decimal
-
Set this Decimal to the given Long.
- set(int) - Method in class org.apache.spark.sql.types.Decimal
-
Set this Decimal to the given Int.
- set(long, int, int) - Method in class org.apache.spark.sql.types.Decimal
-
Set this Decimal to the given unscaled Long, with a given precision and scale.
- set(BigDecimal, int, int) - Method in class org.apache.spark.sql.types.Decimal
-
Set this Decimal to the given BigDecimal value, with a given precision and scale.
- set(BigDecimal) - Method in class org.apache.spark.sql.types.Decimal
-
Set this Decimal to the given BigDecimal value, inheriting its precision and scale.
- set(BigInteger) - Method in class org.apache.spark.sql.types.Decimal
-
Set this Decimal to the given BigInteger value.
- set(Decimal) - Method in class org.apache.spark.sql.types.Decimal
-
Set this Decimal to the given Decimal value.
- setAcceptsNull(boolean) - Static method in class org.apache.spark.serializer.JavaIterableWrapperSerializer
-
- setActive(SQLContext) - Static method in class org.apache.spark.sql.SQLContext
-
Deprecated.
Use SparkSession.setActiveSession instead. Since 2.0.0.
- setActiveSession(SparkSession) - Static method in class org.apache.spark.sql.SparkSession
-
Changes the SparkSession that will be returned in this thread and its children when
SparkSession.getOrCreate() is called.
- setAggregator(Aggregator<K, V, C>) - Method in class org.apache.spark.rdd.ShuffledRDD
-
Set aggregator for RDD's shuffle.
- setAlgo(String) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
Sets Algorithm using a String.
- setAll(Traversable<Tuple2<String, String>>) - Method in class org.apache.spark.SparkConf
-
Set multiple parameters together
- setAlpha(double) - Method in class org.apache.spark.ml.recommendation.ALS
-
- setAlpha(Vector) - Method in class org.apache.spark.mllib.clustering.LDA
-
Alias for setDocConcentration()
- setAlpha(double) - Method in class org.apache.spark.mllib.clustering.LDA
-
Alias for setDocConcentration()
- setAlpha(double) - Method in class org.apache.spark.mllib.recommendation.ALS
-
Sets the constant used in computing confidence in implicit ALS.
- setAppName(String) - Method in class org.apache.spark.launcher.SparkLauncher
-
Set the application name.
- setAppName(String) - Method in class org.apache.spark.SparkConf
-
Set a name for your application.
- setAppResource(String) - Method in class org.apache.spark.launcher.SparkLauncher
-
Set the main application resource.
- setBandwidth(double) - Method in class org.apache.spark.mllib.stat.KernelDensity
-
Sets the bandwidth (standard deviation) of the Gaussian kernel (default: 1.0).
- setBeta(double) - Method in class org.apache.spark.mllib.clustering.LDA
-
Alias for setTopicConcentration()
- setBinary(boolean) - Method in class org.apache.spark.ml.feature.CountVectorizer
-
- setBinary(boolean) - Method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- setBinary(boolean) - Method in class org.apache.spark.ml.feature.HashingTF
-
- setBinary(boolean) - Method in class org.apache.spark.mllib.feature.HashingTF
-
If true, term frequency vector will be binary such that non-zero term counts will be set to 1
(default: false)
- setBlocks(int) - Method in class org.apache.spark.mllib.recommendation.ALS
-
Set the number of blocks for both user blocks and product blocks to parallelize the computation
into; pass -1 for an auto-configured number of blocks.
- setBlockSize(int) - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
Sets the value of param blockSize.
- setCacheNodeIds(boolean) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- setCacheNodeIds(boolean) - Method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- setCacheNodeIds(boolean) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- setCacheNodeIds(boolean) - Method in class org.apache.spark.ml.classification.GBTClassifier
-
- setCacheNodeIds(boolean) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- setCacheNodeIds(boolean) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- setCacheNodeIds(boolean) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- setCacheNodeIds(boolean) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- setCacheNodeIds(boolean) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- setCacheNodeIds(boolean) - Method in class org.apache.spark.ml.regression.GBTRegressor
-
- setCacheNodeIds(boolean) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- setCacheNodeIds(boolean) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- setCallSite(String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Pass-through to SparkContext.setCallSite.
- setCallSite(String) - Method in class org.apache.spark.SparkContext
-
Set the thread-local property for overriding the call sites
of actions and RDDs.
- setCaseSensitive(boolean) - Method in class org.apache.spark.ml.feature.StopWordsRemover
-
- setCategoricalFeaturesInfo(Map<Integer, Integer>) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
Sets categoricalFeaturesInfo using a Java Map.
- setCensorCol(String) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- setCheckpointDir(String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Set the directory under which RDDs are going to be checkpointed.
- setCheckpointDir(String) - Method in class org.apache.spark.SparkContext
-
Set the directory under which RDDs are going to be checkpointed.
- setCheckpointInterval(int) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- setCheckpointInterval(int) - Method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- setCheckpointInterval(int) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- setCheckpointInterval(int) - Method in class org.apache.spark.ml.classification.GBTClassifier
-
- setCheckpointInterval(int) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- setCheckpointInterval(int) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- setCheckpointInterval(int) - Method in class org.apache.spark.ml.clustering.LDA
-
- setCheckpointInterval(int) - Method in class org.apache.spark.ml.recommendation.ALS
-
- setCheckpointInterval(int) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- setCheckpointInterval(int) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- setCheckpointInterval(int) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- setCheckpointInterval(int) - Method in class org.apache.spark.ml.regression.GBTRegressor
-
- setCheckpointInterval(int) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- setCheckpointInterval(int) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- setCheckpointInterval(int) - Method in class org.apache.spark.mllib.clustering.LDA
-
Parameter for set checkpoint interval (>= 1) or disable checkpoint (-1).
- setCheckpointInterval(int) - Method in class org.apache.spark.mllib.recommendation.ALS
-
:: DeveloperApi ::
Set period (in iterations) between checkpoints (default = 10).
- setCheckpointInterval(int) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- setClassifier(Classifier<?, ?, ?>) - Method in class org.apache.spark.ml.classification.OneVsRest
-
- setConf(String, String) - Method in class org.apache.spark.launcher.SparkLauncher
-
Set a single configuration value for the application.
- setConf(Properties) - Method in class org.apache.spark.sql.SQLContext
-
Set Spark SQL configuration properties.
- setConf(String, String) - Method in class org.apache.spark.sql.SQLContext
-
Set the given Spark SQL configuration property.
- setConfig(String, String) - Static method in class org.apache.spark.launcher.SparkLauncher
-
Set a configuration value for the launcher library.
- setConsumerOffsetMetadata(String, Map<TopicAndPartition, OffsetAndMetadata>) - Method in class org.apache.spark.streaming.kafka.KafkaCluster
-
Requires Kafka >= 0.8.1.1.
- setConsumerOffsetMetadata(String, Map<TopicAndPartition, OffsetAndMetadata>, short) - Method in class org.apache.spark.streaming.kafka.KafkaCluster
-
- setConsumerOffsets(String, Map<TopicAndPartition, Object>) - Method in class org.apache.spark.streaming.kafka.KafkaCluster
-
Requires Kafka >= 0.8.1.1.
- setConsumerOffsets(String, Map<TopicAndPartition, Object>, short) - Method in class org.apache.spark.streaming.kafka.KafkaCluster
-
- setConvergenceTol(double) - Method in class org.apache.spark.mllib.clustering.GaussianMixture
-
Set the largest change in log-likelihood at which convergence is
considered to have occurred.
- setConvergenceTol(double) - Method in class org.apache.spark.mllib.optimization.GradientDescent
-
Set the convergence tolerance.
- setConvergenceTol(double) - Method in class org.apache.spark.mllib.optimization.LBFGS
-
Set the convergence tolerance of iterations for L-BFGS.
- setConvergenceTol(double) - Method in class org.apache.spark.mllib.regression.StreamingLinearRegressionWithSGD
-
Set the convergence tolerance.
- setCurrentDatabase(String) - Method in class org.apache.spark.sql.catalog.Catalog
-
Sets the current default database in this session.
- setCurrentDatabase(String) - Method in class org.apache.spark.sql.internal.CatalogImpl
-
Sets the current default database in this session.
- setCustomHostname(String) - Static method in class org.apache.spark.util.Utils
-
Allow setting a custom host name because when we run on Mesos we need to use the same
hostname it reports to the master.
- setDecayFactor(double) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
-
Set the forgetfulness of the previous centroids.
- setDefault(Param<T>, T) - Method in interface org.apache.spark.ml.param.Params
-
Sets a default value for a param.
- setDefault(Seq<ParamPair<?>>) - Method in interface org.apache.spark.ml.param.Params
-
Sets default values for a list of params.
- setDefaultClassLoader(ClassLoader) - Static method in class org.apache.spark.serializer.KryoSerializer
-
- setDefaultClassLoader(ClassLoader) - Method in class org.apache.spark.serializer.Serializer
-
Sets a class loader for the serializer to use in deserialization.
- setDefaultSession(SparkSession) - Static method in class org.apache.spark.sql.SparkSession
-
Sets the default SparkSession that is returned by the builder.
- setDegree(int) - Method in class org.apache.spark.ml.feature.PolynomialExpansion
-
- setDeployMode(String) - Method in class org.apache.spark.launcher.SparkLauncher
-
Set the deploy mode for the application.
- setDocConcentration(double[]) - Method in class org.apache.spark.ml.clustering.LDA
-
- setDocConcentration(double) - Method in class org.apache.spark.ml.clustering.LDA
-
- setDocConcentration(Vector) - Method in class org.apache.spark.mllib.clustering.LDA
-
Concentration parameter (commonly named "alpha") for the prior placed on documents'
distributions over topics ("theta").
- setDocConcentration(double) - Method in class org.apache.spark.mllib.clustering.LDA
-
Replicates a Double docConcentration to create a symmetric prior.
- setDropLast(boolean) - Method in class org.apache.spark.ml.feature.OneHotEncoder
-
- setElasticNetParam(double) - Method in class org.apache.spark.ml.classification.LogisticRegression
-
Set the ElasticNet mixing parameter.
- setElasticNetParam(double) - Method in class org.apache.spark.ml.regression.LinearRegression
-
Set the ElasticNet mixing parameter.
- setEpsilon(double) - Method in class org.apache.spark.mllib.clustering.KMeans
-
Set the distance threshold within which we've consider centers to have converged.
- setEstimator(Estimator<?>) - Method in class org.apache.spark.ml.tuning.CrossValidator
-
- setEstimator(Estimator<?>) - Method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- setEstimatorParamMaps(ParamMap[]) - Method in class org.apache.spark.ml.tuning.CrossValidator
-
- setEstimatorParamMaps(ParamMap[]) - Method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- setEvaluator(Evaluator) - Method in class org.apache.spark.ml.tuning.CrossValidator
-
- setEvaluator(Evaluator) - Method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- setExecutorEnv(String, String) - Method in class org.apache.spark.SparkConf
-
Set an environment variable to be used when launching executors for this application.
- setExecutorEnv(Seq<Tuple2<String, String>>) - Method in class org.apache.spark.SparkConf
-
Set multiple environment variables to be used when launching executors.
- setExecutorEnv(Tuple2<String, String>[]) - Method in class org.apache.spark.SparkConf
-
Set multiple environment variables to be used when launching executors.
- setFamily(String) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
Sets the value of param family.
- setFeatureIndex(int) - Method in class org.apache.spark.ml.regression.IsotonicRegression
-
- setFeatureIndex(int) - Method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- setFeaturesCol(String) - Method in class org.apache.spark.ml.classification.OneVsRest
-
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- setFeaturesCol(String) - Method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- setFeaturesCol(String) - Method in class org.apache.spark.ml.clustering.GaussianMixture
-
- setFeaturesCol(String) - Method in class org.apache.spark.ml.clustering.KMeans
-
- setFeaturesCol(String) - Method in class org.apache.spark.ml.clustering.KMeansModel
-
- setFeaturesCol(String) - Method in class org.apache.spark.ml.clustering.LDA
-
The features for LDA should be a Vector representing the word counts in a document.
- setFeaturesCol(String) - Method in class org.apache.spark.ml.clustering.LDAModel
-
The features for LDA should be a Vector representing the word counts in a document.
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- setFeaturesCol(String) - Method in class org.apache.spark.ml.feature.ChiSqSelector
-
- setFeaturesCol(String) - Method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- setFeaturesCol(String) - Method in class org.apache.spark.ml.feature.RFormula
-
- setFeaturesCol(String) - Method in class org.apache.spark.ml.PredictionModel
-
- setFeaturesCol(String) - Method in class org.apache.spark.ml.Predictor
-
- setFeaturesCol(String) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- setFeaturesCol(String) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- setFeaturesCol(String) - Method in class org.apache.spark.ml.regression.IsotonicRegression
-
- setFeaturesCol(String) - Method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- setFeaturesCol(String) - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- setFeatureSubsetStrategy(String) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- setFeatureSubsetStrategy(String) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- setFeatureSubsetStrategy(String) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- setFeatureSubsetStrategy(String) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- setFinalRDDStorageLevel(StorageLevel) - Method in class org.apache.spark.mllib.recommendation.ALS
-
:: DeveloperApi ::
Sets storage level for final RDDs (user/product used in MatrixFactorizationModel).
- setFinalStorageLevel(String) - Method in class org.apache.spark.ml.recommendation.ALS
-
- setFitIntercept(boolean) - Method in class org.apache.spark.ml.classification.LogisticRegression
-
Whether to fit an intercept term.
- setFitIntercept(boolean) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
Set if we should fit the intercept
Default is true.
- setFitIntercept(boolean) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
Sets if we should fit the intercept.
- setFitIntercept(boolean) - Method in class org.apache.spark.ml.regression.LinearRegression
-
Set if we should fit the intercept
Default is true.
- setFormula(String) - Method in class org.apache.spark.ml.feature.RFormula
-
Sets the formula to use for this transformer.
- setGaps(boolean) - Method in class org.apache.spark.ml.feature.RegexTokenizer
-
- setGenerics(Kryo, Class<?>[]) - Static method in class org.apache.spark.serializer.JavaIterableWrapperSerializer
-
- setGradient(Gradient) - Method in class org.apache.spark.mllib.optimization.GradientDescent
-
Set the gradient function (of the loss function of one single data example)
to be used for SGD.
- setGradient(Gradient) - Method in class org.apache.spark.mllib.optimization.LBFGS
-
Set the gradient function (of the loss function of one single data example)
to be used for L-BFGS.
- setHalfLife(double, String) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
-
Set the half life and time unit ("batches" or "points").
- setHandleInvalid(String) - Method in class org.apache.spark.ml.feature.StringIndexer
-
- setHandleInvalid(String) - Method in class org.apache.spark.ml.feature.StringIndexerModel
-
- setHashAlgorithm(String) - Method in class org.apache.spark.mllib.feature.HashingTF
-
Set the hash algorithm used when mapping term to integer.
- setIfMissing(String, String) - Method in class org.apache.spark.SparkConf
-
Set a parameter if it isn't already configured
- setImmutable(boolean) - Static method in class org.apache.spark.serializer.JavaIterableWrapperSerializer
-
- setImplicitPrefs(boolean) - Method in class org.apache.spark.ml.recommendation.ALS
-
- setImplicitPrefs(boolean) - Method in class org.apache.spark.mllib.recommendation.ALS
-
Sets whether to use implicit preference.
- setImpurity(String) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- setImpurity(String) - Method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- setImpurity(String) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- setImpurity(String) - Method in class org.apache.spark.ml.classification.GBTClassifier
-
The impurity setting is ignored for GBT models.
- setImpurity(String) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- setImpurity(String) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- setImpurity(String) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- setImpurity(String) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- setImpurity(String) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- setImpurity(String) - Method in class org.apache.spark.ml.regression.GBTRegressor
-
The impurity setting is ignored for GBT models.
- setImpurity(String) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- setImpurity(String) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- setImpurity(Impurity) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- setIndices(int[]) - Method in class org.apache.spark.ml.feature.VectorSlicer
-
- setInitialCenters(Vector[], double[]) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
-
Specify initial centers directly.
- setInitializationMode(String) - Method in class org.apache.spark.mllib.clustering.KMeans
-
Set the initialization algorithm.
- setInitializationMode(String) - Method in class org.apache.spark.mllib.clustering.PowerIterationClustering
-
Set the initialization mode.
- setInitializationSteps(int) - Method in class org.apache.spark.mllib.clustering.KMeans
-
Set the number of steps for the k-means|| initialization mode.
- setInitialModel(GaussianMixtureModel) - Method in class org.apache.spark.mllib.clustering.GaussianMixture
-
Set the initial GMM starting point, bypassing the random initialization.
- setInitialModel(KMeansModel) - Method in class org.apache.spark.mllib.clustering.KMeans
-
Set the initial starting point, bypassing the random initialization or k-means||
The condition model.k == this.k must be met, failure results
in an IllegalArgumentException.
- setInitialWeights(Vector) - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
Sets the value of param initialWeights.
- setInitialWeights(Vector) - Method in class org.apache.spark.mllib.classification.StreamingLogisticRegressionWithSGD
-
Set the initial weights.
- setInitialWeights(Vector) - Method in class org.apache.spark.mllib.regression.StreamingLinearRegressionWithSGD
-
Set the initial weights.
- setInitMode(String) - Method in class org.apache.spark.ml.clustering.KMeans
-
- setInitSteps(int) - Method in class org.apache.spark.ml.clustering.KMeans
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.Binarizer
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.Bucketizer
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.CountVectorizer
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- setInputCol(String) - Static method in class org.apache.spark.ml.feature.DCT
-
- setInputCol(String) - Static method in class org.apache.spark.ml.feature.ElementwiseProduct
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.HashingTF
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.IDF
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.IDFModel
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.IndexToString
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.MaxAbsScaler
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.MinMaxScaler
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- setInputCol(String) - Static method in class org.apache.spark.ml.feature.NGram
-
- setInputCol(String) - Static method in class org.apache.spark.ml.feature.Normalizer
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.OneHotEncoder
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.PCA
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.PCAModel
-
- setInputCol(String) - Static method in class org.apache.spark.ml.feature.PolynomialExpansion
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- setInputCol(String) - Static method in class org.apache.spark.ml.feature.RegexTokenizer
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.StandardScaler
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.StandardScalerModel
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.StopWordsRemover
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.StringIndexer
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.StringIndexerModel
-
- setInputCol(String) - Static method in class org.apache.spark.ml.feature.Tokenizer
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.VectorIndexer
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.VectorSlicer
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.Word2Vec
-
- setInputCol(String) - Method in class org.apache.spark.ml.feature.Word2VecModel
-
- setInputCol(String) - Method in class org.apache.spark.ml.UnaryTransformer
-
- setInputCols(String[]) - Method in class org.apache.spark.ml.feature.Interaction
-
- setInputCols(String[]) - Method in class org.apache.spark.ml.feature.VectorAssembler
-
- setIntercept(boolean) - Static method in class org.apache.spark.mllib.classification.LogisticRegressionWithSGD
-
- setIntercept(boolean) - Static method in class org.apache.spark.mllib.classification.SVMWithSGD
-
- setIntercept(boolean) - Method in class org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm
-
Set if the algorithm should add an intercept.
- setIntercept(boolean) - Static method in class org.apache.spark.mllib.regression.LassoWithSGD
-
- setIntercept(boolean) - Static method in class org.apache.spark.mllib.regression.LinearRegressionWithSGD
-
- setIntercept(boolean) - Static method in class org.apache.spark.mllib.regression.RidgeRegressionWithSGD
-
- setIntermediateRDDStorageLevel(StorageLevel) - Method in class org.apache.spark.mllib.recommendation.ALS
-
:: DeveloperApi ::
Sets storage level for intermediate RDDs (user/product in/out links).
- setIntermediateStorageLevel(String) - Method in class org.apache.spark.ml.recommendation.ALS
-
- setInverse(boolean) - Method in class org.apache.spark.ml.feature.DCT
-
- setIsotonic(boolean) - Method in class org.apache.spark.ml.regression.IsotonicRegression
-
- setIsotonic(boolean) - Method in class org.apache.spark.mllib.regression.IsotonicRegression
-
Sets the isotonic parameter.
- setItemCol(String) - Method in class org.apache.spark.ml.recommendation.ALS
-
- setItemCol(String) - Method in class org.apache.spark.ml.recommendation.ALSModel
-
- setIterations(int) - Method in class org.apache.spark.mllib.recommendation.ALS
-
Set the number of iterations to run.
- setJars(Seq<String>) - Method in class org.apache.spark.SparkConf
-
Set JAR files to distribute to the cluster.
- setJars(String[]) - Method in class org.apache.spark.SparkConf
-
Set JAR files to distribute to the cluster.
- setJavaHome(String) - Method in class org.apache.spark.launcher.SparkLauncher
-
Set a custom JAVA_HOME for launching the Spark application.
- setJobDescription(String) - Method in class org.apache.spark.SparkContext
-
Set a human readable description of the current job.
- setJobGroup(String, String, boolean) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Assigns a group ID to all the jobs started by this thread until the group ID is set to a
different value or cleared.
- setJobGroup(String, String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Assigns a group ID to all the jobs started by this thread until the group ID is set to a
different value or cleared.
- setJobGroup(String, String, boolean) - Method in class org.apache.spark.SparkContext
-
Assigns a group ID to all the jobs started by this thread until the group ID is set to a
different value or cleared.
- setK(int) - Method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- setK(int) - Method in class org.apache.spark.ml.clustering.GaussianMixture
-
- setK(int) - Method in class org.apache.spark.ml.clustering.KMeans
-
- setK(int) - Method in class org.apache.spark.ml.clustering.LDA
-
- setK(int) - Method in class org.apache.spark.ml.feature.PCA
-
- setK(int) - Method in class org.apache.spark.mllib.clustering.BisectingKMeans
-
Sets the desired number of leaf clusters (default: 4).
- setK(int) - Method in class org.apache.spark.mllib.clustering.GaussianMixture
-
Set the number of Gaussians in the mixture model.
- setK(int) - Method in class org.apache.spark.mllib.clustering.KMeans
-
Set the number of clusters to create (k).
- setK(int) - Method in class org.apache.spark.mllib.clustering.LDA
-
Set the number of topics to infer, i.e., the number of soft cluster centers.
- setK(int) - Method in class org.apache.spark.mllib.clustering.PowerIterationClustering
-
Set the number of clusters.
- setK(int) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
-
Set the number of clusters.
- setKappa(double) - Method in class org.apache.spark.mllib.clustering.OnlineLDAOptimizer
-
Learning rate: exponential decay rate---should be between
(0.5, 1.0] to guarantee asymptotic convergence.
- setKeepLastCheckpoint(boolean) - Method in class org.apache.spark.ml.clustering.LDA
-
- setKeepLastCheckpoint(boolean) - Method in class org.apache.spark.mllib.clustering.EMLDAOptimizer
-
If using checkpointing, this indicates whether to keep the last checkpoint (vs clean up).
- setKeyOrdering(Ordering<K>) - Method in class org.apache.spark.rdd.ShuffledRDD
-
Set key ordering for RDD's shuffle.
- setLabelCol(String) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- setLabelCol(String) - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- setLabelCol(String) - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- setLabelCol(String) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- setLabelCol(String) - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- setLabelCol(String) - Method in class org.apache.spark.ml.classification.OneVsRest
-
- setLabelCol(String) - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- setLabelCol(String) - Method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- setLabelCol(String) - Method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
- setLabelCol(String) - Method in class org.apache.spark.ml.evaluation.RegressionEvaluator
-
- setLabelCol(String) - Method in class org.apache.spark.ml.feature.ChiSqSelector
-
- setLabelCol(String) - Method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
Deprecated.
labelCol is not used by ChiSqSelectorModel. Since 2.0.0.
- setLabelCol(String) - Method in class org.apache.spark.ml.feature.RFormula
-
- setLabelCol(String) - Method in class org.apache.spark.ml.Predictor
-
- setLabelCol(String) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- setLabelCol(String) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- setLabelCol(String) - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- setLabelCol(String) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- setLabelCol(String) - Method in class org.apache.spark.ml.regression.IsotonicRegression
-
- setLabelCol(String) - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- setLabelCol(String) - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- setLabels(String[]) - Method in class org.apache.spark.ml.feature.IndexToString
-
- setLambda(double) - Method in class org.apache.spark.mllib.classification.NaiveBayes
-
Set the smoothing parameter.
- setLambda(double) - Method in class org.apache.spark.mllib.recommendation.ALS
-
Set the regularization parameter, lambda.
- setLayers(int[]) - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
Sets the value of param layers.
- setLearningDecay(double) - Method in class org.apache.spark.ml.clustering.LDA
-
- setLearningOffset(double) - Method in class org.apache.spark.ml.clustering.LDA
-
- setLearningRate(double) - Method in class org.apache.spark.mllib.feature.Word2Vec
-
Sets initial learning rate (default: 0.025).
- setLearningRate(double) - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- setLink(String) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
Sets the value of param link.
- setLinkPredictionCol(String) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
Sets the link prediction (linear predictor) column name.
- setLinkPredictionCol(String) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
Sets the link prediction (linear predictor) column name.
- setLocalProperty(String, String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Set a local property that affects jobs submitted from this thread, and all child
threads, such as the Spark fair scheduler pool.
- setLocalProperty(String, String) - Method in class org.apache.spark.SparkContext
-
Set a local property that affects jobs submitted from this thread, such as the Spark fair
scheduler pool.
- setLogLevel(String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
Control our logLevel.
- setLogLevel(String) - Method in class org.apache.spark.SparkContext
-
Control our logLevel.
- setLogLevel(Level) - Static method in class org.apache.spark.util.Utils
-
configure a new log4j level
- setLoss(Loss) - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- setLossType(String) - Method in class org.apache.spark.ml.classification.GBTClassifier
-
- setLossType(String) - Method in class org.apache.spark.ml.regression.GBTRegressor
-
- setMainClass(String) - Method in class org.apache.spark.launcher.SparkLauncher
-
Sets the application class name for Java/Scala applications.
- setMapSideCombine(boolean) - Method in class org.apache.spark.rdd.ShuffledRDD
-
Set mapSideCombine flag for RDD's shuffle.
- setMaster(String) - Method in class org.apache.spark.launcher.SparkLauncher
-
Set the Spark master for the application.
- setMaster(String) - Method in class org.apache.spark.SparkConf
-
The master URL to connect to, such as "local" to run locally with one thread, "local[4]" to
run locally with 4 cores, or "spark://master:7077" to run on a Spark standalone cluster.
- setMax(double) - Method in class org.apache.spark.ml.feature.MinMaxScaler
-
- setMax(double) - Method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- setMaxBins(int) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- setMaxBins(int) - Method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- setMaxBins(int) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- setMaxBins(int) - Method in class org.apache.spark.ml.classification.GBTClassifier
-
- setMaxBins(int) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- setMaxBins(int) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- setMaxBins(int) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- setMaxBins(int) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- setMaxBins(int) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- setMaxBins(int) - Method in class org.apache.spark.ml.regression.GBTRegressor
-
- setMaxBins(int) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- setMaxBins(int) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- setMaxBins(int) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- setMaxCategories(int) - Method in class org.apache.spark.ml.feature.VectorIndexer
-
- setMaxDepth(int) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- setMaxDepth(int) - Method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- setMaxDepth(int) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- setMaxDepth(int) - Method in class org.apache.spark.ml.classification.GBTClassifier
-
- setMaxDepth(int) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- setMaxDepth(int) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- setMaxDepth(int) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- setMaxDepth(int) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- setMaxDepth(int) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- setMaxDepth(int) - Method in class org.apache.spark.ml.regression.GBTRegressor
-
- setMaxDepth(int) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- setMaxDepth(int) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- setMaxDepth(int) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- setMaxIter(int) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- setMaxIter(int) - Method in class org.apache.spark.ml.classification.GBTClassifier
-
- setMaxIter(int) - Method in class org.apache.spark.ml.classification.LogisticRegression
-
Set the maximum number of iterations.
- setMaxIter(int) - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
Set the maximum number of iterations.
- setMaxIter(int) - Method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- setMaxIter(int) - Method in class org.apache.spark.ml.clustering.GaussianMixture
-
- setMaxIter(int) - Method in class org.apache.spark.ml.clustering.KMeans
-
- setMaxIter(int) - Method in class org.apache.spark.ml.clustering.LDA
-
- setMaxIter(int) - Method in class org.apache.spark.ml.feature.Word2Vec
-
- setMaxIter(int) - Method in class org.apache.spark.ml.recommendation.ALS
-
- setMaxIter(int) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
Set the maximum number of iterations.
- setMaxIter(int) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- setMaxIter(int) - Method in class org.apache.spark.ml.regression.GBTRegressor
-
- setMaxIter(int) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
Sets the maximum number of iterations (applicable for solver "irls").
- setMaxIter(int) - Method in class org.apache.spark.ml.regression.LinearRegression
-
Set the maximum number of iterations.
- setMaxIterations(int) - Method in class org.apache.spark.mllib.clustering.BisectingKMeans
-
Sets the max number of k-means iterations to split clusters (default: 20).
- setMaxIterations(int) - Method in class org.apache.spark.mllib.clustering.GaussianMixture
-
Set the maximum number of iterations allowed.
- setMaxIterations(int) - Method in class org.apache.spark.mllib.clustering.KMeans
-
Set maximum number of iterations allowed.
- setMaxIterations(int) - Method in class org.apache.spark.mllib.clustering.LDA
-
Set the maximum number of iterations allowed.
- setMaxIterations(int) - Method in class org.apache.spark.mllib.clustering.PowerIterationClustering
-
Set maximum number of iterations of the power iteration loop
- setMaxLocalProjDBSize(long) - Method in class org.apache.spark.mllib.fpm.PrefixSpan
-
Sets the maximum number of items (including delimiters used in the internal storage format)
allowed in a projected database before local processing (default: 32000000L).
- setMaxMemoryInMB(int) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- setMaxMemoryInMB(int) - Method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- setMaxMemoryInMB(int) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- setMaxMemoryInMB(int) - Method in class org.apache.spark.ml.classification.GBTClassifier
-
- setMaxMemoryInMB(int) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- setMaxMemoryInMB(int) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- setMaxMemoryInMB(int) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- setMaxMemoryInMB(int) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- setMaxMemoryInMB(int) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- setMaxMemoryInMB(int) - Method in class org.apache.spark.ml.regression.GBTRegressor
-
- setMaxMemoryInMB(int) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- setMaxMemoryInMB(int) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- setMaxMemoryInMB(int) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- setMaxPatternLength(int) - Method in class org.apache.spark.mllib.fpm.PrefixSpan
-
Sets maximal pattern length (default: 10).
- setMaxSentenceLength(int) - Method in class org.apache.spark.ml.feature.Word2Vec
-
- setMaxSentenceLength(int) - Method in class org.apache.spark.mllib.feature.Word2Vec
-
Sets the maximum length (in words) of each sentence in the input data.
- setMetricName(String) - Method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- setMetricName(String) - Method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
- setMetricName(String) - Method in class org.apache.spark.ml.evaluation.RegressionEvaluator
-
- setMin(double) - Method in class org.apache.spark.ml.feature.MinMaxScaler
-
- setMin(double) - Method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- setMinConfidence(double) - Method in class org.apache.spark.mllib.fpm.AssociationRules
-
Sets the minimal confidence (default: 0.8).
- setMinCount(int) - Method in class org.apache.spark.ml.feature.Word2Vec
-
- setMinCount(int) - Method in class org.apache.spark.mllib.feature.Word2Vec
-
Sets minCount, the minimum number of times a token must appear to be included in the word2vec
model's vocabulary (default: 5).
- setMinDF(double) - Method in class org.apache.spark.ml.feature.CountVectorizer
-
- setMinDivisibleClusterSize(double) - Method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- setMinDivisibleClusterSize(double) - Method in class org.apache.spark.mllib.clustering.BisectingKMeans
-
Sets the minimum number of points (if >= 1.0) or the minimum proportion of points
(if < 1.0) of a divisible cluster (default: 1).
- setMinDocFreq(int) - Method in class org.apache.spark.ml.feature.IDF
-
- setMiniBatchFraction(double) - Method in class org.apache.spark.mllib.classification.StreamingLogisticRegressionWithSGD
-
Set the fraction of each batch to use for updates.
- setMiniBatchFraction(double) - Method in class org.apache.spark.mllib.clustering.OnlineLDAOptimizer
-
Mini-batch fraction in (0, 1], which sets the fraction of document sampled and used in
each iteration.
- setMiniBatchFraction(double) - Method in class org.apache.spark.mllib.optimization.GradientDescent
-
Set fraction of data to be used for each SGD iteration.
- setMiniBatchFraction(double) - Method in class org.apache.spark.mllib.regression.StreamingLinearRegressionWithSGD
-
Set the fraction of each batch to use for updates.
- setMinInfoGain(double) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- setMinInfoGain(double) - Method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- setMinInfoGain(double) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- setMinInfoGain(double) - Method in class org.apache.spark.ml.classification.GBTClassifier
-
- setMinInfoGain(double) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- setMinInfoGain(double) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- setMinInfoGain(double) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- setMinInfoGain(double) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- setMinInfoGain(double) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- setMinInfoGain(double) - Method in class org.apache.spark.ml.regression.GBTRegressor
-
- setMinInfoGain(double) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- setMinInfoGain(double) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- setMinInfoGain(double) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- setMinInstancesPerNode(int) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- setMinInstancesPerNode(int) - Method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- setMinInstancesPerNode(int) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- setMinInstancesPerNode(int) - Method in class org.apache.spark.ml.classification.GBTClassifier
-
- setMinInstancesPerNode(int) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- setMinInstancesPerNode(int) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- setMinInstancesPerNode(int) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- setMinInstancesPerNode(int) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- setMinInstancesPerNode(int) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- setMinInstancesPerNode(int) - Method in class org.apache.spark.ml.regression.GBTRegressor
-
- setMinInstancesPerNode(int) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- setMinInstancesPerNode(int) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- setMinInstancesPerNode(int) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- setMinSupport(double) - Method in class org.apache.spark.mllib.fpm.FPGrowth
-
Sets the minimal support level (default: 0.3).
- setMinSupport(double) - Method in class org.apache.spark.mllib.fpm.PrefixSpan
-
Sets the minimal support level (default: 0.1).
- setMinTF(double) - Method in class org.apache.spark.ml.feature.CountVectorizer
-
- setMinTF(double) - Method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- setMinTokenLength(int) - Method in class org.apache.spark.ml.feature.RegexTokenizer
-
- setModelType(String) - Method in class org.apache.spark.ml.classification.NaiveBayes
-
Set the model type using a string (case-sensitive).
- setModelType(String) - Method in class org.apache.spark.mllib.classification.NaiveBayes
-
Set the model type using a string (case-sensitive).
- setN(int) - Method in class org.apache.spark.ml.feature.NGram
-
- setName(String) - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Assign a name to this RDD
- setName(String) - Method in class org.apache.spark.api.java.JavaPairRDD
-
Assign a name to this RDD
- setName(String) - Method in class org.apache.spark.api.java.JavaRDD
-
Assign a name to this RDD
- setName(String) - Static method in class org.apache.spark.api.r.RRDD
-
- setName(String) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- setName(String) - Method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- setName(String) - Method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- setName(String) - Static method in class org.apache.spark.graphx.VertexRDD
-
- setName(String) - Static method in class org.apache.spark.rdd.HadoopRDD
-
- setName(String) - Static method in class org.apache.spark.rdd.JdbcRDD
-
- setName(String) - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- setName(String) - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- setName(String) - Method in class org.apache.spark.rdd.RDD
-
Assign a name to this RDD
- setName(String) - Static method in class org.apache.spark.rdd.UnionRDD
-
- setNames(String[]) - Method in class org.apache.spark.ml.feature.VectorSlicer
-
- setNonnegative(boolean) - Method in class org.apache.spark.ml.recommendation.ALS
-
- setNonnegative(boolean) - Method in class org.apache.spark.mllib.recommendation.ALS
-
Set whether the least-squares problems solved at each iteration should have
nonnegativity constraints.
- setNumBlocks(int) - Method in class org.apache.spark.ml.recommendation.ALS
-
Sets both numUserBlocks and numItemBlocks to the specific value.
- setNumBuckets(int) - Method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- setNumClasses(int) - Method in class org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS
-
Set the number of possible outcomes for k classes classification problem in
Multinomial Logistic Regression.
- setNumClasses(int) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- setNumCorrections(int) - Method in class org.apache.spark.mllib.optimization.LBFGS
-
Set the number of corrections used in the LBFGS update.
- setNumFeatures(int) - Method in class org.apache.spark.ml.feature.HashingTF
-
- setNumFolds(int) - Method in class org.apache.spark.ml.tuning.CrossValidator
-
- setNumItemBlocks(int) - Method in class org.apache.spark.ml.recommendation.ALS
-
- setNumIterations(int) - Method in class org.apache.spark.mllib.classification.StreamingLogisticRegressionWithSGD
-
Set the number of iterations of gradient descent to run per update.
- setNumIterations(int) - Method in class org.apache.spark.mllib.feature.Word2Vec
-
Sets number of iterations (default: 1), which should be smaller than or equal to number of
partitions.
- setNumIterations(int) - Method in class org.apache.spark.mllib.optimization.GradientDescent
-
Set the number of iterations for SGD.
- setNumIterations(int) - Method in class org.apache.spark.mllib.optimization.LBFGS
-
Set the maximal number of iterations for L-BFGS.
- setNumIterations(int) - Method in class org.apache.spark.mllib.regression.StreamingLinearRegressionWithSGD
-
Set the number of iterations of gradient descent to run per update.
- setNumIterations(int) - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- setNumPartitions(int) - Method in class org.apache.spark.ml.feature.Word2Vec
-
- setNumPartitions(int) - Method in class org.apache.spark.mllib.feature.Word2Vec
-
Sets number of partitions (default: 1).
- setNumPartitions(int) - Method in class org.apache.spark.mllib.fpm.FPGrowth
-
Sets the number of partitions used by parallel FP-growth (default: same as input data).
- setNumTopFeatures(int) - Method in class org.apache.spark.ml.feature.ChiSqSelector
-
- setNumTrees(int) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- setNumTrees(int) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- setNumUserBlocks(int) - Method in class org.apache.spark.ml.recommendation.ALS
-
- setOptimizeDocConcentration(boolean) - Method in class org.apache.spark.ml.clustering.LDA
-
- setOptimizeDocConcentration(boolean) - Method in class org.apache.spark.mllib.clustering.OnlineLDAOptimizer
-
Sets whether to optimize docConcentration parameter during training.
- setOptimizer(String) - Method in class org.apache.spark.ml.clustering.LDA
-
- setOptimizer(LDAOptimizer) - Method in class org.apache.spark.mllib.clustering.LDA
-
:: DeveloperApi ::
- setOptimizer(String) - Method in class org.apache.spark.mllib.clustering.LDA
-
Set the LDAOptimizer used to perform the actual calculation by algorithm name.
- setOrNull(long, int, int) - Method in class org.apache.spark.sql.types.Decimal
-
Set this Decimal to the given unscaled Long, with a given precision and scale,
and return it, or return null if it cannot be set due to overflow.
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.Binarizer
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.Bucketizer
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.ChiSqSelector
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.CountVectorizer
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- setOutputCol(String) - Static method in class org.apache.spark.ml.feature.DCT
-
- setOutputCol(String) - Static method in class org.apache.spark.ml.feature.ElementwiseProduct
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.HashingTF
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.IDF
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.IDFModel
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.IndexToString
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.Interaction
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.MaxAbsScaler
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.MinMaxScaler
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- setOutputCol(String) - Static method in class org.apache.spark.ml.feature.NGram
-
- setOutputCol(String) - Static method in class org.apache.spark.ml.feature.Normalizer
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.OneHotEncoder
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.PCA
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.PCAModel
-
- setOutputCol(String) - Static method in class org.apache.spark.ml.feature.PolynomialExpansion
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- setOutputCol(String) - Static method in class org.apache.spark.ml.feature.RegexTokenizer
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.StandardScaler
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.StandardScalerModel
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.StopWordsRemover
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.StringIndexer
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.StringIndexerModel
-
- setOutputCol(String) - Static method in class org.apache.spark.ml.feature.Tokenizer
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.VectorAssembler
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.VectorIndexer
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.VectorSlicer
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.Word2Vec
-
- setOutputCol(String) - Method in class org.apache.spark.ml.feature.Word2VecModel
-
- setOutputCol(String) - Method in class org.apache.spark.ml.UnaryTransformer
-
- setP(double) - Method in class org.apache.spark.ml.feature.Normalizer
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.clustering.BisectingKMeansModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.feature.Bucketizer
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.feature.CountVectorizerModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.feature.IDFModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.feature.PCAModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.feature.StandardScalerModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.feature.StringIndexerModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- setParent(Estimator<M>) - Method in class org.apache.spark.ml.Model
-
Sets the parent of this model (Java API).
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.PipelineModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.recommendation.ALSModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- setParent(Estimator<M>) - Static method in class org.apache.spark.ml.tuning.TrainValidationSplitModel
-
- setPattern(String) - Method in class org.apache.spark.ml.feature.RegexTokenizer
-
- setPeacePeriod(int) - Method in class org.apache.spark.mllib.stat.test.StreamingTest
-
Set the number of initial batches to ignore.
- setPredictionCol(String) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- setPredictionCol(String) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- setPredictionCol(String) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- setPredictionCol(String) - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- setPredictionCol(String) - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- setPredictionCol(String) - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- setPredictionCol(String) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- setPredictionCol(String) - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- setPredictionCol(String) - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- setPredictionCol(String) - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- setPredictionCol(String) - Method in class org.apache.spark.ml.classification.OneVsRest
-
- setPredictionCol(String) - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- setPredictionCol(String) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- setPredictionCol(String) - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- setPredictionCol(String) - Method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- setPredictionCol(String) - Method in class org.apache.spark.ml.clustering.GaussianMixture
-
- setPredictionCol(String) - Method in class org.apache.spark.ml.clustering.KMeans
-
- setPredictionCol(String) - Method in class org.apache.spark.ml.clustering.KMeansModel
-
- setPredictionCol(String) - Method in class org.apache.spark.ml.evaluation.MulticlassClassificationEvaluator
-
- setPredictionCol(String) - Method in class org.apache.spark.ml.evaluation.RegressionEvaluator
-
- setPredictionCol(String) - Method in class org.apache.spark.ml.PredictionModel
-
- setPredictionCol(String) - Method in class org.apache.spark.ml.Predictor
-
- setPredictionCol(String) - Method in class org.apache.spark.ml.recommendation.ALS
-
- setPredictionCol(String) - Method in class org.apache.spark.ml.recommendation.ALSModel
-
- setPredictionCol(String) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- setPredictionCol(String) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- setPredictionCol(String) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- setPredictionCol(String) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- setPredictionCol(String) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- setPredictionCol(String) - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- setPredictionCol(String) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- setPredictionCol(String) - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- setPredictionCol(String) - Method in class org.apache.spark.ml.regression.IsotonicRegression
-
- setPredictionCol(String) - Method in class org.apache.spark.ml.regression.IsotonicRegressionModel
-
- setPredictionCol(String) - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- setPredictionCol(String) - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- setPredictionCol(String) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- setPredictionCol(String) - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- setProbabilityCol(String) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- setProbabilityCol(String) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- setProbabilityCol(String) - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- setProbabilityCol(String) - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- setProbabilityCol(String) - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- setProbabilityCol(String) - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- setProbabilityCol(String) - Method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- setProbabilityCol(String) - Method in class org.apache.spark.ml.classification.ProbabilisticClassifier
-
- setProbabilityCol(String) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- setProbabilityCol(String) - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- setProbabilityCol(String) - Method in class org.apache.spark.ml.clustering.GaussianMixture
-
- setProductBlocks(int) - Method in class org.apache.spark.mllib.recommendation.ALS
-
Set the number of product blocks to parallelize the computation.
- setPropertiesFile(String) - Method in class org.apache.spark.launcher.SparkLauncher
-
Set a custom properties file with Spark configuration for the application.
- setQuantileCalculationStrategy(Enumeration.Value) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- setQuantileProbabilities(double[]) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- setQuantileProbabilities(double[]) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- setQuantilesCol(String) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- setQuantilesCol(String) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- setRandomCenters(int, double, long) - Method in class org.apache.spark.mllib.clustering.StreamingKMeans
-
Initialize random centers, requiring only the number of dimensions.
- setRank(int) - Method in class org.apache.spark.ml.recommendation.ALS
-
- setRank(int) - Method in class org.apache.spark.mllib.recommendation.ALS
-
Set the rank of the feature matrices computed (number of features).
- setRatingCol(String) - Method in class org.apache.spark.ml.recommendation.ALS
-
- setRawPredictionCol(String) - Method in class org.apache.spark.ml.classification.ClassificationModel
-
- setRawPredictionCol(String) - Method in class org.apache.spark.ml.classification.Classifier
-
- setRawPredictionCol(String) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- setRawPredictionCol(String) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- setRawPredictionCol(String) - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- setRawPredictionCol(String) - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- setRawPredictionCol(String) - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- setRawPredictionCol(String) - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- setRawPredictionCol(String) - Static method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- setRawPredictionCol(String) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- setRawPredictionCol(String) - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- setRawPredictionCol(String) - Method in class org.apache.spark.ml.evaluation.BinaryClassificationEvaluator
-
- setRegParam(double) - Method in class org.apache.spark.ml.classification.LogisticRegression
-
Set the regularization parameter.
- setRegParam(double) - Method in class org.apache.spark.ml.recommendation.ALS
-
- setRegParam(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
Sets the regularization parameter for L2 regularization.
- setRegParam(double) - Method in class org.apache.spark.ml.regression.LinearRegression
-
Set the regularization parameter.
- setRegParam(double) - Method in class org.apache.spark.mllib.classification.StreamingLogisticRegressionWithSGD
-
Set the regularization parameter.
- setRegParam(double) - Method in class org.apache.spark.mllib.optimization.GradientDescent
-
Set the regularization parameter.
- setRegParam(double) - Method in class org.apache.spark.mllib.optimization.LBFGS
-
Set the regularization parameter.
- setRegParam(double) - Method in class org.apache.spark.mllib.regression.StreamingLinearRegressionWithSGD
-
Set the regularization parameter.
- setRelativeError(double) - Method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- setRequiredColumns(Configuration, StructType, StructType) - Static method in class org.apache.spark.sql.hive.orc.OrcRelation
-
- setRest(long, int, VD, ED) - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
-
- setRuns(int) - Method in class org.apache.spark.mllib.clustering.KMeans
-
This function has no effect since Spark 2.0.0.
- setSample(RDD<Object>) - Method in class org.apache.spark.mllib.stat.KernelDensity
-
Sets the sample to use for density estimation.
- setSample(JavaRDD<Double>) - Method in class org.apache.spark.mllib.stat.KernelDensity
-
Sets the sample to use for density estimation (for Java users).
- setScalingVec(Vector) - Method in class org.apache.spark.ml.feature.ElementwiseProduct
-
- setSeed(long) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- setSeed(long) - Method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- setSeed(long) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- setSeed(long) - Method in class org.apache.spark.ml.classification.GBTClassifier
-
- setSeed(long) - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
Set the seed for weights initialization if weights are not set
- setSeed(long) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- setSeed(long) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- setSeed(long) - Method in class org.apache.spark.ml.clustering.BisectingKMeans
-
- setSeed(long) - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- setSeed(long) - Method in class org.apache.spark.ml.clustering.GaussianMixture
-
- setSeed(long) - Method in class org.apache.spark.ml.clustering.KMeans
-
- setSeed(long) - Method in class org.apache.spark.ml.clustering.LDA
-
- setSeed(long) - Method in class org.apache.spark.ml.clustering.LDAModel
-
- setSeed(long) - Static method in class org.apache.spark.ml.clustering.LocalLDAModel
-
- setSeed(long) - Method in class org.apache.spark.ml.feature.Word2Vec
-
- setSeed(long) - Method in class org.apache.spark.ml.recommendation.ALS
-
- setSeed(long) - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- setSeed(long) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- setSeed(long) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- setSeed(long) - Method in class org.apache.spark.ml.regression.GBTRegressor
-
- setSeed(long) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- setSeed(long) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- setSeed(long) - Method in class org.apache.spark.ml.tuning.CrossValidator
-
- setSeed(long) - Method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- setSeed(long) - Method in class org.apache.spark.mllib.clustering.BisectingKMeans
-
Sets the random seed (default: hash value of the class name).
- setSeed(long) - Method in class org.apache.spark.mllib.clustering.GaussianMixture
-
Set the random seed
- setSeed(long) - Method in class org.apache.spark.mllib.clustering.KMeans
-
Set the random seed for cluster initialization.
- setSeed(long) - Method in class org.apache.spark.mllib.clustering.LDA
-
Set the random seed for cluster initialization.
- setSeed(long) - Method in class org.apache.spark.mllib.feature.Word2Vec
-
Sets random seed (default: a random long integer).
- setSeed(long) - Method in class org.apache.spark.mllib.random.ExponentialGenerator
-
- setSeed(long) - Method in class org.apache.spark.mllib.random.GammaGenerator
-
- setSeed(long) - Method in class org.apache.spark.mllib.random.LogNormalGenerator
-
- setSeed(long) - Method in class org.apache.spark.mllib.random.PoissonGenerator
-
- setSeed(long) - Method in class org.apache.spark.mllib.random.StandardNormalGenerator
-
- setSeed(long) - Method in class org.apache.spark.mllib.random.UniformGenerator
-
- setSeed(long) - Method in class org.apache.spark.mllib.random.WeibullGenerator
-
- setSeed(long) - Method in class org.apache.spark.mllib.recommendation.ALS
-
Sets a random seed to have deterministic results.
- setSeed(long) - Method in class org.apache.spark.util.random.BernoulliCellSampler
-
- setSeed(long) - Method in class org.apache.spark.util.random.BernoulliSampler
-
- setSeed(long) - Method in class org.apache.spark.util.random.PoissonSampler
-
- setSeed(long) - Method in interface org.apache.spark.util.random.Pseudorandom
-
Set random seed.
- setSerializer(Serializer) - Method in class org.apache.spark.rdd.CoGroupedRDD
-
Set a serializer for this RDD's shuffle, or null to use the default (spark.serializer)
- setSerializer(Serializer) - Method in class org.apache.spark.rdd.ShuffledRDD
-
Set a serializer for this RDD's shuffle, or null to use the default (spark.serializer)
- setSmoothing(double) - Method in class org.apache.spark.ml.classification.NaiveBayes
-
Set the smoothing parameter.
- setSolver(String) - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
Sets the value of param solver.
- setSolver(String) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
Sets the solver algorithm used for optimization.
- setSolver(String) - Method in class org.apache.spark.ml.regression.LinearRegression
-
Set the solver algorithm used for optimization.
- setSparkContextSessionConf(SparkSession, Map<Object, Object>) - Static method in class org.apache.spark.sql.api.r.SQLUtils
-
- setSparkHome(String) - Method in class org.apache.spark.launcher.SparkLauncher
-
Set a custom Spark installation location for the application.
- setSparkHome(String) - Method in class org.apache.spark.SparkConf
-
Set the location where Spark is installed on worker nodes.
- setSplits(double[]) - Method in class org.apache.spark.ml.feature.Bucketizer
-
- setSrcOnly(long, int, VD) - Method in class org.apache.spark.graphx.impl.AggregatingEdgeContext
-
- setStackTrace(StackTraceElement[]) - Static method in exception org.apache.spark.sql.AnalysisException
-
- setStackTrace(StackTraceElement[]) - Static method in exception org.apache.spark.sql.streaming.StreamingQueryException
-
- setStages(PipelineStage[]) - Method in class org.apache.spark.ml.Pipeline
-
- setStandardization(boolean) - Method in class org.apache.spark.ml.classification.LogisticRegression
-
Whether to standardize the training features before fitting the model.
- setStandardization(boolean) - Method in class org.apache.spark.ml.regression.LinearRegression
-
Whether to standardize the training features before fitting the model.
- setStatement(String) - Method in class org.apache.spark.ml.feature.SQLTransformer
-
- setStepSize(double) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- setStepSize(double) - Method in class org.apache.spark.ml.classification.GBTClassifier
-
- setStepSize(double) - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
Sets the value of param stepSize (applicable only for solver "gd").
- setStepSize(double) - Method in class org.apache.spark.ml.feature.Word2Vec
-
- setStepSize(double) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- setStepSize(double) - Method in class org.apache.spark.ml.regression.GBTRegressor
-
- setStepSize(double) - Method in class org.apache.spark.mllib.classification.StreamingLogisticRegressionWithSGD
-
Set the step size for gradient descent.
- setStepSize(double) - Method in class org.apache.spark.mllib.optimization.GradientDescent
-
Set the initial step size of SGD for the first step.
- setStepSize(double) - Method in class org.apache.spark.mllib.regression.StreamingLinearRegressionWithSGD
-
Set the step size for gradient descent.
- setStopWords(String[]) - Method in class org.apache.spark.ml.feature.StopWordsRemover
-
- setSubsamplingRate(double) - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- setSubsamplingRate(double) - Method in class org.apache.spark.ml.classification.GBTClassifier
-
- setSubsamplingRate(double) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- setSubsamplingRate(double) - Method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- setSubsamplingRate(double) - Method in class org.apache.spark.ml.clustering.LDA
-
- setSubsamplingRate(double) - Static method in class org.apache.spark.ml.regression.GBTRegressionModel
-
- setSubsamplingRate(double) - Method in class org.apache.spark.ml.regression.GBTRegressor
-
- setSubsamplingRate(double) - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- setSubsamplingRate(double) - Method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- setSubsamplingRate(double) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- setTau0(double) - Method in class org.apache.spark.mllib.clustering.OnlineLDAOptimizer
-
A (positive) learning parameter that downweights early iterations.
- setTestMethod(String) - Method in class org.apache.spark.mllib.stat.test.StreamingTest
-
Set the statistical method used for significance testing.
- setThreshold(double) - Method in class org.apache.spark.ml.classification.LogisticRegression
-
- setThreshold(double) - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- setThreshold(double) - Method in class org.apache.spark.ml.feature.Binarizer
-
- setThreshold(double) - Method in class org.apache.spark.mllib.classification.LogisticRegressionModel
-
Sets the threshold that separates positive predictions from negative predictions
in Binary Logistic Regression.
- setThreshold(double) - Method in class org.apache.spark.mllib.classification.SVMModel
-
Sets the threshold that separates positive predictions from negative predictions.
- setThresholds(double[]) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassificationModel
-
- setThresholds(double[]) - Static method in class org.apache.spark.ml.classification.DecisionTreeClassifier
-
- setThresholds(double[]) - Method in class org.apache.spark.ml.classification.LogisticRegression
-
- setThresholds(double[]) - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- setThresholds(double[]) - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- setThresholds(double[]) - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- setThresholds(double[]) - Method in class org.apache.spark.ml.classification.ProbabilisticClassificationModel
-
- setThresholds(double[]) - Method in class org.apache.spark.ml.classification.ProbabilisticClassifier
-
- setThresholds(double[]) - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- setThresholds(double[]) - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- setTol(double) - Method in class org.apache.spark.ml.classification.LogisticRegression
-
Set the convergence tolerance of iterations.
- setTol(double) - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
Set the convergence tolerance of iterations.
- setTol(double) - Method in class org.apache.spark.ml.clustering.GaussianMixture
-
- setTol(double) - Method in class org.apache.spark.ml.clustering.KMeans
-
- setTol(double) - Method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
Set the convergence tolerance of iterations.
- setTol(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
Sets the convergence tolerance of iterations.
- setTol(double) - Method in class org.apache.spark.ml.regression.LinearRegression
-
Set the convergence tolerance of iterations.
- setToLowercase(boolean) - Method in class org.apache.spark.ml.feature.RegexTokenizer
-
- setTopicConcentration(double) - Method in class org.apache.spark.ml.clustering.LDA
-
- setTopicConcentration(double) - Method in class org.apache.spark.mllib.clustering.LDA
-
Concentration parameter (commonly named "beta" or "eta") for the prior placed on topics'
distributions over terms.
- setTopicDistributionCol(String) - Method in class org.apache.spark.ml.clustering.LDA
-
- setTrainRatio(double) - Method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- setTreeStrategy(Strategy) - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- setupContainerBuilderDockerInfo(String, SparkConf, Protos.ContainerInfo.Builder) - Static method in class org.apache.spark.scheduler.cluster.mesos.MesosSchedulerBackendUtil
-
Setup a docker containerizer
- setUpdater(Updater) - Method in class org.apache.spark.mllib.optimization.GradientDescent
-
Set the updater function to actually perform a gradient step in a given direction.
- setUpdater(Updater) - Method in class org.apache.spark.mllib.optimization.LBFGS
-
Set the updater function to actually perform a gradient step in a given direction.
- setupGroups(int, DefaultPartitionCoalescer.PartitionLocations) - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
-
Initializes targetLen partition groups.
- setupSecureURLConnection(URLConnection, org.apache.spark.SecurityManager) - Static method in class org.apache.spark.util.Utils
-
If the given URL connection is HttpsURLConnection, it sets the SSL socket factory and
the host verifier from the given security manager.
- setUseNodeIdCache(boolean) - Method in class org.apache.spark.mllib.tree.configuration.Strategy
-
- setUserBlocks(int) - Method in class org.apache.spark.mllib.recommendation.ALS
-
Set the number of user blocks to parallelize the computation.
- setUserCol(String) - Method in class org.apache.spark.ml.recommendation.ALS
-
- setUserCol(String) - Method in class org.apache.spark.ml.recommendation.ALSModel
-
- setValidateData(boolean) - Static method in class org.apache.spark.mllib.classification.LogisticRegressionWithSGD
-
- setValidateData(boolean) - Static method in class org.apache.spark.mllib.classification.SVMWithSGD
-
- setValidateData(boolean) - Method in class org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm
-
Set if the algorithm should validate data before training.
- setValidateData(boolean) - Static method in class org.apache.spark.mllib.regression.LassoWithSGD
-
- setValidateData(boolean) - Static method in class org.apache.spark.mllib.regression.LinearRegressionWithSGD
-
- setValidateData(boolean) - Static method in class org.apache.spark.mllib.regression.RidgeRegressionWithSGD
-
- setValidationTol(double) - Method in class org.apache.spark.mllib.tree.configuration.BoostingStrategy
-
- setValue(R) - Method in class org.apache.spark.Accumulable
-
Deprecated.
Set the accumulator's value.
- setValue(R) - Static method in class org.apache.spark.Accumulator
-
Deprecated.
- setVarianceCol(String) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- setVarianceCol(String) - Method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- setVectorSize(int) - Method in class org.apache.spark.ml.feature.Word2Vec
-
- setVectorSize(int) - Method in class org.apache.spark.mllib.feature.Word2Vec
-
Sets vector size (default: 100).
- setVerbose(boolean) - Method in class org.apache.spark.launcher.SparkLauncher
-
Enables verbose reporting for SparkSubmit.
- setVocabSize(int) - Method in class org.apache.spark.ml.feature.CountVectorizer
-
- setWeightCol(String) - Method in class org.apache.spark.ml.classification.LogisticRegression
-
Whether to over-/under-sample training instances according to the given weights in weightCol.
- setWeightCol(String) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
Sets the value of param weightCol.
- setWeightCol(String) - Method in class org.apache.spark.ml.regression.IsotonicRegression
-
- setWeightCol(String) - Method in class org.apache.spark.ml.regression.LinearRegression
-
Whether to over-/under-sample training instances according to the given weights in weightCol.
- setWindowSize(int) - Method in class org.apache.spark.ml.feature.Word2Vec
-
- setWindowSize(int) - Method in class org.apache.spark.mllib.feature.Word2Vec
-
Sets the window of words (default: 5)
- setWindowSize(int) - Method in class org.apache.spark.mllib.stat.test.StreamingTest
-
Set the number of batches to compute significance tests over.
- setWithMean(boolean) - Method in class org.apache.spark.ml.feature.StandardScaler
-
- setWithMean(boolean) - Method in class org.apache.spark.mllib.feature.StandardScalerModel
-
:: DeveloperApi ::
- setWithStd(boolean) - Method in class org.apache.spark.ml.feature.StandardScaler
-
- setWithStd(boolean) - Method in class org.apache.spark.mllib.feature.StandardScalerModel
-
:: DeveloperApi ::
- sha1(Column) - Static method in class org.apache.spark.sql.functions
-
Calculates the SHA-1 digest of a binary column and returns the value
as a 40 character hex string.
- sha2(Column, int) - Static method in class org.apache.spark.sql.functions
-
Calculates the SHA-2 family of hash functions of a binary column and
returns the value as a hex string.
- shape() - Method in class org.apache.spark.mllib.random.GammaGenerator
-
- SharedParamsCodeGen - Class in org.apache.spark.ml.param.shared
-
Code generator for shared params (sharedParams.scala).
- SharedParamsCodeGen() - Constructor for class org.apache.spark.ml.param.shared.SharedParamsCodeGen
-
- shiftLeft(Column, int) - Static method in class org.apache.spark.sql.functions
-
Shift the given value numBits left.
- shiftRight(Column, int) - Static method in class org.apache.spark.sql.functions
-
Shift the given value numBits right.
- shiftRightUnsigned(Column, int) - Static method in class org.apache.spark.sql.functions
-
Unsigned shift the given value numBits right.
- SHORT() - Static method in class org.apache.spark.sql.Encoders
-
An encoder for nullable short type.
- ShortestPaths - Class in org.apache.spark.graphx.lib
-
Computes shortest paths to the given set of landmark vertices, returning a graph where each
vertex attribute is a map containing the shortest-path distance to each reachable landmark.
- ShortestPaths() - Constructor for class org.apache.spark.graphx.lib.ShortestPaths
-
- shortName() - Method in class org.apache.spark.sql.hive.orc.OrcFileFormat
-
- shortName() - Method in interface org.apache.spark.sql.sources.DataSourceRegister
-
The string that represents the format that this data source provider uses.
- shortTimeUnitString(TimeUnit) - Static method in class org.apache.spark.streaming.ui.UIUtils
-
Return the short string for a TimeUnit.
- ShortType - Static variable in class org.apache.spark.sql.types.DataTypes
-
Gets the ShortType object.
- ShortType - Class in org.apache.spark.sql.types
-
:: DeveloperApi ::
The data type representing Short values.
- shouldCloseFileAfterWrite(SparkConf, boolean) - Static method in class org.apache.spark.streaming.util.WriteAheadLogUtils
-
- shouldDistributeGaussians(int, int) - Static method in class org.apache.spark.mllib.clustering.GaussianMixture
-
Heuristic to distribute the computation of the MultivariateGaussians, approximately when
d > 25 except for when k is very small.
- shouldGoLeft(Vector) - Method in interface org.apache.spark.ml.tree.Split
-
Return true (split to left) or false (split to right).
- shouldGoLeft(int, Split[]) - Method in interface org.apache.spark.ml.tree.Split
-
Return true (split to left) or false (split to right).
- shouldOwn(Param<?>) - Method in interface org.apache.spark.ml.param.Params
-
Validates that the input param belongs to this instance.
- show(int) - Method in class org.apache.spark.sql.Dataset
-
Displays the Dataset in a tabular form.
- show() - Method in class org.apache.spark.sql.Dataset
-
Displays the top 20 rows of Dataset in a tabular form.
- show(boolean) - Method in class org.apache.spark.sql.Dataset
-
Displays the top 20 rows of Dataset in a tabular form.
- show(int, boolean) - Method in class org.apache.spark.sql.Dataset
-
Displays the Dataset in a tabular form.
- showBytesDistribution(String, Function2<TaskInfo, TaskMetrics, Object>, Seq<Tuple2<TaskInfo, TaskMetrics>>) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- showBytesDistribution(String, Option<org.apache.spark.util.Distribution>) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- showBytesDistribution(String, org.apache.spark.util.Distribution) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- showDagVizForJob(int, Seq<org.apache.spark.ui.scope.RDDOperationGraph>) - Static method in class org.apache.spark.ui.UIUtils
-
Return a "DAG visualization" DOM element that expands into a visualization for a job.
- showDagVizForStage(int, Option<org.apache.spark.ui.scope.RDDOperationGraph>) - Static method in class org.apache.spark.ui.UIUtils
-
Return a "DAG visualization" DOM element that expands into a visualization for a stage.
- showDistribution(String, org.apache.spark.util.Distribution, Function1<Object, String>) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- showDistribution(String, Option<org.apache.spark.util.Distribution>, Function1<Object, String>) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- showDistribution(String, Option<org.apache.spark.util.Distribution>, String) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- showDistribution(String, String, Function2<TaskInfo, TaskMetrics, Object>, Seq<Tuple2<TaskInfo, TaskMetrics>>) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- showMillisDistribution(String, Option<org.apache.spark.util.Distribution>) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- showMillisDistribution(String, Function2<TaskInfo, TaskMetrics, Object>, Seq<Tuple2<TaskInfo, TaskMetrics>>) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- showMillisDistribution(String, Function1<BatchInfo, Option<Object>>) - Method in class org.apache.spark.streaming.scheduler.StatsReportListener
-
- SHUFFLE() - Static method in class org.apache.spark.storage.BlockId
-
- SHUFFLE_DATA() - Static method in class org.apache.spark.storage.BlockId
-
- SHUFFLE_INDEX() - Static method in class org.apache.spark.storage.BlockId
-
- SHUFFLE_READ() - Static method in class org.apache.spark.ui.ToolTips
-
- SHUFFLE_READ_BLOCKED_TIME() - Static method in class org.apache.spark.ui.jobs.TaskDetailsClassNames
-
- SHUFFLE_READ_BLOCKED_TIME() - Static method in class org.apache.spark.ui.ToolTips
-
- SHUFFLE_READ_METRICS_PREFIX() - Static method in class org.apache.spark.InternalAccumulator
-
- SHUFFLE_READ_REMOTE_SIZE() - Static method in class org.apache.spark.ui.jobs.TaskDetailsClassNames
-
- SHUFFLE_READ_REMOTE_SIZE() - Static method in class org.apache.spark.ui.ToolTips
-
- SHUFFLE_WRITE() - Static method in class org.apache.spark.ui.ToolTips
-
- SHUFFLE_WRITE_METRICS_PREFIX() - Static method in class org.apache.spark.InternalAccumulator
-
- ShuffleBlockId - Class in org.apache.spark.storage
-
- ShuffleBlockId(int, int, int) - Constructor for class org.apache.spark.storage.ShuffleBlockId
-
- ShuffleDataBlockId - Class in org.apache.spark.storage
-
- ShuffleDataBlockId(int, int, int) - Constructor for class org.apache.spark.storage.ShuffleDataBlockId
-
- ShuffleDependency<K,V,C> - Class in org.apache.spark
-
:: DeveloperApi ::
Represents a dependency on the output of a shuffle stage.
- ShuffleDependency(RDD<? extends Product2<K, V>>, Partitioner, Serializer, Option<Ordering<K>>, Option<Aggregator<K, V, C>>, boolean, ClassTag<K>, ClassTag<V>, ClassTag<C>) - Constructor for class org.apache.spark.ShuffleDependency
-
- ShuffledRDD<K,V,C> - Class in org.apache.spark.rdd
-
:: DeveloperApi ::
The resulting RDD from a shuffle (e.g.
- ShuffledRDD(RDD<? extends Product2<K, V>>, Partitioner, ClassTag<K>, ClassTag<V>, ClassTag<C>) - Constructor for class org.apache.spark.rdd.ShuffledRDD
-
- shuffleHandle() - Method in class org.apache.spark.ShuffleDependency
-
- shuffleId() - Method in class org.apache.spark.CleanShuffle
-
- shuffleId() - Method in class org.apache.spark.FetchFailed
-
- shuffleId() - Method in class org.apache.spark.ShuffleDependency
-
- shuffleId() - Method in class org.apache.spark.storage.BlockManagerMessages.RemoveShuffle
-
- shuffleId() - Method in class org.apache.spark.storage.ShuffleBlockId
-
- shuffleId() - Method in class org.apache.spark.storage.ShuffleDataBlockId
-
- shuffleId() - Method in class org.apache.spark.storage.ShuffleIndexBlockId
-
- ShuffleIndexBlockId - Class in org.apache.spark.storage
-
- ShuffleIndexBlockId(int, int, int) - Constructor for class org.apache.spark.storage.ShuffleIndexBlockId
-
- shuffleManager() - Method in class org.apache.spark.SparkEnv
-
- shuffleRead() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
-
- shuffleRead() - Method in class org.apache.spark.ui.jobs.UIData.ExecutorSummary
-
- shuffleReadBytes() - Method in class org.apache.spark.status.api.v1.StageData
-
- ShuffleReadMetricDistributions - Class in org.apache.spark.status.api.v1
-
- ShuffleReadMetrics - Class in org.apache.spark.status.api.v1
-
- shuffleReadMetrics() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
-
- shuffleReadMetrics() - Method in class org.apache.spark.status.api.v1.TaskMetrics
-
- shuffleReadMetrics() - Method in class org.apache.spark.ui.jobs.UIData.TaskMetricsUIData
-
- shuffleReadRecords() - Method in class org.apache.spark.status.api.v1.StageData
-
- shuffleReadRecords() - Method in class org.apache.spark.ui.jobs.UIData.ExecutorSummary
-
- shuffleReadRecords() - Method in class org.apache.spark.ui.jobs.UIData.StageUIData
-
- shuffleReadTotalBytes() - Method in class org.apache.spark.ui.jobs.UIData.StageUIData
-
- shuffleRegistered() - Method in class org.apache.spark.scheduler.cluster.mesos.Slave
-
- shuffleWrite() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
-
- shuffleWrite() - Method in class org.apache.spark.ui.jobs.UIData.ExecutorSummary
-
- shuffleWriteBytes() - Method in class org.apache.spark.status.api.v1.StageData
-
- shuffleWriteBytes() - Method in class org.apache.spark.ui.jobs.UIData.StageUIData
-
- ShuffleWriteMetricDistributions - Class in org.apache.spark.status.api.v1
-
- ShuffleWriteMetrics - Class in org.apache.spark.status.api.v1
-
- shuffleWriteMetrics() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
-
- shuffleWriteMetrics() - Method in class org.apache.spark.status.api.v1.TaskMetrics
-
- shuffleWriteMetrics() - Method in class org.apache.spark.ui.jobs.UIData.TaskMetricsUIData
-
- shuffleWriteRecords() - Method in class org.apache.spark.status.api.v1.StageData
-
- shuffleWriteRecords() - Method in class org.apache.spark.ui.jobs.UIData.ExecutorSummary
-
- shuffleWriteRecords() - Method in class org.apache.spark.ui.jobs.UIData.StageUIData
-
- ShutdownHookManager - Class in org.apache.spark.util
-
Various utility methods used by Spark.
- ShutdownHookManager() - Constructor for class org.apache.spark.util.ShutdownHookManager
-
- sigma() - Method in class org.apache.spark.mllib.stat.distribution.MultivariateGaussian
-
- sigmas() - Method in class org.apache.spark.mllib.clustering.ExpectationSum
-
- SignalUtils - Class in org.apache.spark.util
-
Contains utilities for working with posix signals.
- SignalUtils() - Constructor for class org.apache.spark.util.SignalUtils
-
- signum(Column) - Static method in class org.apache.spark.sql.functions
-
Computes the signum of the given value.
- signum(String) - Static method in class org.apache.spark.sql.functions
-
Computes the signum of the given column.
- SimpleFutureAction<T> - Class in org.apache.spark
-
A
FutureAction holding the result of an action that triggers a single job.
- simpleString() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- simpleString() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- simpleString() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformation
-
- simpleString() - Method in class org.apache.spark.sql.types.ArrayType
-
- simpleString() - Static method in class org.apache.spark.sql.types.BinaryType
-
- simpleString() - Static method in class org.apache.spark.sql.types.BooleanType
-
- simpleString() - Method in class org.apache.spark.sql.types.ByteType
-
- simpleString() - Static method in class org.apache.spark.sql.types.CalendarIntervalType
-
- simpleString() - Method in class org.apache.spark.sql.types.DataType
-
Readable string representation for the type.
- simpleString() - Static method in class org.apache.spark.sql.types.DateType
-
- simpleString() - Method in class org.apache.spark.sql.types.DecimalType
-
- simpleString() - Static method in class org.apache.spark.sql.types.DoubleType
-
- simpleString() - Static method in class org.apache.spark.sql.types.FloatType
-
- simpleString() - Method in class org.apache.spark.sql.types.IntegerType
-
- simpleString() - Method in class org.apache.spark.sql.types.LongType
-
- simpleString() - Method in class org.apache.spark.sql.types.MapType
-
- simpleString() - Static method in class org.apache.spark.sql.types.NullType
-
- simpleString() - Method in class org.apache.spark.sql.types.ShortType
-
- simpleString() - Static method in class org.apache.spark.sql.types.StringType
-
- simpleString() - Method in class org.apache.spark.sql.types.StructType
-
- simpleString() - Static method in class org.apache.spark.sql.types.TimestampType
-
- SimpleUpdater - Class in org.apache.spark.mllib.optimization
-
:: DeveloperApi ::
A simple updater for gradient descent *without* any regularization.
- SimpleUpdater() - Constructor for class org.apache.spark.mllib.optimization.SimpleUpdater
-
- sin(Column) - Static method in class org.apache.spark.sql.functions
-
Computes the sine of the given value.
- sin(String) - Static method in class org.apache.spark.sql.functions
-
Computes the sine of the given column.
- SingularValueDecomposition<UType,VType> - Class in org.apache.spark.mllib.linalg
-
Represents singular value decomposition (SVD) factors.
- SingularValueDecomposition(UType, Vector, VType) - Constructor for class org.apache.spark.mllib.linalg.SingularValueDecomposition
-
- sinh(Column) - Static method in class org.apache.spark.sql.functions
-
Computes the hyperbolic sine of the given value.
- sinh(String) - Static method in class org.apache.spark.sql.functions
-
Computes the hyperbolic sine of the given column.
- SinkStatus - Class in org.apache.spark.sql.streaming
-
:: Experimental ::
Status and metrics of a streaming Sink.
- sinkStatus() - Method in interface org.apache.spark.sql.streaming.StreamingQuery
-
Returns current status of the sink.
- sinkStatus() - Method in class org.apache.spark.sql.streaming.StreamingQueryInfo
-
- size() - Method in class org.apache.spark.api.java.JavaUtils.SerializableMapWrapper
-
- size() - Method in class org.apache.spark.ml.attribute.AttributeGroup
-
Size of the attribute group.
- size() - Method in class org.apache.spark.ml.linalg.DenseVector
-
- size() - Method in class org.apache.spark.ml.linalg.SparseVector
-
- size() - Method in interface org.apache.spark.ml.linalg.Vector
-
Size of the vector.
- size() - Method in class org.apache.spark.ml.param.ParamMap
-
Number of param pairs in this map.
- size() - Method in class org.apache.spark.mllib.linalg.DenseVector
-
- size() - Method in class org.apache.spark.mllib.linalg.SparseVector
-
- size() - Method in interface org.apache.spark.mllib.linalg.Vector
-
Size of the vector.
- size(Column) - Static method in class org.apache.spark.sql.functions
-
Returns length of array or map.
- size() - Method in interface org.apache.spark.sql.Row
-
Number of elements in the Row.
- size() - Static method in class org.apache.spark.sql.types.StructType
-
- size() - Method in class org.apache.spark.storage.memory.DeserializedMemoryEntry
-
- size() - Method in interface org.apache.spark.storage.memory.MemoryEntry
-
- size() - Method in class org.apache.spark.storage.memory.SerializedMemoryEntry
-
- SizeEstimator - Class in org.apache.spark.util
-
:: DeveloperApi ::
Estimates the sizes of Java objects (number of bytes of memory they occupy), for use in
memory-aware caches.
- SizeEstimator() - Constructor for class org.apache.spark.util.SizeEstimator
-
- sizeInBytes() - Method in class org.apache.spark.sql.sources.BaseRelation
-
Returns an estimated size of this relation in bytes.
- sketch(RDD<K>, int, ClassTag<K>) - Static method in class org.apache.spark.RangePartitioner
-
Sketches the input RDD via reservoir sampling on each partition.
- skewness(Column) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the skewness of the values in a group.
- skewness(String) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the skewness of the values in a group.
- skip(long) - Method in class org.apache.spark.io.LZ4BlockInputStream
-
- skip(long) - Method in class org.apache.spark.storage.BufferReleasingInputStream
-
- skip(long) - Method in class org.apache.spark.util.io.ChunkedByteBufferInputStream
-
- skippedStages() - Method in class org.apache.spark.ui.jobs.JobProgressListener
-
- skipWhitespace() - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- Slave - Class in org.apache.spark.scheduler.cluster.mesos
-
- Slave(String) - Constructor for class org.apache.spark.scheduler.cluster.mesos.Slave
-
- slice(int, int) - Static method in class org.apache.spark.sql.types.StructType
-
- slice(Time, Time) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- slice(Time, Time) - Method in interface org.apache.spark.streaming.api.java.JavaDStreamLike
-
Return all the RDDs between 'fromDuration' to 'toDuration' (both included)
- slice(Time, Time) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- slice(Time, Time) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- slice(Time, Time) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- slice(Time, Time) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- slice(Time, Time) - Static method in class org.apache.spark.streaming.api.java.JavaReceiverInputDStream
-
- slice(org.apache.spark.streaming.Interval) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return all the RDDs defined by the Interval object (both end times included)
- slice(Time, Time) - Method in class org.apache.spark.streaming.dstream.DStream
-
Return all the RDDs between 'fromTime' to 'toTime' (both included)
- slideDuration() - Method in class org.apache.spark.streaming.dstream.DStream
-
Time interval after which the DStream generates a RDD
- slideDuration() - Method in class org.apache.spark.streaming.dstream.InputDStream
-
- sliding(int, int) - Method in class org.apache.spark.mllib.rdd.RDDFunctions
-
Returns a RDD from grouping items of its parent RDD in fixed size blocks by passing a sliding
window over them.
- sliding(int) - Method in class org.apache.spark.mllib.rdd.RDDFunctions
-
sliding(Int, Int)* with step = 1.
- sliding(int) - Static method in class org.apache.spark.sql.types.StructType
-
- sliding(int, int) - Static method in class org.apache.spark.sql.types.StructType
-
- smoothing() - Static method in class org.apache.spark.ml.classification.NaiveBayes
-
- smoothing() - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- SnappyCompressionCodec - Class in org.apache.spark.io
-
- SnappyCompressionCodec(SparkConf) - Constructor for class org.apache.spark.io.SnappyCompressionCodec
-
- SnappyOutputStreamWrapper - Class in org.apache.spark.io
-
Wrapper over SnappyOutputStream which guards against write-after-close and double-close
issues.
- SnappyOutputStreamWrapper(SnappyOutputStream) - Constructor for class org.apache.spark.io.SnappyOutputStreamWrapper
-
- socketStream(String, int, Function<InputStream, Iterable<T>>, StorageLevel) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Create an input stream from network source hostname:port.
- socketStream(String, int, Function1<InputStream, Iterator<T>>, StorageLevel, ClassTag<T>) - Method in class org.apache.spark.streaming.StreamingContext
-
Creates an input stream from TCP source hostname:port.
- socketTextStream(String, int, StorageLevel) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Create an input stream from network source hostname:port.
- socketTextStream(String, int) - Method in class org.apache.spark.streaming.api.java.JavaStreamingContext
-
Create an input stream from network source hostname:port.
- socketTextStream(String, int, StorageLevel) - Method in class org.apache.spark.streaming.StreamingContext
-
Creates an input stream from TCP source hostname:port.
- solve(double[], double[]) - Static method in class org.apache.spark.mllib.linalg.CholeskyDecomposition
-
Solves a symmetric positive definite linear system via Cholesky factorization.
- solve(double[], double[], NNLS.Workspace) - Static method in class org.apache.spark.mllib.optimization.NNLS
-
Solve a least squares problem, possibly with nonnegativity constraints, by a modified
projected gradient method.
- solver() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- solver() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- solver() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- solver() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionTrainingSummary
-
- solver() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- solver() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- Sort() - Static method in class org.apache.spark.mllib.tree.configuration.QuantileStrategy
-
- sort(String, String...) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset sorted by the specified column, all in ascending order.
- sort(Column...) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset sorted by the given expressions.
- sort(String, Seq<String>) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset sorted by the specified column, all in ascending order.
- sort(Seq<Column>) - Method in class org.apache.spark.sql.Dataset
-
Returns a new Dataset sorted by the given expressions.
- sort_array(Column) - Static method in class org.apache.spark.sql.functions
-
Sorts the input array for the given column in ascending order,
according to the natural ordering of the array elements.
- sort_array(Column, boolean) - Static method in class org.apache.spark.sql.functions
-
Sorts the input array for the given column in ascending / descending order,
according to the natural ordering of the array elements.
- sortBy(Function<T, S>, boolean, int) - Method in class org.apache.spark.api.java.JavaRDD
-
Return this RDD sorted by the given key function.
- sortBy(Function1<T, K>, boolean, int, Ordering<K>, ClassTag<K>) - Static method in class org.apache.spark.api.r.RRDD
-
- sortBy(Function1<T, K>, boolean, int, Ordering<K>, ClassTag<K>) - Static method in class org.apache.spark.graphx.EdgeRDD
-
- sortBy(Function1<T, K>, boolean, int, Ordering<K>, ClassTag<K>) - Static method in class org.apache.spark.graphx.impl.