- abort(WriterCommitMessage[]) - Method in interface org.apache.spark.sql.sources.v2.writer.DataSourceWriter
-
- abort() - Method in interface org.apache.spark.sql.sources.v2.writer.DataWriter
-
Aborts this writer if it is failed.
- abort(long, WriterCommitMessage[]) - Method in interface org.apache.spark.sql.sources.v2.writer.streaming.StreamWriter
-
- abort(WriterCommitMessage[]) - Method in interface org.apache.spark.sql.sources.v2.writer.streaming.StreamWriter
-
- abortJob(JobContext) - Method in class org.apache.spark.internal.io.FileCommitProtocol
-
Aborts a job after the writes fail.
- abortJob(JobContext) - Method in class org.apache.spark.internal.io.HadoopMapReduceCommitProtocol
-
- abortTask(TaskAttemptContext) - Method in class org.apache.spark.internal.io.FileCommitProtocol
-
Aborts a task after the writes have failed.
- abortTask(TaskAttemptContext) - Method in class org.apache.spark.internal.io.HadoopMapReduceCommitProtocol
-
- 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
-
- AbstractLauncher<T extends AbstractLauncher> - Class in org.apache.spark.launcher
-
Base class for launcher implementations.
- 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
-
- accept(Path) - Method in class org.apache.spark.ml.image.SamplePathFilter
-
- 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
-
- acceptsType(DataType) - Method in class org.apache.spark.sql.types.ObjectType
-
- accId() - Method in class org.apache.spark.CleanAccum
-
- Accumulable<R,T> - Class in org.apache.spark
-
- 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
-
- accumulable(T, String, AccumulableParam<T, R>) - Method in class org.apache.spark.api.java.JavaSparkContext
-
- accumulable(R, AccumulableParam<R, T>) - Method in class org.apache.spark.SparkContext
-
- accumulable(R, String, AccumulableParam<R, T>) - Method in class org.apache.spark.SparkContext
-
- accumulableCollection(R, Function1<R, Growable<T>>, ClassTag<R>) - Method in class org.apache.spark.SparkContext
-
- 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
-
- 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.
- accumulablesToJson(Traversable<AccumulableInfo>) - Static method in class org.apache.spark.util.JsonProtocol
-
- Accumulator<T> - Class in org.apache.spark
-
- accumulator(int) - Method in class org.apache.spark.api.java.JavaSparkContext
-
- accumulator(int, String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
- accumulator(double) - Method in class org.apache.spark.api.java.JavaSparkContext
-
- accumulator(double, String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
- accumulator(T, AccumulatorParam<T>) - Method in class org.apache.spark.api.java.JavaSparkContext
-
- accumulator(T, String, AccumulatorParam<T>) - Method in class org.apache.spark.api.java.JavaSparkContext
-
- accumulator(T, AccumulatorParam<T>) - Method in class org.apache.spark.SparkContext
-
- accumulator(T, String, AccumulatorParam<T>) - Method in class org.apache.spark.SparkContext
-
- 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
-
- AccumulatorParam.DoubleAccumulatorParam$ - Class in org.apache.spark
-
- AccumulatorParam.FloatAccumulatorParam$ - Class in org.apache.spark
-
- AccumulatorParam.IntAccumulatorParam$ - Class in org.apache.spark
-
- AccumulatorParam.LongAccumulatorParam$ - Class in org.apache.spark
-
- AccumulatorParam.StringAccumulatorParam$ - Class in org.apache.spark
-
- ACCUMULATORS() - Static method in class org.apache.spark.status.TaskIndexNames
-
- 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 interface org.apache.spark.ml.classification.LogisticRegressionSummary
-
Returns accuracy.
- 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
-
- acos(String) - Static method in class org.apache.spark.sql.functions
-
- 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
-
- activeStages() - Method in class org.apache.spark.status.LiveJob
-
- activeTasks() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
-
- activeTasks() - Method in class org.apache.spark.status.LiveExecutor
-
- activeTasks() - Method in class org.apache.spark.status.LiveJob
-
- activeTasks() - Method in class org.apache.spark.status.LiveStage
-
- 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(Vector) - Method in class org.apache.spark.ml.clustering.ExpectationAggregator
-
Add a new training instance to this ExpectationAggregator, update the weights,
means and covariances for each distributions, and update the log likelihood.
- 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(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, DataType, boolean, String) - 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(String, String, boolean, String) - 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.AbstractLauncher
-
Adds command line arguments for the application.
- addAppArgs(String...) - Method in class org.apache.spark.launcher.SparkLauncher
-
- 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
.
- 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, boolean) - 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.AbstractLauncher
-
Adds a file to be submitted with the application.
- addFile(String) - Method in class org.apache.spark.launcher.SparkLauncher
-
- 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.AbstractLauncher
-
Adds a jar file to be submitted with the application.
- addJar(String) - Method in class org.apache.spark.launcher.SparkLauncher
-
- 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.
- addJar(String) - Method in class org.apache.spark.sql.hive.HiveSessionResourceLoader
-
- 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(L) - Static method in class org.apache.spark.scheduler.AsyncEventQueue
-
- 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
.
- addMapOutput(int, MapStatus) - Method in class org.apache.spark.ShuffleStatus
-
Register a map output.
- addMetrics(TaskMetrics, TaskMetrics) - Static method in class org.apache.spark.status.LiveEntityHelpers
-
Add m2 values to m1.
- addPartition(LiveRDDPartition) - Method in class org.apache.spark.status.RDDPartitionSeq
-
- addPartToPGroup(Partition, PartitionGroup) - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
-
- addPyFile(String) - Method in class org.apache.spark.launcher.AbstractLauncher
-
Adds a python file / zip / egg to be submitted with the application.
- addPyFile(String) - Method in class org.apache.spark.launcher.SparkLauncher
-
- 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.AbstractLauncher
-
Adds a no-value argument to the Spark invocation.
- addSparkArg(String, String) - Method in class org.apache.spark.launcher.AbstractLauncher
-
Adds an argument with a value to the Spark invocation.
- addSparkArg(String) - Method in class org.apache.spark.launcher.SparkLauncher
-
- addSparkArg(String, String) - Method in class org.apache.spark.launcher.SparkLauncher
-
- addSparkListener(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
-
- 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.
- addTime() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
-
- addTime() - Method in class org.apache.spark.status.LiveExecutor
-
- AddWebUIFilter(String, Map<String, String>, String) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.AddWebUIFilter
-
- AddWebUIFilter$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.AddWebUIFilter$
-
- 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(Broadcast<DenseVector<Object>>, boolean, Broadcast<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, Broadcast<double[]>, int) - Constructor for class org.apache.spark.ml.regression.AFTCostFun
-
- AFTSurvivalRegression - Class in org.apache.spark.ml.regression
-
- 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
-
- aggregationDepth() - Static method in class org.apache.spark.ml.classification.LinearSVC
-
- aggregationDepth() - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- aggregationDepth() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- aggregationDepth() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- aggregationDepth() - Method in interface org.apache.spark.ml.param.shared.HasAggregationDepth
-
Param for suggested depth for treeAggregate (>= 2).
- aggregationDepth() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- aggregationDepth() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- aggregationDepth() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- aggregationDepth() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- 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.
- aliases - Variable in class org.apache.spark.util.kvstore.LevelDB.TypeAliases
-
- 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.InsertIntoHiveDirCommand
-
- allAttributes() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- allAttributes() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- 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.Rating<ID> - Class in org.apache.spark.ml.recommendation
-
:: DeveloperApi ::
Rating class for better code readability.
- ALS.Rating$ - Class in org.apache.spark.ml.recommendation
-
- ALS.RatingBlock$ - Class in org.apache.spark.ml.recommendation
-
- 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
-
Thrown when a query fails to analyze, usually because the query itself is invalid.
- 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.
- anyNull() - Method in class org.apache.spark.sql.vectorized.ColumnarRow
-
- ApiHelper - Class in org.apache.spark.ui.jobs
-
- ApiHelper() - Constructor for class org.apache.spark.ui.jobs.ApiHelper
-
- 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
-
- 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
-
- ApplicationEnvironmentInfo - Class in org.apache.spark.status.api.v1
-
- applicationId() - Method in class org.apache.spark.SparkContext
-
A unique identifier for the Spark application.
- ApplicationInfo - Class in org.apache.spark.status.api.v1
-
- 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(GeneralizedLinearRegressionBase) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.FamilyAndLink$
-
Constructs the FamilyAndLink object from a parameter map
- 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(int) - Static method in class org.apache.spark.rdd.DeterministicLevel
-
- apply(long, String, Option<String>, String, boolean) - Static method in class org.apache.spark.scheduler.AccumulableInfo
-
- apply(long, String, Option<String>, String) - Static method in class org.apache.spark.scheduler.AccumulableInfo
-
- apply(long, String, String) - Static method in class org.apache.spark.scheduler.AccumulableInfo
-
- 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 returns it as a
Column
.
- apply(Column...) - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
-
Creates a Column
for this UDAF using given Column
s as input arguments.
- apply(Seq<Column>) - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
-
Creates a Column
for this UDAF using given Column
s as input arguments.
- apply(Column...) - Method in class org.apache.spark.sql.expressions.UserDefinedFunction
-
Returns an expression that invokes the UDF, using the given arguments.
- apply(Seq<Column>) - Method in class org.apache.spark.sql.expressions.UserDefinedFunction
-
Returns an expression that invokes the UDF, using the given arguments.
- apply(LogicalPlan) - Method in class org.apache.spark.sql.hive.DetermineTableStats
-
- 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.InsertIntoHiveDirCommand
-
- 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.ScriptTransformationExec
-
- apply(LogicalPlan) - Static method in class org.apache.spark.sql.hive.HiveAnalysis
-
- apply(LogicalPlan) - Method in class org.apache.spark.sql.hive.RelationConversions
-
- apply(LogicalPlan) - Method in class org.apache.spark.sql.hive.ResolveHiveSerdeTable
-
- 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
StructField
s of the given names, preserving the
original order of fields.
- apply(int) - Method in class org.apache.spark.sql.types.StructType
-
- apply(int) - Method in class org.apache.spark.status.RDDPartitionSeq
-
- apply(String) - Static method in class org.apache.spark.storage.BlockId
-
- apply(String, String, int, Option<String>) - 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(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(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
-
- applySchema(JavaRDD<Row>, StructType) - Method in class org.apache.spark.sql.SQLContext
-
- applySchema(RDD<?>, Class<?>) - Method in class org.apache.spark.sql.SQLContext
-
- applySchema(JavaRDD<?>, Class<?>) - Method in class org.apache.spark.sql.SQLContext
-
- 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.
- approx_count_distinct(Column) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the approximate number of distinct items in a group.
- approx_count_distinct(String) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the approximate number of distinct items in a group.
- approx_count_distinct(Column, double) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the approximate number of distinct items in a group.
- approx_count_distinct(String, double) - Static method in class org.apache.spark.sql.functions
-
Aggregate function: returns the approximate number of distinct items in a group.
- approxCountDistinct(Column) - Static method in class org.apache.spark.sql.functions
-
- approxCountDistinct(String) - Static method in class org.apache.spark.sql.functions
-
- approxCountDistinct(Column, double) - Static method in class org.apache.spark.sql.functions
-
- approxCountDistinct(String, double) - Static method in class org.apache.spark.sql.functions
-
- ApproxHist() - Static method in class org.apache.spark.mllib.tree.configuration.QuantileStrategy
-
- approxNearestNeighbors(Dataset<?>, Vector, int, String) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- approxNearestNeighbors(Dataset<?>, Vector, int) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- approxNearestNeighbors(Dataset<?>, Vector, int, String) - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- approxNearestNeighbors(Dataset<?>, Vector, int) - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- approxQuantile(String, double[], double) - Method in class org.apache.spark.sql.DataFrameStatFunctions
-
Calculates the approximate quantiles of a numerical column of a DataFrame.
- approxQuantile(String[], double[], double) - Method in class org.apache.spark.sql.DataFrameStatFunctions
-
Calculates the approximate quantiles of numerical columns of a DataFrame.
- approxSimilarityJoin(Dataset<?>, Dataset<?>, double, String) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- approxSimilarityJoin(Dataset<?>, Dataset<?>, double) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- approxSimilarityJoin(Dataset<?>, Dataset<?>, double, String) - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- approxSimilarityJoin(Dataset<?>, Dataset<?>, double) - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- appSparkVersion() - Method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
-
- AppStatusUtils - Class in org.apache.spark.status
-
- AppStatusUtils() - Constructor for class org.apache.spark.status.AppStatusUtils
-
- 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 interface 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.InsertIntoHiveDirCommand
-
- argString() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- argString() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- 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() - Method in class org.apache.spark.sql.vectorized.ColumnarArray
-
- array_contains(Column, Object) - Static method in class org.apache.spark.sql.functions
-
Returns null if the array is null, true if the array contains value
, and false otherwise.
- 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
-
- ArrowColumnVector - Class in org.apache.spark.sql.vectorized
-
A column vector backed by Apache Arrow.
- ArrowColumnVector(ValueVector) - Constructor for class org.apache.spark.sql.vectorized.ArrowColumnVector
-
- 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.
- asBinary() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
-
Convenient method for casting to binary logistic regression summary.
- 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 a sort expression based on ascending order of the column.
- asc(String) - Static method in class org.apache.spark.sql.functions
-
Returns a sort expression based on ascending order of the column.
- asc_nulls_first() - Method in class org.apache.spark.sql.Column
-
Returns a sort expression based on ascending order of the column,
and null values return before non-null values.
- asc_nulls_first(String) - Static method in class org.apache.spark.sql.functions
-
Returns a sort expression based on ascending order of the column,
and null values return before non-null values.
- asc_nulls_last() - Method in class org.apache.spark.sql.Column
-
Returns a sort expression based on ascending order of the column,
and null values appear after non-null values.
- asc_nulls_last(String) - Static method in class org.apache.spark.sql.functions
-
Returns a sort expression based on ascending order of the column,
and null values appear after non-null values.
- 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.InsertIntoHiveDirCommand
-
- asCode() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- asCode() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- asin(Column) - Static method in class org.apache.spark.sql.functions
-
- asin(String) - Static method in class org.apache.spark.sql.functions
-
- 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, 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
-
- asMap() - Method in class org.apache.spark.sql.sources.v2.DataSourceOptions
-
- 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.
- asNondeterministic() - Method in class org.apache.spark.sql.expressions.UserDefinedFunction
-
Updates UserDefinedFunction to nondeterministic.
- asNonNullable() - Method in class org.apache.spark.sql.expressions.UserDefinedFunction
-
Updates UserDefinedFunction to non-nullable.
- asNullable() - Method in class org.apache.spark.sql.types.ObjectType
-
- 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
-
- assertConf(JobContext, SparkConf) - Method in class org.apache.spark.internal.io.HadoopWriteConfigUtil
-
- 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.
- Assignment(long, int) - Constructor for class org.apache.spark.mllib.clustering.PowerIterationClustering.Assignment
-
- Assignment$() - Constructor for class org.apache.spark.mllib.clustering.PowerIterationClustering.Assignment$
-
- assignments() - Method in class org.apache.spark.mllib.clustering.PowerIterationClusteringModel
-
- AssociationRules - Class in org.apache.spark.ml.fpm
-
- AssociationRules() - Constructor for class org.apache.spark.ml.fpm.AssociationRules
-
- associationRules() - Method in class org.apache.spark.ml.fpm.FPGrowthModel
-
Get association rules fitted using the minConfidence.
- 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.
- ASYNC_TRACKING_ENABLED() - Static method in class org.apache.spark.status.config
-
- AsyncEventQueue - Class in org.apache.spark.scheduler
-
An asynchronous queue for events.
- AsyncEventQueue(String, SparkConf, LiveListenerBusMetrics, LiveListenerBus) - Constructor for class org.apache.spark.scheduler.AsyncEventQueue
-
- 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
-
- atan(String) - Static method in class org.apache.spark.sql.functions
-
- atan2(Column, Column) - Static method in class org.apache.spark.sql.functions
-
- atan2(Column, String) - Static method in class org.apache.spark.sql.functions
-
- atan2(String, Column) - Static method in class org.apache.spark.sql.functions
-
- atan2(String, String) - Static method in class org.apache.spark.sql.functions
-
- atan2(Column, double) - Static method in class org.apache.spark.sql.functions
-
- atan2(String, double) - Static method in class org.apache.spark.sql.functions
-
- atan2(double, Column) - Static method in class org.apache.spark.sql.functions
-
- atan2(double, String) - Static method in class org.apache.spark.sql.functions
-
- attempt() - Method in class org.apache.spark.status.api.v1.TaskData
-
- ATTEMPT() - Static method in class org.apache.spark.status.TaskIndexNames
-
- 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.StageInfo
-
- 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
-
- AtTimestamp(Date) - Constructor for class org.apache.spark.streaming.kinesis.KinesisInitialPositions.AtTimestamp
-
- 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.NioBufferedFileInputStream
-
- available() - Method in class org.apache.spark.io.ReadAheadInputStream
-
- 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.
- avgEventRate() - Method in class org.apache.spark.status.api.v1.streaming.ReceiverInfo
-
- avgInputRate() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
-
- avgMetrics() - Method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- avgProcessingTime() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
-
- avgSchedulingDelay() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
-
- avgTotalDelay() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
-
- 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.
- awaitReady(Awaitable<T>, Duration) - Static method in class org.apache.spark.util.ThreadUtils
-
Preferred alternative to Await.ready()
.
- 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
-
Deprecated.
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, StorageLevel) - Method in class org.apache.spark.sql.catalog.Catalog
-
Caches the specified table with the given storage level.
- 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.regression.AFTCostFun
-
- 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
- calculateNumberOfPartitions(long, int, int) - Method in class org.apache.spark.ml.feature.Word2VecModel.Word2VecModelWriter$
-
Calculate the number of partitions to use in saving the model.
- CalendarIntervalType - Class in org.apache.spark.sql.types
-
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(K, Iterator<V>, GroupState<S>) - Method in interface org.apache.spark.api.java.function.FlatMapGroupsWithStateFunction
-
- 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(K, Iterator<V>, GroupState<S>) - Method in interface org.apache.spark.api.java.function.MapGroupsWithStateFunction
-
- 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() - Method in interface org.apache.spark.sql.api.java.UDF0
-
- 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.
- cancelJob(int, String) - Method in class org.apache.spark.SparkContext
-
Cancel a given job if it's scheduled or running.
- cancelJob(int) - Method in class org.apache.spark.SparkContext
-
Cancel a given job if it's scheduled or 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.
- cancelStage(int, String) - Method in class org.apache.spark.SparkContext
-
Cancel a given stage and all jobs associated with it.
- cancelStage(int) - Method in class org.apache.spark.SparkContext
-
Cancel a given stage and all jobs associated with it.
- 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) - Static method in class org.apache.spark.scheduler.BlacklistedExecutor
-
- 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.SparkListenerExecutorBlacklisted
-
- 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.SparkListenerExecutorUnblacklisted
-
- 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.SparkListenerLogStart
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerNodeBlacklisted
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerNodeUnblacklisted
-
- canEqual(Object) - Static method in class org.apache.spark.scheduler.SparkListenerSpeculativeTaskSubmitted
-
- 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.InsertIntoHiveDirCommand
-
- 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.ScriptTransformationExec
-
- canEqual(Object) - Static method in class org.apache.spark.sql.hive.RelationConversions
-
- 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.jdbc.TeradataDialect
-
- 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
-
Deprecated.
- canEqual(Object) - Static method in class org.apache.spark.sql.types.ArrayType
-
- canEqual(Object) - Static method in class org.apache.spark.sql.types.CharType
-
- 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.ObjectType
-
- 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.sql.types.VarcharType
-
- canEqual(Object) - Static method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
-
- canEqual(Object) - Static method in class org.apache.spark.status.api.v1.ApplicationInfo
-
- 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.kinesis.DefaultCredentials
-
- 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.StreamingListenerStreamingStarted
-
- 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
-
- canHandle(String) - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
-
- canonicalized() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- canonicalized() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- canonicalized() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- canonicalized() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- CanonicalRandomVertexCut$() - Constructor for class org.apache.spark.graphx.PartitionStrategy.CanonicalRandomVertexCut$
-
- 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.
- 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() - Static method in class org.apache.spark.sql.types.CharType
-
- 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.HiveStringType
-
- 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.ObjectType
-
- 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
-
- catalogString() - Static method in class org.apache.spark.sql.types.VarcharType
-
- 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
-
- categoricalCols() - Method in class org.apache.spark.ml.feature.FeatureHasher
-
Numeric columns to treat as categorical features.
- 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
-
- categorySizes() - Method in class org.apache.spark.ml.feature.OneHotEncoderModel
-
- 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.
- channelRead0(ChannelHandlerContext, byte[]) - Method in class org.apache.spark.api.r.RBackendAuthHandler
-
- CharType - Class in org.apache.spark.sql.types
-
Hive char type.
- CharType(int) - Constructor for class org.apache.spark.sql.types.CharType
-
- checkAndGetK8sMasterUrl(String) - Static method in class org.apache.spark.util.Utils
-
Check the validity of the given Kubernetes master URL and return the resolved URL.
- checkColumnNameDuplication(Seq<String>, String, Function2<String, String, Object>) - Static method in class org.apache.spark.sql.util.SchemaUtils
-
Checks if input column names have duplicate identifiers.
- checkColumnNameDuplication(Seq<String>, String, boolean) - Static method in class org.apache.spark.sql.util.SchemaUtils
-
Checks if input column names have duplicate identifiers.
- 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.
- checkDataColumns(RFormula, Dataset<?>) - Static method in class org.apache.spark.ml.r.RWrapperUtils
-
DataFrame column check.
- checkFileExists(String, Configuration) - Static method in class org.apache.spark.streaming.util.HdfsUtils
-
Check if the file exists at the given path.
- checkHost(String) - Static method in class org.apache.spark.util.Utils
-
- checkHostPort(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() - Method in class org.apache.spark.sql.Dataset
-
Eagerly checkpoint a Dataset and return the new Dataset.
- checkpoint(boolean) - Method in class org.apache.spark.sql.Dataset
-
Returns a checkpointed version of this Dataset.
- 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() - Method in interface org.apache.spark.ml.param.shared.HasCheckpointInterval
-
Param for set checkpoint interval (>= 1) or disable checkpoint (-1).
- 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
- CheckpointState() - Constructor for class org.apache.spark.rdd.CheckpointState
-
- checkSchemaColumnNameDuplication(StructType, String, boolean) - Static method in class org.apache.spark.sql.util.SchemaUtils
-
Checks if an input schema has duplicate column names.
- checkSingleVsMultiColumnParams(Params, Seq<Param<?>>, Seq<Param<?>>) - Static method in class org.apache.spark.ml.param.ParamValidators
-
Utility for Param validity checks for Transformers which have both single- and multi-column
support.
- checkState(boolean, Function0<String>) - Static method in class org.apache.spark.streaming.util.HdfsUtils
-
- child() - Method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- 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.InsertIntoHiveDirCommand
-
- children() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- children() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- childrenResolved() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- childrenResolved() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- childrenResolved() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- 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() - Constructor for class org.apache.spark.mllib.feature.ChiSqSelector
-
- ChiSqSelector(int) - Constructor for class org.apache.spark.mllib.feature.ChiSqSelector
-
The is the same to call this() and setNumTopFeatures(numTopFeatures)
- 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$.Data - Class in org.apache.spark.mllib.feature
-
Model data for import/export
- chiSqTest(Vector, Vector) - Static method in class org.apache.spark.mllib.stat.Statistics
-
Conduct Pearson's chi-squared goodness of fit test of the observed data against the
expected distribution.
- chiSqTest(Vector) - Static method in class org.apache.spark.mllib.stat.Statistics
-
Conduct Pearson's chi-squared goodness of fit test of the observed data against the uniform
distribution, with each category having an expected frequency of 1 / observed.size
.
- chiSqTest(Matrix) - Static method in class org.apache.spark.mllib.stat.Statistics
-
Conduct Pearson's independence test on the input contingency matrix, which cannot contain
negative entries or columns or rows that sum up to 0.
- chiSqTest(RDD<LabeledPoint>) - Static method in class org.apache.spark.mllib.stat.Statistics
-
Conduct Pearson's independence test for every feature against the label across the input RDD.
- chiSqTest(JavaRDD<LabeledPoint>) - Static method in class org.apache.spark.mllib.stat.Statistics
-
Java-friendly version of chiSqTest()
- ChiSqTest - Class in org.apache.spark.mllib.stat.test
-
Conduct the chi-squared test for the input RDDs using the specified method.
- ChiSqTest() - Constructor for class org.apache.spark.mllib.stat.test.ChiSqTest
-
- ChiSqTest.Method - Class in org.apache.spark.mllib.stat.test
-
param: name String name for the method.
- ChiSqTest.Method$ - Class in org.apache.spark.mllib.stat.test
-
- ChiSqTest.NullHypothesis$ - Class in org.apache.spark.mllib.stat.test
-
- 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
-
- ChiSquareTest - Class in org.apache.spark.ml.stat
-
:: Experimental ::
- ChiSquareTest() - Constructor for class org.apache.spark.ml.stat.ChiSquareTest
-
- 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
-
- 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() - Static method in class org.apache.spark.ml.linalg.JsonMatrixConverter
-
Unique class name for identifying JSON object encoded by this class.
- className() - Method in class org.apache.spark.sql.catalog.Function
-
- classpathEntries() - Method in class org.apache.spark.status.api.v1.ApplicationEnvironmentInfo
-
- 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.sql.Dataset
-
- 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
-
- cleaning() - Method in class org.apache.spark.status.LiveStage
-
- 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.LinearSVC
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- 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.ClusteringEvaluator
-
- 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.BucketedRandomProjectionLSH
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- 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.FeatureHasher
-
- 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.Imputer
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.ImputerModel
-
- 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.MinHashLSH
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- 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
-
Deprecated.
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.feature.OneHotEncoderModel
-
- 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.VectorSizeHint
-
- 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<?>) - Static method in class org.apache.spark.ml.fpm.FPGrowth
-
- clear(Param<?>) - Static method in class org.apache.spark.ml.fpm.FPGrowthModel
-
- 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
-
- 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.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.
- CLogLog$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.CLogLog$
-
- clone() - Method in class org.apache.spark.SparkConf
-
Copy this object
- clone() - Method in class org.apache.spark.sql.ExperimentalMethods
-
- clone() - Method in class org.apache.spark.sql.types.Decimal
-
- clone() - Method in class org.apache.spark.sql.util.ExecutionListenerManager
-
Get an identical copy of this listener manager.
- 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.NioBufferedFileInputStream
-
- close() - Method in class org.apache.spark.io.ReadAheadInputStream
-
- 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.sql.hive.execution.HiveOutputWriter
-
- close() - Method in class org.apache.spark.sql.SparkSession
-
Synonym for stop()
.
- close() - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
-
- close() - Method in class org.apache.spark.sql.vectorized.ColumnarBatch
-
Called to close all the columns in this batch.
- close() - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Cleans up memory for this column vector.
- close() - Method in class org.apache.spark.storage.BufferReleasingInputStream
-
- close() - Method in class org.apache.spark.storage.CountingWritableChannel
-
- 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.kvstore.InMemoryStore
-
- close() - Method in class org.apache.spark.util.kvstore.LevelDB
-
- closeableIterator() - Method in class org.apache.spark.util.kvstore.KVStoreView
-
Returns an iterator for the current configuration.
- closeWriter(TaskAttemptContext) - Method in class org.apache.spark.internal.io.HadoopWriteConfigUtil
-
- 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.sql.types.ObjectType
-
- 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 an Array to contain a collection of T
.
- cluster() - Method in class org.apache.spark.ml.clustering.ClusteringSummary
-
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
-
- clusteredColumns - Variable in class org.apache.spark.sql.sources.v2.reader.partitioning.ClusteredDistribution
-
The names of the clustered columns.
- ClusteredDistribution - Class in org.apache.spark.sql.sources.v2.reader.partitioning
-
- ClusteredDistribution(String[]) - Constructor for class org.apache.spark.sql.sources.v2.reader.partitioning.ClusteredDistribution
-
- ClusteringEvaluator - Class in org.apache.spark.ml.evaluation
-
:: Experimental ::
- ClusteringEvaluator(String) - Constructor for class org.apache.spark.ml.evaluation.ClusteringEvaluator
-
- ClusteringEvaluator() - Constructor for class org.apache.spark.ml.evaluation.ClusteringEvaluator
-
- ClusteringSummary - Class in org.apache.spark.ml.clustering
-
:: Experimental ::
Summary of clustering algorithms.
- clusterSizes() - Method in class org.apache.spark.ml.clustering.ClusteringSummary
-
Size of (number of data points in) each cluster.
- ClusterStats(Vector, double, long) - Constructor for class org.apache.spark.ml.evaluation.SquaredEuclideanSilhouette.ClusterStats
-
- ClusterStats$() - Constructor for class org.apache.spark.ml.evaluation.SquaredEuclideanSilhouette.ClusterStats$
-
- 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, when the fewer partitions
are requested.
- 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$4(int, boolean, Option<PartitionCoalescer>) - Static method in class org.apache.spark.rdd.UnionRDD
-
- CoarseGrainedClusterMessages - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages
-
- CoarseGrainedClusterMessages.AddWebUIFilter - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.AddWebUIFilter$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.GetExecutorLossReason - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.GetExecutorLossReason$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.KillExecutors - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.KillExecutors$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.KillExecutorsOnHost - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.KillExecutorsOnHost$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.KillTask - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.KillTask$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.LaunchTask - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.LaunchTask$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RegisterClusterManager - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RegisterClusterManager$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RegisteredExecutor$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RegisterExecutor - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RegisterExecutor$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RegisterExecutorFailed - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RegisterExecutorFailed$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RegisterExecutorResponse - Interface in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RemoveExecutor - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RemoveExecutor$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RemoveWorker - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RemoveWorker$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RequestExecutors - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RequestExecutors$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RetrieveLastAllocatedExecutorId$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.RetrieveSparkAppConfig$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.ReviveOffers$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.SetupDriver - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.SetupDriver$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.Shutdown$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.SparkAppConfig - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.SparkAppConfig$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.StatusUpdate - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.StatusUpdate$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.StopDriver$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.StopExecutor$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.StopExecutors$ - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.UpdateDelegationTokens - Class in org.apache.spark.scheduler.cluster
-
- CoarseGrainedClusterMessages.UpdateDelegationTokens$ - Class in org.apache.spark.scheduler.cluster
-
- 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
-
- coefficientMatrix() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- coefficients() - Method in class org.apache.spark.ml.classification.LinearSVCModel
-
- coefficients() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
A vector of model coefficients for "binomial" logistic regression.
- 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
-
(Scala-specific)
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
-
(Java-specific)
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 ::
An 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 returns it as a
Column
.
- col(String) - Static method in class org.apache.spark.sql.functions
-
Returns a
Column
based on the given column name.
- coldStartStrategy() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- coldStartStrategy() - Static method in class org.apache.spark.ml.recommendation.ALSModel
-
- 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 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.InsertIntoHiveDirCommand
-
- 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.ScriptTransformationExec
-
- 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 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.InsertIntoHiveDirCommand
-
- 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.ScriptTransformationExec
-
- 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
-
- collectLeaves() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- collectLeaves() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- collectLeaves() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- collectLeaves() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- 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.
- collectSubModels() - Method in interface org.apache.spark.ml.param.shared.HasCollectSubModels
-
Param for whether to collect a list of sub-models trained during tuning.
- collectSubModels() - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- collectSubModels() - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- colPtrs() - Method in class org.apache.spark.ml.linalg.SparseMatrix
-
- colPtrs() - Method in class org.apache.spark.mllib.linalg.SparseMatrix
-
- colRegex(String) - Method in class org.apache.spark.sql.Dataset
-
Selects column based on the column name specified as a regex and returns it as
Column
.
- 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.
- column(int) - Method in class org.apache.spark.sql.vectorized.ColumnarBatch
-
Returns the column at `ordinal`.
- ColumnarArray - Class in org.apache.spark.sql.vectorized
-
- ColumnarArray(ColumnVector, int, int) - Constructor for class org.apache.spark.sql.vectorized.ColumnarArray
-
- ColumnarBatch - Class in org.apache.spark.sql.vectorized
-
This class wraps multiple ColumnVectors as a row-wise table.
- ColumnarBatch(ColumnVector[]) - Constructor for class org.apache.spark.sql.vectorized.ColumnarBatch
-
- ColumnarMap - Class in org.apache.spark.sql.vectorized
-
- ColumnarMap(ColumnVector, ColumnVector, int, int) - Constructor for class org.apache.spark.sql.vectorized.ColumnarMap
-
- ColumnarRow - Class in org.apache.spark.sql.vectorized
-
- ColumnarRow(ColumnVector, int) - Constructor for class org.apache.spark.sql.vectorized.ColumnarRow
-
- ColumnName - Class in org.apache.spark.sql
-
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.
- columnSchema() - Static method in class org.apache.spark.ml.image.ImageSchema
-
Schema for the image column: Row(String, Int, Int, Int, Int, Array[Byte])
- 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
-
- ColumnVector - Class in org.apache.spark.sql.vectorized
-
An interface representing in-memory columnar data in Spark.
- 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
-
- commit(Offset) - Method in interface org.apache.spark.sql.sources.v2.reader.streaming.ContinuousReader
-
Informs the source that Spark has completed processing all data for offsets less than or
equal to `end` and will only request offsets greater than `end` in the future.
- commit(Offset) - Method in interface org.apache.spark.sql.sources.v2.reader.streaming.MicroBatchReader
-
Informs the source that Spark has completed processing all data for offsets less than or
equal to `end` and will only request offsets greater than `end` in the future.
- commit(WriterCommitMessage[]) - Method in interface org.apache.spark.sql.sources.v2.writer.DataSourceWriter
-
Commits this writing job with a list of commit messages.
- commit() - Method in interface org.apache.spark.sql.sources.v2.writer.DataWriter
-
- commit(long, WriterCommitMessage[]) - Method in interface org.apache.spark.sql.sources.v2.writer.streaming.StreamWriter
-
Commits this writing job for the specified epoch with a list of commit messages.
- commit(WriterCommitMessage[]) - Method in interface org.apache.spark.sql.sources.v2.writer.streaming.StreamWriter
-
- commitJob(JobContext, Seq<FileCommitProtocol.TaskCommitMessage>) - Method in class org.apache.spark.internal.io.FileCommitProtocol
-
Commits a job after the writes succeed.
- commitJob(JobContext, Seq<FileCommitProtocol.TaskCommitMessage>) - Method in class org.apache.spark.internal.io.HadoopMapReduceCommitProtocol
-
- commitTask(TaskAttemptContext) - Method in class org.apache.spark.internal.io.FileCommitProtocol
-
Commits a task after the writes succeed.
- commitTask(TaskAttemptContext) - Method in class org.apache.spark.internal.io.HadoopMapReduceCommitProtocol
-
- 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
-
- compileValue(Object) - Static method in class org.apache.spark.sql.jdbc.DB2Dialect
-
- compileValue(Object) - Static method in class org.apache.spark.sql.jdbc.DerbyDialect
-
- compileValue(Object) - Method in class org.apache.spark.sql.jdbc.JdbcDialect
-
Converts value to SQL expression.
- compileValue(Object) - Static method in class org.apache.spark.sql.jdbc.MsSqlServerDialect
-
- compileValue(Object) - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
-
- compileValue(Object) - Static method in class org.apache.spark.sql.jdbc.NoopDialect
-
- compileValue(Object) - Static method in class org.apache.spark.sql.jdbc.OracleDialect
-
- compileValue(Object) - Static method in class org.apache.spark.sql.jdbc.PostgresDialect
-
- compileValue(Object) - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
-
- 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 there are some updates.
- completed() - Method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
-
- completedIndices() - Method in class org.apache.spark.status.LiveJob
-
- completedIndices() - Method in class org.apache.spark.status.LiveStage
-
- completedStages() - Method in class org.apache.spark.status.LiveJob
-
- completedTasks() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
-
- completedTasks() - Method in class org.apache.spark.status.LiveExecutor
-
- completedTasks() - Method in class org.apache.spark.status.LiveJob
-
- completedTasks() - Method in class org.apache.spark.status.LiveStage
-
- COMPLETION_TIME() - Static method in class org.apache.spark.status.TaskIndexNames
-
- 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.status.LiveJob
-
- 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.DenseMatrix
-
- compressed() - Static method in class org.apache.spark.ml.linalg.DenseVector
-
- compressed() - Method in interface org.apache.spark.ml.linalg.Matrix
-
Returns a matrix in dense column major, dense row major, sparse row major, or sparse column
major format, whichever uses less storage.
- compressed() - Static method in class org.apache.spark.ml.linalg.SparseMatrix
-
- 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.
- compressedColMajor() - Static method in class org.apache.spark.ml.linalg.DenseMatrix
-
- compressedColMajor() - Method in interface org.apache.spark.ml.linalg.Matrix
-
Returns a matrix in dense or sparse column major format, whichever uses less storage.
- compressedColMajor() - Static method in class org.apache.spark.ml.linalg.SparseMatrix
-
- 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
-
- compressedInputStream(InputStream) - Method in class org.apache.spark.io.ZStdCompressionCodec
-
- 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
-
- compressedOutputStream(OutputStream) - Method in class org.apache.spark.io.ZStdCompressionCodec
-
- compressedRowMajor() - Static method in class org.apache.spark.ml.linalg.DenseMatrix
-
- compressedRowMajor() - Method in interface org.apache.spark.ml.linalg.Matrix
-
Returns a matrix in dense or sparse row major format, whichever uses less storage.
- compressedRowMajor() - Static method in class org.apache.spark.ml.linalg.SparseMatrix
-
- 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 an 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 an RDD for the given time
- compute(Time) - Method in class org.apache.spark.streaming.dstream.ReceiverInputDStream
-
- computeClusterStats(Dataset<Row>, String, String) - Static method in class org.apache.spark.ml.evaluation.SquaredEuclideanSilhouette
-
The method takes the input dataset and computes the aggregated values
about a cluster which are needed by the algorithm.
- 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 greater than or equal to
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.
- computeSilhouetteCoefficient(Broadcast<Map<Object, SquaredEuclideanSilhouette.ClusterStats>>, Vector, double, double) - Static method in class org.apache.spark.ml.evaluation.SquaredEuclideanSilhouette
-
It computes the Silhouette coefficient for a point.
- computeSilhouetteScore(Dataset<?>, String, String) - Static method in class org.apache.spark.ml.evaluation.SquaredEuclideanSilhouette
-
Compute the mean Silhouette values of all samples.
- 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 columns together into a single column.
- concat(Seq<Column>) - Static method in class org.apache.spark.sql.functions
-
Concatenates multiple input columns together into a single 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(int, int, double, double, double, double, double, double) - Constructor for class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
-
- conf() - Method in class org.apache.spark.SparkEnv
-
- conf() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- conf() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- conf() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- conf() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- conf() - Method in class org.apache.spark.sql.hive.RelationConversions
-
- 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 - Class in org.apache.spark.status
-
- config() - Constructor for class org.apache.spark.status.config
-
- ConfigEntryWithDefault<T> - Class in org.apache.spark.internal.config
-
- ConfigEntryWithDefault(String, List<String>, T, Function1<String, T>, Function1<T, String>, String, boolean) - Constructor for class org.apache.spark.internal.config.ConfigEntryWithDefault
-
- ConfigEntryWithDefaultFunction<T> - Class in org.apache.spark.internal.config
-
- ConfigEntryWithDefaultFunction(String, List<String>, Function0<T>, Function1<String, T>, Function1<T, String>, String, boolean) - Constructor for class org.apache.spark.internal.config.ConfigEntryWithDefaultFunction
-
- ConfigEntryWithDefaultString<T> - Class in org.apache.spark.internal.config
-
- ConfigEntryWithDefaultString(String, List<String>, String, Function1<String, T>, Function1<T, String>, String, boolean) - Constructor for class org.apache.spark.internal.config.ConfigEntryWithDefaultString
-
- 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, Configuration, 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"
- 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
-
- 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.InsertIntoHiveDirCommand
-
- constraints() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- 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
-
Deprecated.
Return whether the given block is stored in this block manager in O(1) time.
- containsChild() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- containsChild() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- containsChild() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- containsChild() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- containsDelimiters() - Method in class org.apache.spark.sql.hive.execution.HiveOptions
-
- containsKey(Object) - Method in class org.apache.spark.api.java.JavaUtils.SerializableMapWrapper
-
- 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
-
- Continuous(long) - Static method in class org.apache.spark.sql.streaming.Trigger
-
A trigger that continuously processes streaming data, asynchronously checkpointing at
the specified interval.
- Continuous(long, TimeUnit) - Static method in class org.apache.spark.sql.streaming.Trigger
-
A trigger that continuously processes streaming data, asynchronously checkpointing at
the specified interval.
- Continuous(Duration) - Static method in class org.apache.spark.sql.streaming.Trigger
-
(Scala-friendly)
A trigger that continuously processes streaming data, asynchronously checkpointing at
the specified interval.
- Continuous(String) - Static method in class org.apache.spark.sql.streaming.Trigger
-
A trigger that continuously processes streaming data, asynchronously checkpointing at
the specified interval.
- ContinuousDataReader<T> - Interface in org.apache.spark.sql.sources.v2.reader.streaming
-
A variation on
DataReader
for use with streaming in continuous processing mode.
- ContinuousReader - Interface in org.apache.spark.sql.sources.v2.reader.streaming
-
- ContinuousReadSupport - Interface in org.apache.spark.sql.sources.v2
-
- 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.
- convertToNetty() - Method in class org.apache.spark.storage.EncryptedManagedBuffer
-
- 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.LinearSVC
-
- copy(ParamMap) - Method in class org.apache.spark.ml.classification.LinearSVCModel
-
- 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.ClusteringEvaluator
-
- 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.BucketedRandomProjectionLSH
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- 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.FeatureHasher
-
- 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.Imputer
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.ImputerModel
-
- 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.MinHashLSH
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- 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
-
Deprecated.
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
-
- copy(ParamMap) - Method in class org.apache.spark.ml.feature.OneHotEncoderModel
-
- 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.VectorSizeHint
-
- 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(ParamMap) - Method in class org.apache.spark.ml.fpm.FPGrowth
-
- copy(ParamMap) - Method in class org.apache.spark.ml.fpm.FPGrowthModel
-
- 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.sql.vectorized.ColumnarArray
-
- copy() - Method in class org.apache.spark.sql.vectorized.ColumnarMap
-
- copy() - Method in class org.apache.spark.sql.vectorized.ColumnarRow
-
Revisit this.
- 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
-
- copyFileStreamNIO(FileChannel, FileChannel, long, long) - Static method in class org.apache.spark.util.Utils
-
- 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(Dataset<?>, String, String) - Static method in class org.apache.spark.ml.stat.Correlation
-
:: Experimental ::
Compute the correlation matrix for the input Dataset of Vectors using the specified method.
- corr(Dataset<?>, String) - Static method in class org.apache.spark.ml.stat.Correlation
-
Compute the Pearson correlation matrix for the input Dataset of Vectors.
- 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.
- Correlation - Class in org.apache.spark.ml.stat
-
API for correlation functions in MLlib, compatible with DataFrames and Datasets.
- Correlation() - Constructor for class org.apache.spark.ml.stat.Correlation
-
- 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
-
- cos(String) - Static method in class org.apache.spark.sql.functions
-
- cosh(Column) - Static method in class org.apache.spark.sql.functions
-
- cosh(String) - Static method in class org.apache.spark.sql.functions
-
- 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.clustering.ExpectationAggregator
-
- count() - Method in class org.apache.spark.ml.regression.AFTAggregator
-
- count(Column, Column) - Static method in class org.apache.spark.ml.stat.Summarizer
-
- count(Column) - Static method in class org.apache.spark.ml.stat.Summarizer
-
- 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() - Method in class org.apache.spark.status.RDDPartitionSeq
-
- count() - Method in class org.apache.spark.storage.ReadableChannelFileRegion
-
- 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.util.DoubleAccumulator
-
Returns the number of elements added to the accumulator.
- count(Class<?>) - Method in class org.apache.spark.util.kvstore.InMemoryStore
-
- count(Class<?>, String, Object) - Method in class org.apache.spark.util.kvstore.InMemoryStore
-
- count(Class<?>) - Method in interface org.apache.spark.util.kvstore.KVStore
-
Returns the number of items of the given type currently in the store.
- count(Class<?>, String, Object) - Method in interface org.apache.spark.util.kvstore.KVStore
-
Returns the number of items of the given type which match the given indexed value.
- count(Class<?>) - Method in class org.apache.spark.util.kvstore.LevelDB
-
- count(Class<?>, String, Object) - Method in class org.apache.spark.util.kvstore.LevelDB
-
- 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.
- COUNTER() - Static method in class org.apache.spark.metrics.sink.StatsdMetricType
-
- CountingWritableChannel - Class in org.apache.spark.storage
-
- CountingWritableChannel(WritableByteChannel) - Constructor for class org.apache.spark.storage.CountingWritableChannel
-
- 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 cardinality estimation using
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() - Method in class org.apache.spark.FetchFailed
-
Fetch failures lead to a different failure handling path: (1) we don't abort the stage after
4 task failures, instead we immediately go back to the stage which generated the map output,
and regenerate the missing data.
- 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() - 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.
- covs() - Method in class org.apache.spark.ml.clustering.ExpectationAggregator
-
- 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(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
).
- createAttrGroupForAttrNames(String, int, boolean, boolean) - Static method in class org.apache.spark.ml.feature.OneHotEncoderCommon
-
Creates an `AttributeGroup` with the required number of `BinaryAttribute`.
- createBatchDataReaderFactories() - Method in interface org.apache.spark.sql.sources.v2.reader.SupportsScanColumnarBatch
-
- createCombiner() - Method in class org.apache.spark.Aggregator
-
- createCommitter(int) - Method in class org.apache.spark.internal.io.HadoopWriteConfigUtil
-
- 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.
- createContinuousReader(Optional<StructType>, String, DataSourceOptions) - Method in interface org.apache.spark.sql.sources.v2.ContinuousReadSupport
-
- createCryptoInputStream(InputStream, SparkConf, byte[]) - Static method in class org.apache.spark.security.CryptoStreamUtils
-
Helper method to wrap InputStream
with CryptoInputStream
for decryption.
- createCryptoOutputStream(OutputStream, SparkConf, byte[]) - Static method in class org.apache.spark.security.CryptoStreamUtils
-
Helper method to wrap OutputStream
with CryptoOutputStream
for encryption.
- 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
Row
s using the given schema.
- createDataFrame(JavaRDD<Row>, StructType) - Method in class org.apache.spark.sql.SparkSession
-
:: DeveloperApi ::
Creates a
DataFrame
from a
JavaRDD
containing
Row
s using the given schema.
- createDataFrame(List<Row>, StructType) - Method in class org.apache.spark.sql.SparkSession
-
:: DeveloperApi ::
Creates a
DataFrame
from a
java.util.List
containing
Row
s 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
-
- createDataReader() - Method in interface org.apache.spark.sql.sources.v2.reader.DataReaderFactory
-
Returns a data reader to do the actual reading work.
- createDataReaderFactories() - Method in interface org.apache.spark.sql.sources.v2.reader.DataSourceReader
-
Returns a list of reader factories.
- createDataReaderFactories() - Method in interface org.apache.spark.sql.sources.v2.reader.SupportsScanColumnarBatch
-
- createDataReaderFactories() - Method in interface org.apache.spark.sql.sources.v2.reader.SupportsScanUnsafeRow
-
- 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
java.util.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
-
- createDataWriter(int, int) - Method in interface org.apache.spark.sql.sources.v2.writer.DataWriterFactory
-
Returns a data writer to do the actual writing work.
- 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.
- createdTempDir() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- createdTempDir() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- createdTempDir_$eq(Option<Path>) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- createdTempDir_$eq(Option<Path>) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- createExternalTable(String, String) - Method in class org.apache.spark.sql.catalog.Catalog
-
- createExternalTable(String, String, String) - Method in class org.apache.spark.sql.catalog.Catalog
-
- createExternalTable(String, String, Map<String, String>) - Method in class org.apache.spark.sql.catalog.Catalog
-
- createExternalTable(String, String, Map<String, String>) - Method in class org.apache.spark.sql.catalog.Catalog
-
- createExternalTable(String, String, StructType, Map<String, String>) - Method in class org.apache.spark.sql.catalog.Catalog
-
- createExternalTable(String, String, StructType, Map<String, String>) - Method in class org.apache.spark.sql.catalog.Catalog
-
- 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
-
- createGlobalTempView(String) - Method in class org.apache.spark.sql.Dataset
-
Creates a global temporary view using the given name.
- CreateHiveTableAsSelectCommand - Class in org.apache.spark.sql.hive.execution
-
Create table and insert the query result into it.
- CreateHiveTableAsSelectCommand(CatalogTable, LogicalPlan, Seq<String>, SaveMode) - Constructor for class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- createInputStream() - Method in class org.apache.spark.storage.EncryptedManagedBuffer
-
- createInternalRowWriterFactory() - Method in interface org.apache.spark.sql.sources.v2.writer.SupportsWriteInternalRow
-
- 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.
- createJobContext(String, int) - Method in class org.apache.spark.internal.io.HadoopWriteConfigUtil
-
- createJobID(Date, int) - Static method in class org.apache.spark.internal.io.SparkHadoopWriterUtils
-
- createJobTrackerID(Date) - Static method in class org.apache.spark.internal.io.SparkHadoopWriterUtils
-
- createKey(SparkConf) - Static method in class org.apache.spark.security.CryptoStreamUtils
-
Creates a new encryption key.
- 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
).
- createMetrics(long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long, long) - Static method in class org.apache.spark.status.LiveEntityHelpers
-
- createMetrics(long) - Static method in class org.apache.spark.status.LiveEntityHelpers
-
- createMicroBatchReader(Optional<StructType>, String, DataSourceOptions) - Method in interface org.apache.spark.sql.sources.v2.MicroBatchReadSupport
-
Creates a
MicroBatchReader
to read batches of data from this data source in a
streaming query.
- createOrReplaceGlobalTempView(String) - Method in class org.apache.spark.sql.Dataset
-
Creates or replaces a global temporary view using the given name.
- createOrReplaceTempView(String) - Method in class org.apache.spark.sql.Dataset
-
Creates a local temporary view using the given name.
- createOutputOperationFailureForUI(String) - Static method in class org.apache.spark.streaming.ui.UIUtils
-
- createPathFromString(String, JobConf) - Static method in class org.apache.spark.internal.io.SparkHadoopWriterUtils
-
- 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).
- createProxyHandler(Function1<String, Option<String>>) - Static method in class org.apache.spark.ui.JettyUtils
-
Create a handler for proxying request to Workers and Application Drivers
- createProxyLocationHeader(String, HttpServletRequest, URI) - Static method in class org.apache.spark.ui.JettyUtils
-
- createProxyURI(String, String, String, String) - Static method in class org.apache.spark.ui.JettyUtils
-
- createRDDFromArray(JavaSparkContext, byte[][]) - Static method in class org.apache.spark.api.r.RRDD
-
Create an RRDD given a sequence of byte arrays.
- createRDDFromFile(JavaSparkContext, String, int) - Static method in class org.apache.spark.api.r.RRDD
-
Create an RRDD given a temporary file name.
- createReadableChannel(ReadableByteChannel, SparkConf, byte[]) - Static method in class org.apache.spark.security.CryptoStreamUtils
-
Wrap a ReadableByteChannel
for decryption.
- createReader(DataSourceOptions) - Method in interface org.apache.spark.sql.sources.v2.ReadSupport
-
- createReader(StructType, DataSourceOptions) - Method in interface org.apache.spark.sql.sources.v2.ReadSupportWithSchema
-
- 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
-
Saves a DataFrame to a destination (using data source-specific parameters)
- 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.
- createSecret(SparkConf) - Static method in class org.apache.spark.util.Utils
-
- createServlet(JettyUtils.ServletParams<T>, org.apache.spark.SecurityManager, SparkConf) - Static method in class org.apache.spark.ui.JettyUtils
-
- createServletHandler(String, JettyUtils.ServletParams<T>, org.apache.spark.SecurityManager, SparkConf, String) - 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, String, String, String, InitialPositionInStream, Duration, StorageLevel, Function1<Record, T>, ClassTag<T>) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
-
- 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
-
- createStream(StreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel, Function1<Record, T>, String, String, String, String, String, ClassTag<T>) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
-
- createStream(StreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
-
- createStream(StreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel, String, String) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
-
- createStream(JavaStreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel, Function<Record, T>, Class<T>) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
-
- 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
-
- createStream(JavaStreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel, Function<Record, T>, Class<T>, String, String, String, String, String) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
-
- createStream(JavaStreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
-
- createStream(JavaStreamingContext, String, String, String, String, InitialPositionInStream, Duration, StorageLevel, String, String) - Static method in class org.apache.spark.streaming.kinesis.KinesisUtils
-
- createStream(JavaStreamingContext, String, String, String, String, int, Duration, StorageLevel, String, String, String, String, String) - Method in class org.apache.spark.streaming.kinesis.KinesisUtilsPythonHelper
-
- createStreamWriter(String, StructType, OutputMode, DataSourceOptions) - Method in interface org.apache.spark.sql.sources.v2.StreamWriteSupport
-
Creates an optional
StreamWriter
to save the data to this data source.
- 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
).
- createTable(String, String) - Method in class org.apache.spark.sql.catalog.Catalog
-
:: Experimental ::
Creates a table from the given path and returns the corresponding DataFrame.
- createTable(String, String, String) - Method in class org.apache.spark.sql.catalog.Catalog
-
:: Experimental ::
Creates a table from the given path based on a data source and returns the corresponding
DataFrame.
- createTable(String, String, Map<String, String>) - Method in class org.apache.spark.sql.catalog.Catalog
-
:: Experimental ::
Creates a table based on the dataset in a data source and a set of options.
- createTable(String, String, Map<String, String>) - Method in class org.apache.spark.sql.catalog.Catalog
-
:: Experimental ::
(Scala-specific)
Creates a table based on the dataset in a data source and a set of options.
- createTable(String, String, StructType, Map<String, String>) - Method in class org.apache.spark.sql.catalog.Catalog
-
:: Experimental ::
Create a table based on the dataset in a data source, a schema and a set of options.
- createTable(String, String, StructType, Map<String, String>) - Method in class org.apache.spark.sql.catalog.Catalog
-
:: Experimental ::
(Scala-specific)
Create a table based on the dataset in a data source, a schema and a set of options.
- createTaskAttemptContext(String, int, int, int) - Method in class org.apache.spark.internal.io.HadoopWriteConfigUtil
-
- 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 local 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.
- createUnsafeRowReaderFactories() - Method in interface org.apache.spark.sql.sources.v2.reader.SupportsScanUnsafeRow
-
- createWorkspace(int) - Static method in class org.apache.spark.mllib.optimization.NNLS
-
- createWritableChannel(WritableByteChannel, SparkConf, byte[]) - Static method in class org.apache.spark.security.CryptoStreamUtils
-
Wrap a WritableByteChannel
for encryption.
- createWriter(String, StructType, SaveMode, DataSourceOptions) - Method in interface org.apache.spark.sql.sources.v2.WriteSupport
-
- createWriterFactory() - Method in interface org.apache.spark.sql.sources.v2.writer.DataSourceWriter
-
Creates a writer factory which will be serialized and sent to executors.
- createWriterFactory() - Method in interface org.apache.spark.sql.sources.v2.writer.SupportsWriteInternalRow
-
- crossJoin(Dataset<?>) - Method in class org.apache.spark.sql.Dataset
-
Explicit cartesian join with another DataFrame
.
- 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 performs model selection by splitting the dataset into a set of
non-overlapping randomly partitioned folds which are used as separate training and test datasets
e.g., with k=3 folds, K-fold cross validation will generate 3 (training, test) dataset pairs,
each of which uses 2/3 of the data for training and 1/3 for testing.
- 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
-
CrossValidatorModel contains the model with the highest average cross-validation
metric across folds and uses this model to transform input data.
- CrossValidatorModel.CrossValidatorModelWriter - Class in org.apache.spark.ml.tuning
-
Writer for CrossValidatorModel.
- CryptoStreamUtils - Class in org.apache.spark.security
-
A util class for manipulating IO encryption and decryption streams.
- CryptoStreamUtils() - Constructor for class org.apache.spark.security.CryptoStreamUtils
-
- csv(String...) - Method in class org.apache.spark.sql.DataFrameReader
-
Loads CSV files 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(Dataset<String>) - Method in class org.apache.spark.sql.DataFrameReader
-
Loads an Dataset[String]
storing CSV rows and returns the result as a DataFrame
.
- csv(Seq<String>) - Method in class org.apache.spark.sql.DataFrameReader
-
Loads CSV files 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
-
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.
- CubeType$() - Constructor for class org.apache.spark.sql.RelationalGroupedDataset.CubeType$
-
- 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.
- currentRow() - Static method in class org.apache.spark.sql.expressions.Window
-
Value representing the current row.
- currentRow() - Static method in class org.apache.spark.sql.functions
-
Window function: returns the special frame boundary that represents the current row in the
window partition.
- 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(Vector, double, Option<Object>) - Constructor for class org.apache.spark.mllib.classification.impl.GLMClassificationModel.SaveLoadV1_0$.Data
-
- Data(double[], double[], double[][]) - Constructor for class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV1_0$.Data
-
- Data(double[], double[], double[][], String) - Constructor for class org.apache.spark.mllib.classification.NaiveBayesModel.SaveLoadV2_0$.Data
-
- Data(int) - Constructor for class org.apache.spark.mllib.feature.ChiSqSelectorModel.SaveLoadV1_0$.Data
-
- Data(Vector, double) - Constructor for class org.apache.spark.mllib.regression.impl.GLMRegressionModel.SaveLoadV1_0$.Data
-
- 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
-
- databaseExists(String) - Method in class org.apache.spark.sql.catalog.Catalog
-
Check if the database with the specified name exists.
- 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
-
Functionality for working with missing data in DataFrame
s.
- 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
-
Statistic functions for DataFrame
s.
- DataFrameWriter<T> - Class in org.apache.spark.sql
-
Interface used to write a
Dataset
to external storage systems (e.g.
- DataReader<T> - Interface in org.apache.spark.sql.sources.v2.reader
-
- DataReaderFactory<T> - Interface in org.apache.spark.sql.sources.v2.reader
-
- 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.
- DataSourceOptions - Class in org.apache.spark.sql.sources.v2
-
An immutable string-to-string map in which keys are case-insensitive.
- DataSourceOptions(Map<String, String>) - Constructor for class org.apache.spark.sql.sources.v2.DataSourceOptions
-
- DataSourceReader - Interface in org.apache.spark.sql.sources.v2.reader
-
- DataSourceRegister - Interface in org.apache.spark.sql.sources
-
Data sources should implement this trait so that they can register an alias to their data source.
- DataSourceV2 - Interface in org.apache.spark.sql.sources.v2
-
The base interface for data source v2.
- DataSourceWriter - Interface in org.apache.spark.sql.sources.v2.writer
-
- 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
-
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
-
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
-
- dataType() - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Returns the data type of this column vector.
- 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
-
- DataWriter<T> - Interface in org.apache.spark.sql.sources.v2.writer
-
- DataWriterFactory<T> - Interface in org.apache.spark.sql.sources.v2.writer
-
- 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
- date_trunc(String, Column) - Static method in class org.apache.spark.sql.functions
-
Returns timestamp truncated to the unit specified by the format.
- 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
-
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.
- dayofweek(Column) - Static method in class org.apache.spark.sql.functions
-
Extracts the day of the week 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
-
- deallocate() - Method in class org.apache.spark.storage.ReadableChannelFileRegion
-
- 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.DecimalIsFractional$ - Class in org.apache.spark.sql.types
-
A Fractional
evidence parameter for Decimals.
- DecimalAsIfIntegral$() - Constructor for class org.apache.spark.sql.types.Decimal.DecimalAsIfIntegral$
-
- DecimalIsFractional$() - Constructor for class org.apache.spark.sql.types.Decimal.DecimalIsFractional$
-
- DecimalType - Class in org.apache.spark.sql.types
-
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.Fixed$ - Class in org.apache.spark.sql.types
-
- 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$.NodeData - Class in org.apache.spark.mllib.tree.model
-
Model data for model import/export
- DecisionTreeModel.SaveLoadV1_0$.PredictData - Class in org.apache.spark.mllib.tree.model
-
- DecisionTreeModel.SaveLoadV1_0$.SplitData - Class in org.apache.spark.mllib.tree.model
-
- DecisionTreeModelReadWrite - Class in org.apache.spark.ml.tree
-
Helper classes for tree model persistence
- DecisionTreeModelReadWrite() - Constructor for class org.apache.spark.ml.tree.DecisionTreeModelReadWrite
-
- DecisionTreeModelReadWrite.NodeData - Class in org.apache.spark.ml.tree
-
- DecisionTreeModelReadWrite.NodeData$ - Class in org.apache.spark.ml.tree
-
- DecisionTreeModelReadWrite.SplitData - Class in org.apache.spark.ml.tree
-
- DecisionTreeModelReadWrite.SplitData$ - Class in org.apache.spark.ml.tree
-
- DecisionTreeRegressionModel - Class in org.apache.spark.ml.regression
-
- DecisionTreeRegressor - Class in org.apache.spark.ml.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_CONNECTION_TIMEOUT() - Static method in class org.apache.spark.api.r.SparkRDefaults
-
- 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_HEARTBEAT_INTERVAL() - Static method in class org.apache.spark.api.r.SparkRDefaults
-
- 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_NUM_RBACKEND_THREADS() - Static method in class org.apache.spark.api.r.SparkRDefaults
-
- DEFAULT_NUMBER_EXECUTORS() - Static method in class org.apache.spark.scheduler.cluster.SchedulerBackendUtils
-
- 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
-
- DefaultCredentials - Class in org.apache.spark.streaming.kinesis
-
Returns DefaultAWSCredentialsProviderChain for authentication.
- DefaultCredentials() - Constructor for class org.apache.spark.streaming.kinesis.DefaultCredentials
-
- 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
-
- 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 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() - Static method in class org.apache.spark.sql.types.CharType
-
- 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 when precision is at most 18,
and 16 bytes otherwise.
- 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.HiveStringType
-
- 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
(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.ObjectType
-
- 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.
- defaultSize() - Static method in class org.apache.spark.sql.types.VarcharType
-
- 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
-
- DefaultTopologyMapper - Class in org.apache.spark.storage
-
A TopologyMapper that assumes all nodes are in the same rack
- DefaultTopologyMapper(SparkConf) - Constructor for class org.apache.spark.storage.DefaultTopologyMapper
-
- defaultValue() - Method in class org.apache.spark.internal.config.ConfigEntryWithDefault
-
- defaultValue() - Method in class org.apache.spark.internal.config.ConfigEntryWithDefaultFunction
-
- defaultValue() - Method in class org.apache.spark.internal.config.ConfigEntryWithDefaultString
-
- defaultValueString() - Method in class org.apache.spark.internal.config.ConfigEntryWithDefault
-
- defaultValueString() - Method in class org.apache.spark.internal.config.ConfigEntryWithDefaultFunction
-
- defaultValueString() - Method in class org.apache.spark.internal.config.ConfigEntryWithDefaultString
-
- degree() - Method in class org.apache.spark.ml.feature.PolynomialExpansion
-
The polynomial degree to expand, which should be greater than equal to 1.
- degrees() - Method in class org.apache.spark.graphx.GraphOps
-
The degree of each vertex in the graph.
- degrees(Column) - Static method in class org.apache.spark.sql.functions
-
Converts an angle measured in radians to an approximately equivalent angle measured in degrees.
- degrees(String) - Static method in class org.apache.spark.sql.functions
-
Converts an angle measured in radians to an approximately equivalent angle measured in degrees.
- degreesOfFreedom() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
-
Degrees of freedom.
- degreesOfFreedom() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
-
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
-
- delete(Class<?>, Object) - Method in class org.apache.spark.util.kvstore.InMemoryStore
-
- delete(Class<?>, Object) - Method in interface org.apache.spark.util.kvstore.KVStore
-
Removes an object and all data related to it, like index entries, from the store.
- delete(Class<?>, Object) - Method in class org.apache.spark.util.kvstore.LevelDB
-
- 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.
- deleteWithJob(FileSystem, Path, boolean) - Method in class org.apache.spark.internal.io.FileCommitProtocol
-
Specifies that a file should be deleted with the commit of this job.
- deleteWithJob(FileSystem, Path, boolean) - Static method in class org.apache.spark.internal.io.HadoopMapReduceCommitProtocol
-
- delimiterOptions() - Static method in class org.apache.spark.sql.hive.execution.HiveOptions
-
- delta() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Tweedie$
-
Constant used in initialization and deviance to avoid numerical issues.
- 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 a sort expression based on the descending order of the column.
- 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
-
- desc_nulls_first() - Method in class org.apache.spark.sql.Column
-
Returns a sort expression based on the descending order of the column,
and null values appear before non-null values.
- desc_nulls_first(String) - Static method in class org.apache.spark.sql.functions
-
Returns a sort expression based on the descending order of the column,
and null values appear before non-null values.
- desc_nulls_last() - Method in class org.apache.spark.sql.Column
-
Returns a sort expression based on the descending order of the column,
and null values appear after non-null values.
- desc_nulls_last(String) - Static method in class org.apache.spark.sql.functions
-
Returns a sort expression based on the descending order of the column,
and null values appear after non-null values.
- describe(String...) - Method in class org.apache.spark.sql.Dataset
-
Computes basic statistics for numeric and string columns, including count, mean, stddev, min,
and max.
- describe(Seq<String>) - Method in class org.apache.spark.sql.Dataset
-
Computes basic statistics for numeric and string 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.SinkProgress
-
- description() - Method in class org.apache.spark.sql.streaming.SourceProgress
-
- description() - Method in class org.apache.spark.status.api.v1.JobData
-
- description() - Method in class org.apache.spark.status.api.v1.StageData
-
- description() - Method in class org.apache.spark.status.api.v1.streaming.OutputOperationInfo
-
- description() - Method in class org.apache.spark.status.LiveStage
-
- description() - Method in class org.apache.spark.storage.StorageLevel
-
- description() - Method in class org.apache.spark.streaming.scheduler.OutputOperationInfo
-
- DESER_CPU_TIME() - Static method in class org.apache.spark.status.TaskIndexNames
-
- DESER_TIME() - Static method in class org.apache.spark.status.TaskIndexNames
-
- 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[], Class<T>) - Method in class org.apache.spark.util.kvstore.KVStoreSerializer
-
- 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
)
- deserializeOffset(String) - Method in interface org.apache.spark.sql.sources.v2.reader.streaming.ContinuousReader
-
Deserialize a JSON string into an Offset of the implementation-defined offset type.
- deserializeOffset(String) - Method in interface org.apache.spark.sql.sources.v2.reader.streaming.MicroBatchReader
-
Deserialize a JSON string into an Offset of the implementation-defined offset type.
- 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
-
- DETERMINATE() - Static method in class org.apache.spark.rdd.DeterministicLevel
-
- 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.
- DetermineTableStats - Class in org.apache.spark.sql.hive
-
- DetermineTableStats(SparkSession) - Constructor for class org.apache.spark.sql.hive.DetermineTableStats
-
- deterministic() - Method in class org.apache.spark.sql.expressions.UserDefinedAggregateFunction
-
Returns true iff this function is deterministic, i.e.
- deterministic() - Method in class org.apache.spark.sql.expressions.UserDefinedFunction
-
Returns true iff the UDF is deterministic, i.e.
- DeterministicLevel - Class in org.apache.spark.rdd
-
The deterministic level of RDD's output (i.e.
- DeterministicLevel() - Constructor for class org.apache.spark.rdd.DeterministicLevel
-
- 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
-
- directory(File) - Method in class org.apache.spark.launcher.SparkLauncher
-
Sets the working directory of spark-submit.
- disableOutputSpecValidation() - Static method in class org.apache.spark.internal.io.SparkHadoopWriterUtils
-
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
-
- DISK_SPILL() - Static method in class org.apache.spark.status.TaskIndexNames
-
- DiskBlockData - Class in org.apache.spark.storage
-
- DiskBlockData(long, long, File, long) - Constructor for class org.apache.spark.storage.DiskBlockData
-
- 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
-
- 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.status.LiveExecutor
-
- diskUsed() - Method in class org.apache.spark.status.LiveRDD
-
- diskUsed() - Method in class org.apache.spark.status.LiveRDDDistribution
-
- diskUsed() - Method in class org.apache.spark.status.LiveRDDPartition
-
- diskUsed() - Method in class org.apache.spark.storage.StorageStatus
-
Deprecated.
Return the disk space used by this block manager.
- diskUsedByRdd(int) - Method in class org.apache.spark.storage.StorageStatus
-
Deprecated.
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() - Method in class org.apache.spark.storage.DiskBlockData
-
- dispose() - Method in class org.apache.spark.storage.EncryptedBlockData
-
- dispose(ByteBuffer) - Static method in class org.apache.spark.storage.StorageUtils
-
Attempt to clean up a ByteBuffer if it is direct or 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
Column
s 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
Column
s 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$2(int) - Static method in class org.apache.spark.rdd.UnionRDD
-
- DistributedLDAModel - Class in org.apache.spark.ml.clustering
-
Distributed model fitted by
LDA
.
- DistributedLDAModel - Class in org.apache.spark.mllib.clustering
-
Distributed LDA model.
- DistributedMatrix - Interface in org.apache.spark.mllib.linalg.distributed
-
Represents a distributively stored matrix backed by one or more RDDs.
- Distribution - Interface in org.apache.spark.sql.sources.v2.reader.partitioning
-
An interface to represent data distribution requirement, which specifies how the records should
be distributed among the data partitions(one
DataReader
outputs data for one partition).
- distribution(LiveExecutor) - Method in class org.apache.spark.status.LiveRDD
-
- distributionOpt(LiveExecutor) - Method in class org.apache.spark.status.LiveRDD
-
- div(Decimal, Decimal) - Method in class org.apache.spark.sql.types.Decimal.DecimalIsFractional$
-
- 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
-
- DocumentFrequencyAggregator(int) - Constructor for class org.apache.spark.mllib.feature.IDF.DocumentFrequencyAggregator
-
- DocumentFrequencyAggregator() - Constructor for class org.apache.spark.mllib.feature.IDF.DocumentFrequencyAggregator
-
- doesDirectoryContainAnyNewFiles(File, long) - Static method in class org.apache.spark.util.Utils
-
Determines if a directory contains any files newer than cutoff seconds.
- doFetchFile(String, File, String, SparkConf, org.apache.spark.SecurityManager, Configuration) - Static method in class org.apache.spark.util.Utils
-
Download a file or directory to target directory.
- 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
-
- doubleAccumulator(double, String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
- 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
-
- DoubleAccumulatorParam$() - Constructor for class org.apache.spark.AccumulatorParam.DoubleAccumulatorParam$
-
Deprecated.
- DoubleArrayArrayParam - Class in org.apache.spark.ml.param
-
:: DeveloperApi ::
Specialized version of Param[Array[Array[Double}]
for Java.
- DoubleArrayArrayParam(Params, String, String, Function1<double[][], Object>) - Constructor for class org.apache.spark.ml.param.DoubleArrayArrayParam
-
- DoubleArrayArrayParam(Params, String, String) - Constructor for class org.apache.spark.ml.param.DoubleArrayArrayParam
-
- 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
-
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.
- dropGlobalTempView(String) - Method in class org.apache.spark.sql.catalog.Catalog
-
Drops the global temporary view with the given view name in the catalog.
- dropLast() - Method in class org.apache.spark.ml.feature.OneHotEncoder
-
Deprecated.
Whether to drop the last category in the encoded vector (default: true)
- dropLast() - Static method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
-
- dropLast() - Static method in class org.apache.spark.ml.feature.OneHotEncoderModel
-
- 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 local temporary view with the given view name in the catalog.
- dropWhile(Function1<A, Object>) - Static method in class org.apache.spark.sql.types.StructType
-
- dspmv(int, double, DenseVector, DenseVector, double, DenseVector) - Static method in class org.apache.spark.ml.linalg.BLAS
-
y := alpha*A*x + beta*y
- 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() - Method in class org.apache.spark.status.api.v1.streaming.OutputOperationInfo
-
- duration() - Method in class org.apache.spark.status.api.v1.TaskData
-
- DURATION() - Static method in class org.apache.spark.status.TaskIndexNames
-
- 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.
- durationMs() - Method in class org.apache.spark.sql.streaming.StreamingQueryProgress
-
- 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
-
- failedStages() - Method in class org.apache.spark.status.LiveJob
-
- 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.status.LiveExecutor
-
- failedTasks() - Method in class org.apache.spark.status.LiveExecutorStageSummary
-
- failedTasks() - Method in class org.apache.spark.status.LiveJob
-
- failedTasks() - Method in class org.apache.spark.status.LiveStage
-
- 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.status.api.v1.StageData
-
- failureReason() - Method in class org.apache.spark.status.api.v1.streaming.OutputOperationInfo
-
- 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
-
- FAKE_HIVE_VERSION() - Static method in class org.apache.spark.sql.hive.HiveUtils
-
- 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)
- falsePositiveRateByLabel() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
-
Returns false positive rate for each label (category).
- family() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- family() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- family() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- family() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- Family$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Family$
-
- FamilyAndLink$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.FamilyAndLink$
-
- 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.InsertIntoHiveDirCommand
-
- 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.ScriptTransformationExec
-
- fdr() - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- fdr() - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- fdr() - Method in class org.apache.spark.mllib.feature.ChiSqSelector
-
- 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
-
- FeatureHasher - Class in org.apache.spark.ml.feature
-
Feature hashing projects a set of categorical or numerical features into a feature vector of
specified dimension (typically substantially smaller than that of the original feature
space).
- FeatureHasher(String) - Constructor for class org.apache.spark.ml.feature.FeatureHasher
-
- FeatureHasher() - Constructor for class org.apache.spark.ml.feature.FeatureHasher
-
- 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() - 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.LinearSVC
-
- featuresCol() - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- 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() - Method in class org.apache.spark.ml.classification.LogisticRegressionSummaryImpl
-
- 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() - Method in class org.apache.spark.ml.clustering.ClusteringSummary
-
- 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() - Static method in class org.apache.spark.ml.clustering.KMeans
-
- featuresCol() - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- 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.evaluation.ClusteringEvaluator
-
- 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() - Method in interface org.apache.spark.ml.param.shared.HasFeaturesCol
-
Param for features column name.
- 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.GBTClassificationModel
-
- featureSubsetStrategy() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- 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.GBTRegressionModel
-
- featureSubsetStrategy() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- featureSubsetStrategy() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- featureSubsetStrategy() - Static method in class org.apache.spark.ml.regression.RandomForestRegressor
-
- featureSum() - Method in class org.apache.spark.ml.evaluation.SquaredEuclideanSilhouette.ClusterStats
-
- 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
-
- 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
-
- FILE_FORMAT() - Static method in class org.apache.spark.sql.hive.execution.HiveOptions
-
- FileBasedTopologyMapper - Class in org.apache.spark.storage
-
A simple file based topology mapper.
- FileBasedTopologyMapper(SparkConf) - Constructor for class org.apache.spark.storage.FileBasedTopologyMapper
-
- FileCommitProtocol - Class in org.apache.spark.internal.io
-
An interface to define how a single Spark job commits its outputs.
- FileCommitProtocol() - Constructor for class org.apache.spark.internal.io.FileCommitProtocol
-
- FileCommitProtocol.EmptyTaskCommitMessage$ - Class in org.apache.spark.internal.io
-
- FileCommitProtocol.TaskCommitMessage - Class in org.apache.spark.internal.io
-
- fileFormat() - Method in class org.apache.spark.sql.hive.execution.HiveOptions
-
- 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(long) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
Returns a new DataFrame
that replaces null or NaN values in numeric columns with value
.
- 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(long, 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, String[]) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
Returns a new DataFrame
that replaces null or NaN values in specified numeric columns.
- fill(long, 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(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(boolean) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
Returns a new DataFrame
that replaces null values in boolean columns with value
.
- fill(boolean, Seq<String>) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
(Scala-specific) Returns a new DataFrame
that replaces null values in specified
boolean columns.
- fill(boolean, String[]) - Method in class org.apache.spark.sql.DataFrameNaFunctions
-
Returns a new DataFrame
that replaces null values in specified boolean 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
-
- 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.InsertIntoHiveDirCommand
-
- 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.ScriptTransformationExec
-
- find(Function1<A, Object>) - Static method in class org.apache.spark.sql.types.StructType
-
- findMissingPartitions() - Method in class org.apache.spark.ShuffleStatus
-
Returns the sequence of partition ids that are missing (i.e.
- 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 is 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.
- findSynonymsArray(Vector, int) - Method in class org.apache.spark.ml.feature.Word2VecModel
-
Find "num" number of words whose vector representation is most similar to the supplied vector.
- findSynonymsArray(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.
- 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
-
- 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).
- 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.
- first(Object) - Method in class org.apache.spark.util.kvstore.KVStoreView
-
Iterates starting at the given value of the chosen index (inclusive).
- firstFailureReason() - Method in class org.apache.spark.status.api.v1.streaming.BatchInfo
-
- firstLaunchTime() - Method in class org.apache.spark.status.LiveStage
-
- 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.LinearSVC
-
- fit(Dataset<?>, ParamMap) - Static method in class org.apache.spark.ml.classification.LinearSVC
-
- fit(Dataset<?>, ParamMap[]) - Static method in class org.apache.spark.ml.classification.LinearSVC
-
- fit(Dataset<?>, ParamPair<?>, ParamPair<?>...) - Static method in class org.apache.spark.ml.classification.LinearSVC
-
- fit(Dataset<?>) - Static method in class org.apache.spark.ml.classification.LinearSVC
-
- 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<?>, ParamPair<?>, Seq<ParamPair<?>>) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
-
- fit(Dataset<?>, ParamMap) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
-
- fit(Dataset<?>, ParamMap[]) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
-
- fit(Dataset<?>, ParamPair<?>, ParamPair<?>...) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
-
- fit(Dataset<?>) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
-
- 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.Imputer
-
- fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.MaxAbsScaler
-
- fit(Dataset<?>, ParamPair<?>, Seq<ParamPair<?>>) - Static method in class org.apache.spark.ml.feature.MinHashLSH
-
- fit(Dataset<?>, ParamMap) - Static method in class org.apache.spark.ml.feature.MinHashLSH
-
- fit(Dataset<?>, ParamMap[]) - Static method in class org.apache.spark.ml.feature.MinHashLSH
-
- fit(Dataset<?>, ParamPair<?>, ParamPair<?>...) - Static method in class org.apache.spark.ml.feature.MinHashLSH
-
- fit(Dataset<?>) - Static method in class org.apache.spark.ml.feature.MinHashLSH
-
- fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.MinMaxScaler
-
- fit(Dataset<?>) - Method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
-
- 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.fpm.FPGrowth
-
- 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.LinearSVC
-
- fitIntercept() - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- fitIntercept() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- fitIntercept() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- fitIntercept() - Method in interface org.apache.spark.ml.param.shared.HasFitIntercept
-
Param for whether to fit an intercept term.
- 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
-
- Fixed$() - Constructor for class org.apache.spark.sql.types.DecimalType.Fixed$
-
- 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.InsertIntoHiveDirCommand
-
- 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.ScriptTransformationExec
-
- 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
-
(Scala-specific)
Applies the given function to each group of data.
- flatMapGroups(FlatMapGroupsFunction<K, V, U>, Encoder<U>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
-
(Java-specific)
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.
- flatMapGroupsWithState(OutputMode, GroupStateTimeout, Function3<K, Iterator<V>, GroupState<S>, Iterator<U>>, Encoder<S>, Encoder<U>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
-
::Experimental::
(Scala-specific)
Applies the given function to each group of data, while maintaining a user-defined per-group
state.
- flatMapGroupsWithState(FlatMapGroupsWithStateFunction<K, V, S, U>, OutputMode, Encoder<S>, Encoder<U>, GroupStateTimeout) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
-
::Experimental::
(Java-specific)
Applies the given function to each group of data, while maintaining a user-defined per-group
state.
- FlatMapGroupsWithStateFunction<K,V,S,R> - Interface in org.apache.spark.api.java.function
-
::Experimental::
Base interface for a map function used in
org.apache.spark.sql.KeyValueGroupedDataset.flatMapGroupsWithState(
FlatMapGroupsWithStateFunction, org.apache.spark.sql.streaming.OutputMode,
org.apache.spark.sql.Encoder, org.apache.spark.sql.Encoder)
- 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.
- FloatAccumulatorParam$() - Constructor for class org.apache.spark.AccumulatorParam.FloatAccumulatorParam$
-
Deprecated.
- 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
-
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
-
- 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
-
- fMeasureByLabel(double) - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
-
Returns f-measure for each label (category).
- fMeasureByLabel() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
-
Returns f1-measure for each label (category).
- fMeasureByThreshold() - Method in interface 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
-
- forceIndexLabel() - Static method in class org.apache.spark.ml.feature.RFormula
-
- forceIndexLabel() - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- 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.InsertIntoHiveDirCommand
-
- 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.ScriptTransformationExec
-
- foreach(ForeachWriter<T>) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
-
Starts the execution of the streaming query, which will continually send results to the given
ForeachWriter
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(Function3<Object, Object, Object, BoxedUnit>) - Method in class org.apache.spark.ml.linalg.DenseMatrix
-
- 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(Function3<Object, Object, Object, BoxedUnit>) - Method in class org.apache.spark.ml.linalg.SparseMatrix
-
- 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.InsertIntoHiveDirCommand
-
- 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.ScriptTransformationExec
-
- ForeachWriter<T> - Class in org.apache.spark.sql
-
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
-
Specifies the input data source format.
- format(String) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
-
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
with HALF_EVEN round mode, 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() - Static method in class org.apache.spark.ml.feature.RFormula
-
- formula() - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- FPGrowth - Class in org.apache.spark.ml.fpm
-
:: Experimental ::
A parallel FP-growth algorithm to mine frequent itemsets.
- FPGrowth(String) - Constructor for class org.apache.spark.ml.fpm.FPGrowth
-
- FPGrowth() - Constructor for class org.apache.spark.ml.fpm.FPGrowth
-
- 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.
- FPGrowthModel - Class in org.apache.spark.ml.fpm
-
:: Experimental ::
Model fitted by FPGrowth.
- 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
-
- fpr() - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- fpr() - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- fpr() - Method in class org.apache.spark.mllib.feature.ChiSqSelector
-
- 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.
- FreqItemset(Object, long) - Constructor for class org.apache.spark.mllib.fpm.FPGrowth.FreqItemset
-
- freqItemsets() - Method in class org.apache.spark.ml.fpm.FPGrowthModel
-
- freqItemsets() - Method in class org.apache.spark.mllib.fpm.FPGrowthModel
-
- FreqSequence(Object[], long) - Constructor for class org.apache.spark.mllib.fpm.PrefixSpan.FreqSequence
-
- freqSequences() - Method in class org.apache.spark.mllib.fpm.PrefixSpanModel
-
- from_json(Column, StructType, Map<String, String>) - Static method in class org.apache.spark.sql.functions
-
(Scala-specific) Parses a column containing a JSON string into a StructType
with the
specified schema.
- from_json(Column, DataType, Map<String, String>) - Static method in class org.apache.spark.sql.functions
-
(Scala-specific) Parses a column containing a JSON string into a StructType
or ArrayType
of StructType
s with the specified schema.
- from_json(Column, StructType, Map<String, String>) - Static method in class org.apache.spark.sql.functions
-
(Java-specific) Parses a column containing a JSON string into a StructType
with the
specified schema.
- from_json(Column, DataType, Map<String, String>) - Static method in class org.apache.spark.sql.functions
-
(Java-specific) Parses a column containing a JSON string into a StructType
or ArrayType
of StructType
s with the specified schema.
- from_json(Column, StructType) - Static method in class org.apache.spark.sql.functions
-
Parses a column containing a JSON string into a StructType
with the specified schema.
- from_json(Column, DataType) - Static method in class org.apache.spark.sql.functions
-
Parses a column containing a JSON string into a StructType
or ArrayType
of StructType
s
with the specified schema.
- from_json(Column, String, Map<String, String>) - Static method in class org.apache.spark.sql.functions
-
(Java-specific) Parses a column containing a JSON string into a StructType
or ArrayType
of StructType
s with the specified schema.
- from_json(Column, String, Map<String, String>) - Static method in class org.apache.spark.sql.functions
-
(Scala-specific) Parses a column containing a JSON string into a StructType
or ArrayType
of StructType
s with the specified schema.
- 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
-
Given a timestamp like '2017-07-14 02:40:00.0', interprets it as a time in UTC, and renders
that time as a timestamp in the given time zone.
- 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.
- fromDDL(String) - Static method in class org.apache.spark.sql.types.StructType
-
Creates StructType for a given DDL-formatted string, which is a comma separated list of field
definitions, e.g., a INT, b STRING.
- 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.JsonMatrixConverter
-
Parses the JSON representation of a Matrix into a
Matrix
.
- 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.
- fromKinesisInitialPosition(InitialPositionInStream) - Static method in class org.apache.spark.streaming.kinesis.KinesisInitialPositions
-
Returns instance of [[KinesisInitialPosition]] based on the passed
[[InitialPositionInStream]].
- 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
-
- fromNullable(T) - Static method in class org.apache.spark.api.java.Optional
-
- 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.
- fromParams(GeneralizedLinearRegressionBase) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Family$
-
Gets the Family
object based on param family and variancePower.
- fromParams(GeneralizedLinearRegressionBase) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Link$
-
Gets the Link
object based on param family, link and linkPower.
- 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.streaming.BatchStatus
-
- 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.
- functionExists(String) - Method in class org.apache.spark.sql.catalog.Catalog
-
Check if the function with the specified name exists.
- functionExists(String, String) - Method in class org.apache.spark.sql.catalog.Catalog
-
Check if the function with the specified name exists in the specified database.
- functions - Class in org.apache.spark.sql
-
Functions available for DataFrame operations.
- 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
-
- fwe() - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- fwe() - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- fwe() - Method in class org.apache.spark.mllib.feature.ChiSqSelector
-
- 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
-
- Gamma$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gamma$
-
- 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
-
Java-friendly version of RandomRDDs.gammaRDD
.
- gammaJavaRDD(JavaSparkContext, double, double, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
RandomRDDs.gammaJavaRDD
with the default seed.
- gammaJavaRDD(JavaSparkContext, double, double, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
RandomRDDs.gammaJavaRDD
with the default number of partitions and the default seed.
- gammaJavaVectorRDD(JavaSparkContext, double, double, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
Java-friendly version of RandomRDDs.gammaVectorRDD
.
- gammaJavaVectorRDD(JavaSparkContext, double, double, long, int, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
RandomRDDs.gammaJavaVectorRDD
with the default seed.
- gammaJavaVectorRDD(JavaSparkContext, double, double, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
RandomRDDs.gammaJavaVectorRDD
with the default number of partitions and the default seed.
- 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).
- GAUGE() - Static method in class org.apache.spark.metrics.sink.StatsdMetricType
-
- Gaussian$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gaussian$
-
- GaussianMixture - Class in org.apache.spark.ml.clustering
-
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
-
Multivariate Gaussian Mixture Model (GMM) consisting of k Gaussians, where points
are drawn from each Gaussian i with probability weights(i).
- 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
-
- GBTRegressionModel(String, DecisionTreeRegressionModel[], double[]) - Constructor for class org.apache.spark.ml.regression.GBTRegressionModel
-
Construct a GBTRegressionModel
- GBTRegressor - Class in org.apache.spark.ml.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.status.TaskIndexNames
-
- 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.CLogLog$ - Class in org.apache.spark.ml.regression
-
- GeneralizedLinearRegression.Family$ - Class in org.apache.spark.ml.regression
-
- GeneralizedLinearRegression.FamilyAndLink$ - Class in org.apache.spark.ml.regression
-
- GeneralizedLinearRegression.Gamma$ - Class in org.apache.spark.ml.regression
-
Gamma exponential family distribution.
- GeneralizedLinearRegression.Gaussian$ - Class in org.apache.spark.ml.regression
-
Gaussian exponential family distribution.
- GeneralizedLinearRegression.Identity$ - Class in org.apache.spark.ml.regression
-
- GeneralizedLinearRegression.Inverse$ - Class in org.apache.spark.ml.regression
-
- GeneralizedLinearRegression.Link$ - Class in org.apache.spark.ml.regression
-
- GeneralizedLinearRegression.Log$ - Class in org.apache.spark.ml.regression
-
- GeneralizedLinearRegression.Logit$ - Class in org.apache.spark.ml.regression
-
- GeneralizedLinearRegression.Poisson$ - Class in org.apache.spark.ml.regression
-
Poisson exponential family distribution.
- GeneralizedLinearRegression.Probit$ - Class in org.apache.spark.ml.regression
-
- GeneralizedLinearRegression.Sqrt$ - Class in org.apache.spark.ml.regression
-
- GeneralizedLinearRegression.Tweedie$ - Class in org.apache.spark.ml.regression
-
- 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 Item
s 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, boolean) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- generateTreeString(int, Seq<Object>, StringBuilder, boolean, String, boolean) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- generateTreeString(int, Seq<Object>, StringBuilder, boolean, String, boolean) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- generateTreeString(int, Seq<Object>, StringBuilder, boolean, String, boolean) - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- generateTreeString$default$5() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- generateTreeString$default$5() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- generateTreeString$default$5() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- generateTreeString$default$5() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- generateTreeString$default$6() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- generateTreeString$default$6() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- generateTreeString$default$6() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- generateTreeString$default$6() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- 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() - 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.LinearSVC
-
- get(Param<T>) - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- 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.ClusteringEvaluator
-
- 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.BucketedRandomProjectionLSH
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- 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.FeatureHasher
-
- 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.Imputer
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.ImputerModel
-
- 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.MinHashLSH
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- 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
-
Deprecated.
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
-
- get(Param<T>) - Static method in class org.apache.spark.ml.feature.OneHotEncoderModel
-
- 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.VectorSizeHint
-
- 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>) - Static method in class org.apache.spark.ml.fpm.FPGrowth
-
- get(Param<T>) - Static method in class org.apache.spark.ml.fpm.FPGrowthModel
-
- 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(String) - Static method in class org.apache.spark.sql.jdbc.JdbcDialects
-
Fetch the JdbcDialect class corresponding to a given database url.
- 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(String) - Method in class org.apache.spark.sql.sources.v2.DataSourceOptions
-
Returns the option value to which the specified key is mapped, case-insensitively.
- get() - Method in interface org.apache.spark.sql.sources.v2.reader.DataReader
-
Return the current record.
- get() - Method in interface org.apache.spark.sql.streaming.GroupState
-
Get the state value if it exists, or throw NoSuchElementException.
- get(UUID) - 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(String) - 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(int, DataType) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
-
- get(int, DataType) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
-
- 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 ::
- getActiveSession() - Static method in class org.apache.spark.sql.SparkSession
-
Returns the active SparkSession for the current thread, returned by the builder.
- 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.
- getAggregationDepth() - Static method in class org.apache.spark.ml.classification.LinearSVC
-
- getAggregationDepth() - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- getAggregationDepth() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getAggregationDepth() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getAggregationDepth() - Method in interface org.apache.spark.ml.param.shared.HasAggregationDepth
-
- getAggregationDepth() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegression
-
- getAggregationDepth() - Static method in class org.apache.spark.ml.regression.AFTSurvivalRegressionModel
-
- getAggregationDepth() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- getAggregationDepth() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- 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
-
- getAllWithPrefix(String) - Method in class org.apache.spark.SparkConf
-
Get all parameters that start with prefix
- 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 at position i.
- 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.
- getArray(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
-
- getArray(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
-
- getArray(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
-
- getArray(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Returns the array type value for rowId.
- 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.
- getAssociationRulesFromFP(Dataset<?>, String, String, double, ClassTag<T>) - Static method in class org.apache.spark.ml.fpm.AssociationRules
-
Computes the association rules with confidence above minConfidence.
- 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
-
- getBinary(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
-
- getBinary(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
-
- getBinary(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
-
- getBinary(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Returns the binary type value for rowId.
- getBlock(BlockId) - Method in class org.apache.spark.storage.StorageStatus
-
Deprecated.
Return the given block stored in this block manager in O(1) time.
- getBlockSize() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- GetBlockStatus(BlockId, boolean) - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetBlockStatus
-
- GetBlockStatus$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetBlockStatus$
-
- 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, boolean) - Method in class org.apache.spark.sql.sources.v2.DataSourceOptions
-
Returns the boolean value to which the specified key is mapped,
or defaultValue if there is no mapping for the key.
- getBoolean(String) - Method in class org.apache.spark.sql.types.Metadata
-
Gets a Boolean.
- getBoolean(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
-
- getBoolean(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
-
- getBoolean(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
-
- getBoolean(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Returns the boolean type value for rowId.
- getBooleanArray(String) - Method in class org.apache.spark.sql.types.Metadata
-
Gets a Boolean array.
- getBooleans(int, int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Gets boolean type values from [rowId, rowId + count).
- getBucketLength() - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
-
- getBucketLength() - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- getByte(int) - Method in interface org.apache.spark.sql.Row
-
Returns the value at position i as a primitive byte.
- getByte(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
-
- getByte(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
-
- getByte(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
-
- getByte(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Returns the byte type value for rowId.
- getBytes(int, int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Gets byte type values from [rowId, rowId + count).
- 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
-
- getCatalystType(int, String, int, MetadataBuilder) - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
-
- getCategoricalCols() - Method in class org.apache.spark.ml.feature.FeatureHasher
-
- 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
-
- 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() - Method in interface org.apache.spark.ml.param.shared.HasCheckpointInterval
-
- 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
-
- getChild(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
-
- getClassifier() - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- getClassifier() - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- getColdStartStrategy() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- getColdStartStrategy() - Static method in class org.apache.spark.ml.recommendation.ALSModel
-
- getCollectSubModels() - Method in interface org.apache.spark.ml.param.shared.HasCollectSubModels
-
- getCollectSubModels() - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- getCollectSubModels() - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- getCombOp() - Static method in class org.apache.spark.util.random.StratifiedSamplingUtils
-
Returns the function used combine results returned by seqOp from different partitions.
- getComment() - Method in class org.apache.spark.sql.types.StructField
-
Return the comment of this StructField.
- getConf() - Method in class org.apache.spark.api.java.JavaSparkContext
-
Return a copy of this JavaSparkContext's configuration.
- getConf() - Static method in class org.apache.spark.ml.image.SamplePathFilter
-
- 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.
- getConfiguration() - Method in class org.apache.spark.input.PortableDataStream
-
- 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
-
- 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
-
- getCount() - Method in class org.apache.spark.storage.CountingWritableChannel
-
- getCurrentProcessingTimeMs() - Method in interface org.apache.spark.sql.streaming.GroupState
-
Get the current processing time as milliseconds in epoch time.
- 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.
- getCurrentWatermarkMs() - Method in interface org.apache.spark.sql.streaming.GroupState
-
Get the current event time watermark as milliseconds in epoch time.
- getData(Row) - Static method in class org.apache.spark.ml.image.ImageSchema
-
Gets the image data
- getDatabase(String) - Method in class org.apache.spark.sql.catalog.Catalog
-
Get the database with the specified 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.
- getDecimal(int, int, int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
-
- getDecimal(int, int, int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
-
- getDecimal(int, int, int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
-
- getDecimal(int, int, int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Returns the decimal type value for rowId.
- 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.LinearSVC
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- 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.ClusteringEvaluator
-
- 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.BucketedRandomProjectionLSH
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- 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.FeatureHasher
-
- 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.Imputer
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.ImputerModel
-
- 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.MinHashLSH
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- 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
-
Deprecated.
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.OneHotEncoderModel
-
- 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.VectorSizeHint
-
- 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>) - Static method in class org.apache.spark.ml.fpm.FPGrowth
-
- getDefault(Param<T>) - Static method in class org.apache.spark.ml.fpm.FPGrowthModel
-
- 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.
- getDefaultSession() - Static method in class org.apache.spark.sql.SparkSession
-
Returns the default SparkSession that is returned by the builder.
- getDegree() - Method in class org.apache.spark.ml.feature.PolynomialExpansion
-
- getDenseSizeInBytes() - Method in interface org.apache.spark.ml.linalg.Matrix
-
Gets the size of the dense representation of this `Matrix`.
- 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, Map<String, String>) - Static method in class org.apache.spark.SparkConf
-
Looks for available deprecated keys for the given config option, and return the first
value available.
- getDistributions() - Method in class org.apache.spark.status.LiveRDD
-
- 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, double) - Method in class org.apache.spark.sql.sources.v2.DataSourceOptions
-
Returns the double value to which the specified key is mapped,
or defaultValue if there is no mapping for the key.
- getDouble(String) - Method in class org.apache.spark.sql.types.Metadata
-
Gets a Double.
- getDouble(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
-
- getDouble(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
-
- getDouble(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
-
- getDouble(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Returns the double type value for rowId.
- getDoubleArray(String) - Method in class org.apache.spark.sql.types.Metadata
-
Gets a Double array.
- getDoubles(int, int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Gets double type values from [rowId, rowId + count).
- getDropLast() - Method in class org.apache.spark.ml.feature.OneHotEncoder
-
Deprecated.
- getDropLast() - Static method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
-
- getDropLast() - Static method in class org.apache.spark.ml.feature.OneHotEncoderModel
-
- getDynamicAllocationInitialExecutors(SparkConf) - Static method in class org.apache.spark.util.Utils
-
Return the initial number of executors for dynamic allocation.
- getElasticNetParam() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getElasticNetParam() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getElasticNetParam() - Method in interface org.apache.spark.ml.param.shared.HasElasticNetParam
-
- getElasticNetParam() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- getElasticNetParam() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- getEndOffset() - Method in interface org.apache.spark.sql.sources.v2.reader.streaming.MicroBatchReader
-
Return the specified (if explicitly set through setOffsetRange) or inferred end offset
for this reader.
- getEndTimeEpoch() - Method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
-
- getEpsilon() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- getEpsilon() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- 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
-
- GetExecutorEndpointRef(String) - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetExecutorEndpointRef
-
- GetExecutorEndpointRef$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetExecutorEndpointRef$
-
- 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.
- GetExecutorLossReason(String) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.GetExecutorLossReason
-
- GetExecutorLossReason$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.GetExecutorLossReason$
-
- 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
-
- getFamily() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getFamily() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getFamily() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- getFamily() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- getFdr() - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- getFdr() - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- 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.
- getFeaturesAndLabels(RFormulaModel, Dataset<?>) - Static method in class org.apache.spark.ml.r.RWrapperUtils
-
Get the feature names and original labels from the schema
of DataFrame transformed by RFormulaModel.
- 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.LinearSVC
-
- getFeaturesCol() - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- 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.evaluation.ClusteringEvaluator
-
- 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() - Method in interface org.apache.spark.ml.param.shared.HasFeaturesCol
-
- 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.GBTClassificationModel
-
- getFeatureSubsetStrategy() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- 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.GBTRegressionModel
-
- getFeatureSubsetStrategy() - Static method in class org.apache.spark.ml.regression.GBTRegressor
-
- 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
.
- getFileLength(File, SparkConf) - Static method in class org.apache.spark.util.Utils
-
Return the file length, if the file is compressed it returns the uncompressed file length.
- 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>, boolean) - 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.LinearSVC
-
- getFitIntercept() - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- getFitIntercept() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getFitIntercept() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getFitIntercept() - Method in interface org.apache.spark.ml.param.shared.HasFitIntercept
-
- 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.
- getFloat(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
-
- getFloat(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
-
- getFloat(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
-
- getFloat(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Returns the float type value for rowId.
- getFloats(int, int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Gets float type values from [rowId, rowId + count).
- getForceIndexLabel() - Static method in class org.apache.spark.ml.feature.RFormula
-
- getForceIndexLabel() - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- getFormattedClassName(Object) - Static method in class org.apache.spark.util.Utils
-
Return the class name of the given object, removing all dollar signs
- getFormula() - Static method in class org.apache.spark.ml.feature.RFormula
-
- getFormula() - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- getFpr() - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- getFpr() - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- getFunction(String) - Method in class org.apache.spark.sql.catalog.Catalog
-
Get the function with the specified name.
- getFunction(String, String) - Method in class org.apache.spark.sql.catalog.Catalog
-
Get the function with the specified name.
- getFwe() - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- getFwe() - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- 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.Bucketizer
-
- getHandleInvalid() - Static method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
-
- getHandleInvalid() - Static method in class org.apache.spark.ml.feature.OneHotEncoderModel
-
- getHandleInvalid() - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- getHandleInvalid() - Static method in class org.apache.spark.ml.feature.RFormula
-
- getHandleInvalid() - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- getHandleInvalid() - Static method in class org.apache.spark.ml.feature.StringIndexer
-
- getHandleInvalid() - Static method in class org.apache.spark.ml.feature.StringIndexerModel
-
- getHandleInvalid() - Static method in class org.apache.spark.ml.feature.VectorIndexer
-
- getHandleInvalid() - Static method in class org.apache.spark.ml.feature.VectorIndexerModel
-
- getHandleInvalid() - Static method in class org.apache.spark.ml.feature.VectorSizeHint
-
- getHandleInvalid() - Method in interface org.apache.spark.ml.param.shared.HasHandleInvalid
-
- getHeight(Row) - Static method in class org.apache.spark.ml.image.ImageSchema
-
Gets the height of the image
- getHiveWriteCompression(TableDesc, SQLConf) - Static method in class org.apache.spark.sql.hive.execution.HiveOptions
-
- 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
-
- getIndexValue(String, Object) - Method in class org.apache.spark.util.kvstore.KVTypeInfo
-
- 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
-
- getInitialTargetExecutorNumber(SparkConf, int) - Static method in class org.apache.spark.scheduler.cluster.SchedulerBackendUtils
-
Getting the initial target number of executors depends on whether dynamic allocation is
enabled.
- 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.BucketedRandomProjectionLSH
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- 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.MinHashLSH
-
- getInputCol() - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- 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
-
Deprecated.
- 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.VectorSizeHint
-
- 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
-
- getInputCol() - Method in interface org.apache.spark.ml.param.shared.HasInputCol
-
- getInputCols() - Static method in class org.apache.spark.ml.feature.Bucketizer
-
- getInputCols() - Static method in class org.apache.spark.ml.feature.FeatureHasher
-
- getInputCols() - Static method in class org.apache.spark.ml.feature.Imputer
-
- getInputCols() - Static method in class org.apache.spark.ml.feature.ImputerModel
-
- getInputCols() - Static method in class org.apache.spark.ml.feature.Interaction
-
- getInputCols() - Static method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
-
- getInputCols() - Static method in class org.apache.spark.ml.feature.OneHotEncoderModel
-
- getInputCols() - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- getInputCols() - Static method in class org.apache.spark.ml.feature.VectorAssembler
-
- getInputCols() - Method in interface org.apache.spark.ml.param.shared.HasInputCols
-
- getInputFilePath() - Static method in class org.apache.spark.rdd.InputFileBlockHolder
-
Returns the holding file name or empty string if it is unknown.
- 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.
- getInt(String, int) - Method in class org.apache.spark.sql.sources.v2.DataSourceOptions
-
Returns the integer value to which the specified key is mapped,
or defaultValue if there is no mapping for the key.
- getInt(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
-
- getInt(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
-
- getInt(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
-
- getInt(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Returns the int type value for rowId.
- getIntermediateStorageLevel() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- getInterval(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
-
- getInterval(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
-
- getInterval(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Returns the calendar interval type value for rowId.
- getInts(int, int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Gets int type values from [rowId, rowId + count).
- 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
-
- getItemsCol() - Static method in class org.apache.spark.ml.fpm.FPGrowth
-
- getItemsCol() - Static method in class org.apache.spark.ml.fpm.FPGrowthModel
-
- 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.
- getIteratorZipWithIndex(Iterator<T>, long) - Static method in class org.apache.spark.util.Utils
-
Generate a zipWithIndex iterator, avoid index value overflowing problem
in scala's zipWithIndex
- getJavaMap(int) - Method in interface org.apache.spark.sql.Row
-
Returns the value at position i of array type as a java.util.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
-
- getJDBCType(DataType) - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
-
- 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.LinearSVC
-
- getLabelCol() - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- 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() - Method in interface org.apache.spark.ml.param.shared.HasLabelCol
-
- 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
-
- getLayers() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- getLDAModel(double[]) - Method in interface org.apache.spark.mllib.clustering.LDAOptimizer
-
- 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"
- getLength() - Static method in class org.apache.spark.rdd.InputFileBlockHolder
-
Returns the length of the block being read, or -1 if it is unknown.
- getLink() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- getLink() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- getLinkPower() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- getLinkPower() - 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 java.util.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
-
- 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.
- getLocalUserJarsForShell(SparkConf) - Static method in class org.apache.spark.util.Utils
-
Return the local jar files which will be added to REPL's classpath.
- GetLocations(BlockId) - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetLocations
-
- GetLocations$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetLocations$
-
- GetLocationsAndStatus(BlockId) - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetLocationsAndStatus
-
- GetLocationsAndStatus$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetLocationsAndStatus$
-
- GetLocationsMultipleBlockIds(BlockId[]) - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetLocationsMultipleBlockIds
-
- GetLocationsMultipleBlockIds$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetLocationsMultipleBlockIds$
-
- 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, long) - Method in class org.apache.spark.sql.sources.v2.DataSourceOptions
-
Returns the long value to which the specified key is mapped,
or defaultValue if there is no mapping for the key.
- getLong(String) - Method in class org.apache.spark.sql.types.Metadata
-
Gets a Long.
- getLong(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
-
- getLong(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
-
- getLong(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
-
- getLong(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Returns the long type value for rowId.
- getLongArray(String) - Method in class org.apache.spark.sql.types.Metadata
-
Gets a Long array.
- getLongs(int, int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Gets long type values from [rowId, rowId + count).
- getLoss() - Method in interface org.apache.spark.ml.param.shared.HasLoss
-
- getLoss() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- getLoss() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- 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).
- getLowerBoundsOnCoefficients() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getLowerBoundsOnCoefficients() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getLowerBoundsOnIntercepts() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getLowerBoundsOnIntercepts() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getMap(int) - Method in interface org.apache.spark.sql.Row
-
Returns the value at position i of map type as a Scala Map.
- getMap(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
-
- getMap(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
-
- getMap(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
-
- getMap(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Returns the map type value for rowId.
- GetMatchingBlockIds(Function1<BlockId, Object>, boolean) - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetMatchingBlockIds
-
- GetMatchingBlockIds$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetMatchingBlockIds$
-
- 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.LinearSVC
-
- getMaxIter() - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- 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() - Method in interface org.apache.spark.ml.param.shared.HasMaxIter
-
- 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
-
- GetMemoryStatus$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetMemoryStatus$
-
- getMessage() - Method in exception org.apache.spark.sql.AnalysisException
-
- getMetadata(String) - Method in class org.apache.spark.sql.types.Metadata
-
Gets a Metadata.
- getMetadata(Class<T>) - Method in class org.apache.spark.util.kvstore.InMemoryStore
-
- getMetadata(Class<T>) - Method in interface org.apache.spark.util.kvstore.KVStore
-
Returns app-specific metadata from the store, or null if it's not currently set.
- getMetadata(Class<T>) - Method in class org.apache.spark.util.kvstore.LevelDB
-
- 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.ClusteringEvaluator
-
- 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
-
- getMinConfidence() - Static method in class org.apache.spark.ml.fpm.FPGrowth
-
- getMinConfidence() - Static method in class org.apache.spark.ml.fpm.FPGrowthModel
-
- 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 greater than or equal to 1.0
) or the minimum proportion
of points (if less than 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() - Static method in class org.apache.spark.ml.fpm.FPGrowth
-
- getMinSupport() - Static method in class org.apache.spark.ml.fpm.FPGrowthModel
-
- 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
-
- getMissingValue() - Static method in class org.apache.spark.ml.feature.Imputer
-
- getMissingValue() - Static method in class org.apache.spark.ml.feature.ImputerModel
-
- getMode(Row) - Static method in class org.apache.spark.ml.image.ImageSchema
-
Gets the OpenCV representation as an int
- 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
-
- getNChannels(Row) - Static method in class org.apache.spark.ml.image.ImageSchema
-
Gets the number of channels in the image
- 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
-
- getNumBucketsArray() - 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.FeatureHasher
-
- 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
-
- getNumHashTables() - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
-
- getNumHashTables() - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- getNumHashTables() - Static method in class org.apache.spark.ml.feature.MinHashLSH
-
- getNumHashTables() - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- 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.ml.fpm.FPGrowth
-
- getNumPartitions() - Static method in class org.apache.spark.ml.fpm.FPGrowthModel
-
- 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() - Method in class org.apache.spark.ml.classification.GBTClassificationModel
-
Number of trees in ensemble
- getNumTrees() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- getNumTrees() - Static method in class org.apache.spark.ml.classification.RandomForestClassifier
-
- getNumTrees() - Method in class org.apache.spark.ml.regression.GBTRegressionModel
-
Number of trees in ensemble
- 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
.
- 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
-
- getOffset() - Method in interface org.apache.spark.sql.sources.v2.reader.streaming.ContinuousDataReader
-
Get the offset of the current record, or the start offset if no records have been read.
- getOffsetCol() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- getOffsetCol() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- 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 interface org.apache.spark.sql.streaming.GroupState
-
Get the state value as a scala Option.
- getOption() - Method in class org.apache.spark.streaming.State
-
Get the state as a scala.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
-
- 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.LinearSVC
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- 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.ClusteringEvaluator
-
- 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.BucketedRandomProjectionLSH
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- 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.FeatureHasher
-
- 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.Imputer
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.ImputerModel
-
- 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.MinHashLSH
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- 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
-
Deprecated.
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.feature.OneHotEncoderModel
-
- 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.VectorSizeHint
-
- 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>) - Static method in class org.apache.spark.ml.fpm.FPGrowth
-
- getOrDefault(Param<T>) - Static method in class org.apache.spark.ml.fpm.FPGrowthModel
-
- 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.
- getOrigin(Row) - Static method in class org.apache.spark.ml.image.ImageSchema
-
Gets the origin of the image
- getOutputAttrGroupFromData(Dataset<?>, Seq<String>, Seq<String>, boolean) - Static method in class org.apache.spark.ml.feature.OneHotEncoderCommon
-
This method is called when we want to generate AttributeGroup
from actual data for
one-hot encoder.
- getOutputCol() - Static method in class org.apache.spark.ml.feature.Binarizer
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- 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.FeatureHasher
-
- 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.MinHashLSH
-
- getOutputCol() - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- 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
-
Deprecated.
- 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
-
- getOutputCol() - Method in interface org.apache.spark.ml.param.shared.HasOutputCol
-
- getOutputCols() - Static method in class org.apache.spark.ml.feature.Bucketizer
-
- getOutputCols() - Static method in class org.apache.spark.ml.feature.Imputer
-
- getOutputCols() - Static method in class org.apache.spark.ml.feature.ImputerModel
-
- getOutputCols() - Static method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
-
- getOutputCols() - Static method in class org.apache.spark.ml.feature.OneHotEncoderModel
-
- getOutputCols() - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- getOutputCols() - Method in interface org.apache.spark.ml.param.shared.HasOutputCols
-
- getOutputStream(String, Configuration) - Static method in class org.apache.spark.streaming.util.HdfsUtils
-
- getP() - Method in class org.apache.spark.ml.feature.Normalizer
-
- getParallelism() - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- getParallelism() - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- getParallelism() - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- 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.LinearSVC
-
- getParam(String) - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- 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.ClusteringEvaluator
-
- 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.BucketedRandomProjectionLSH
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- 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.FeatureHasher
-
- 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.Imputer
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.ImputerModel
-
- 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.MinHashLSH
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- 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
-
Deprecated.
- getParam(String) - Static method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
-
- getParam(String) - Static method in class org.apache.spark.ml.feature.OneHotEncoderModel
-
- 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.VectorSizeHint
-
- 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) - Static method in class org.apache.spark.ml.fpm.FPGrowth
-
- getParam(String) - Static method in class org.apache.spark.ml.fpm.FPGrowthModel
-
- 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.
- 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() - Method in class org.apache.spark.status.LiveRDD
-
- getPath() - Method in class org.apache.spark.input.PortableDataStream
-
- getPattern() - Method in class org.apache.spark.ml.feature.RegexTokenizer
-
- GetPeers(BlockManagerId) - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetPeers
-
- GetPeers$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetPeers$
-
- getPercentile() - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- getPercentile() - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- 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
- getPosition() - Method in class org.apache.spark.streaming.kinesis.KinesisInitialPositions.AtTimestamp
-
- getPosition() - Method in class org.apache.spark.streaming.kinesis.KinesisInitialPositions.Latest
-
- getPosition() - Method in class org.apache.spark.streaming.kinesis.KinesisInitialPositions.TrimHorizon
-
- 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.LinearSVC
-
- getPredictionCol() - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- 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.ClusteringEvaluator
-
- 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.fpm.FPGrowth
-
- getPredictionCol() - Static method in class org.apache.spark.ml.fpm.FPGrowthModel
-
- getPredictionCol() - Method in interface org.apache.spark.ml.param.shared.HasPredictionCol
-
- 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.GBTClassificationModel
-
- getProbabilityCol() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- 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.MultilayerPerceptronClassificationModel
-
- getProbabilityCol() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- 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
-
- getProbabilityCol() - Method in interface org.apache.spark.ml.param.shared.HasProbabilityCol
-
- 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
-
- getRandomSample(Seq<T>, int, Random) - Static method in class org.apache.spark.storage.BlockReplicationUtils
-
Get a random sample of size m from the elems
- 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.GBTClassificationModel
-
- getRawPredictionCol() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- getRawPredictionCol() - Static method in class org.apache.spark.ml.classification.LinearSVC
-
- getRawPredictionCol() - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- 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.MultilayerPerceptronClassificationModel
-
- getRawPredictionCol() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- 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
-
- getRawPredictionCol() - Method in interface org.apache.spark.ml.param.shared.HasRawPredictionCol
-
- 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.LinearSVC
-
- getRegParam() - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- getRegParam() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getRegParam() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getRegParam() - Method in interface org.apache.spark.ml.param.shared.HasRegParam
-
- 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()
.
- getRow(int) - Method in class org.apache.spark.sql.vectorized.ColumnarBatch
-
Returns the row in this batch at `rowId`.
- getRuns() - Method in class org.apache.spark.mllib.clustering.KMeans
-
- getScalingVec() - Method in class org.apache.spark.ml.feature.ElementwiseProduct
-
- getSchedulingMode() - Method in class org.apache.spark.SparkContext
-
Return current scheduling mode
- getSchemaQuery(String) - Method in class org.apache.spark.sql.jdbc.AggregatedDialect
-
- getSchemaQuery(String) - Static method in class org.apache.spark.sql.jdbc.DB2Dialect
-
- getSchemaQuery(String) - Static method in class org.apache.spark.sql.jdbc.DerbyDialect
-
- getSchemaQuery(String) - Method in class org.apache.spark.sql.jdbc.JdbcDialect
-
The SQL query that should be used to discover the schema of a table.
- getSchemaQuery(String) - Static method in class org.apache.spark.sql.jdbc.MsSqlServerDialect
-
- getSchemaQuery(String) - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
-
- getSchemaQuery(String) - Static method in class org.apache.spark.sql.jdbc.NoopDialect
-
- getSchemaQuery(String) - Static method in class org.apache.spark.sql.jdbc.OracleDialect
-
- getSchemaQuery(String) - Static method in class org.apache.spark.sql.jdbc.PostgresDialect
-
- getSchemaQuery(String) - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
-
- 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.BucketedRandomProjectionLSH
-
- getSeed() - Static method in class org.apache.spark.ml.feature.MinHashLSH
-
- getSeed() - Static method in class org.apache.spark.ml.feature.Word2Vec
-
- getSeed() - Static method in class org.apache.spark.ml.feature.Word2VecModel
-
- getSeed() - Method in interface org.apache.spark.ml.param.shared.HasSeed
-
- 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.
- getSelectorType() - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- getSelectorType() - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- 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.
- getShort(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
-
- getShort(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
-
- getShort(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
-
- getShort(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Returns the short type value for rowId.
- getShorts(int, int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Gets short type values from [rowId, rowId + count).
- getSimpleMessage() - Method in exception org.apache.spark.sql.AnalysisException
-
- getSimpleName(Class<?>) - Static method in class org.apache.spark.util.Utils
-
Safer than Class obj's getSimpleName which may throw Malformed class name error in scala.
- getSize() - Method in class org.apache.spark.ml.feature.VectorSizeHint
-
group getParam
- 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.
- getSizeInBytes() - Method in interface org.apache.spark.ml.linalg.Matrix
-
Gets the current size in bytes of this `Matrix`.
- 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() - Method in interface org.apache.spark.ml.param.shared.HasSolver
-
- 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.
- getSparseSizeInBytes(boolean) - Method in interface org.apache.spark.ml.linalg.Matrix
-
Gets the size of the minimal sparse representation of this `Matrix`.
- getSplit() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.SplitData
-
- getSplits() - Method in class org.apache.spark.ml.feature.Bucketizer
-
- getSplitsArray() - Method in class org.apache.spark.ml.feature.Bucketizer
-
- getStackTrace() - Static method in exception org.apache.spark.sql.AnalysisException
-
- 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.LinearSVC
-
- getStandardization() - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- getStandardization() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getStandardization() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getStandardization() - Method in interface org.apache.spark.ml.param.shared.HasStandardization
-
- getStandardization() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- getStandardization() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- getStartOffset() - Static method in class org.apache.spark.rdd.InputFileBlockHolder
-
Returns the starting offset of the block currently being read, or -1 if it is unknown.
- getStartOffset() - Method in interface org.apache.spark.sql.sources.v2.reader.streaming.ContinuousReader
-
Return the specified or inferred start offset for this reader.
- getStartOffset() - Method in interface org.apache.spark.sql.sources.v2.reader.streaming.MicroBatchReader
-
Returns the specified (if explicitly set through setOffsetRange) or inferred start offset
for this reader.
- 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
-
- getStatistics() - Method in interface org.apache.spark.sql.sources.v2.reader.SupportsReportStatistics
-
Returns the basic statistics of this data source.
- 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() - Method in interface org.apache.spark.ml.param.shared.HasStepSize
-
- 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
-
- GetStorageStatus$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.GetStorageStatus$
-
- getStrategy() - Static method in class org.apache.spark.ml.feature.Imputer
-
- getStrategy() - Static method in class org.apache.spark.ml.feature.ImputerModel
-
- 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.
- getStringIndexerOrderType() - Static method in class org.apache.spark.ml.feature.RFormula
-
- getStringIndexerOrderType() - Static method in class org.apache.spark.ml.feature.RFormulaModel
-
- getStringOrderType() - Static method in class org.apache.spark.ml.feature.StringIndexer
-
- getStringOrderType() - Static method in class org.apache.spark.ml.feature.StringIndexerModel
-
- getStruct(int) - Method in interface org.apache.spark.sql.Row
-
Returns the value at position i of struct type as a
Row
object.
- getStruct(int, int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
-
- getStruct(int, int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
-
- getStruct(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Returns the struct type value for rowId.
- 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
-
- getSystemProperties() - Static method in class org.apache.spark.util.Utils
-
Returns the system properties map that is thread-safe to iterator over.
- getTable(String) - Method in class org.apache.spark.sql.catalog.Catalog
-
Get the table or view with the specified name.
- getTable(String, String) - Method in class org.apache.spark.sql.catalog.Catalog
-
Get the table or view with the specified name in the specified database.
- getTableExistsQuery(String) - Method in class org.apache.spark.sql.jdbc.AggregatedDialect
-
- 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
-
- getTableExistsQuery(String) - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
-
- 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.
- getThreadDumpForThread(long) - Static method in class org.apache.spark.util.Utils
-
- getThreshold() - Static method in class org.apache.spark.ml.classification.LinearSVC
-
- getThreshold() - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- 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 interface org.apache.spark.ml.param.shared.HasThreshold
-
- 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() - Static method in class org.apache.spark.ml.classification.GBTClassificationModel
-
- getThresholds() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- 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.MultilayerPerceptronClassificationModel
-
- getThresholds() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- 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
-
- getThresholds() - Method in interface org.apache.spark.ml.param.shared.HasThresholds
-
- 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.
- getTimestamp() - Method in class org.apache.spark.streaming.kinesis.KinesisInitialPositions.AtTimestamp
-
- getTimeZoneOffset() - Static method in class org.apache.spark.ui.UIUtils
-
- GETTING_RESULT_TIME() - Static method in class org.apache.spark.status.TaskIndexNames
-
- 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.
- gettingResultTime() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
-
- gettingResultTime(TaskData) - Static method in class org.apache.spark.status.AppStatusUtils
-
- gettingResultTime(long, long, long) - Static method in class org.apache.spark.status.AppStatusUtils
-
- getTol() - Static method in class org.apache.spark.ml.classification.LinearSVC
-
- getTol() - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- 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() - Method in interface org.apache.spark.ml.param.shared.HasTol
-
- 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
-
- getTopologyForHost(String) - Method in class org.apache.spark.storage.DefaultTopologyMapper
-
- getTopologyForHost(String) - Method in class org.apache.spark.storage.FileBasedTopologyMapper
-
- getTopologyForHost(String) - Method in class org.apache.spark.storage.TopologyMapper
-
Gets the topology information given the host name
- 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
-
- getTruncateQuery(String) - Method in class org.apache.spark.sql.jdbc.AggregatedDialect
-
- getTruncateQuery(String) - Static method in class org.apache.spark.sql.jdbc.DB2Dialect
-
- getTruncateQuery(String) - Static method in class org.apache.spark.sql.jdbc.DerbyDialect
-
- getTruncateQuery(String) - Method in class org.apache.spark.sql.jdbc.JdbcDialect
-
The SQL query that should be used to truncate a table.
- getTruncateQuery(String) - Static method in class org.apache.spark.sql.jdbc.MsSqlServerDialect
-
- getTruncateQuery(String) - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
-
- getTruncateQuery(String) - Static method in class org.apache.spark.sql.jdbc.NoopDialect
-
- getTruncateQuery(String) - Static method in class org.apache.spark.sql.jdbc.OracleDialect
-
- getTruncateQuery(String) - Static method in class org.apache.spark.sql.jdbc.PostgresDialect
-
The SQL query used to truncate a table.
- getTruncateQuery(String) - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
-
- 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.
- getUiRoot(ServletContext) - Static method in class org.apache.spark.status.api.v1.UIRootFromServletContext
-
- 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).
- getUpperBoundsOnCoefficients() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getUpperBoundsOnCoefficients() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- getUpperBoundsOnIntercepts() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- getUpperBoundsOnIntercepts() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- 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) - Static method in class org.apache.spark.util.Utils
-
Return the jar files pointed by the "spark.jars" property.
- getUTF8String(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
-
- getUTF8String(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
-
- getUTF8String(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
-
- getUTF8String(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Returns the string type value for rowId.
- 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 consisting of names and values for the requested fieldNames
For primitive types if value is null it returns 'zero value' specific for primitive
ie.
- getVarianceCol() - Method in interface org.apache.spark.ml.param.shared.HasVarianceCol
-
- getVarianceCol() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressionModel
-
- getVarianceCol() - Static method in class org.apache.spark.ml.regression.DecisionTreeRegressor
-
- getVariancePower() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- getVariancePower() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- 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.LinearSVC
-
- getWeightCol() - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- 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.classification.NaiveBayes
-
- getWeightCol() - Static method in class org.apache.spark.ml.classification.NaiveBayesModel
-
- getWeightCol() - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- getWeightCol() - Static method in class org.apache.spark.ml.classification.OneVsRestModel
-
- getWeightCol() - Method in interface org.apache.spark.ml.param.shared.HasWeightCol
-
- 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
-
- getWidth(Row) - Static method in class org.apache.spark.ml.image.ImageSchema
-
Gets the width of the image
- 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$.Data - Class in org.apache.spark.mllib.classification.impl
-
Model data for import/export
- GLMRegressionModel - Class in org.apache.spark.mllib.regression.impl
-
Helper methods for import/export of GLM regression models.
- GLMRegressionModel() - Constructor for class org.apache.spark.mllib.regression.impl.GLMRegressionModel
-
- GLMRegressionModel.SaveLoadV1_0$ - Class in org.apache.spark.mllib.regression.impl
-
- GLMRegressionModel.SaveLoadV1_0$.Data - Class in org.apache.spark.mllib.regression.impl
-
Model data for model import/export
- 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.regression.AFTAggregator
-
- 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
-
- 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
Graph
s 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.
- GroupByType$() - Constructor for class org.apache.spark.sql.RelationalGroupedDataset.GroupByType$
-
- 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.
- GroupState<S> - Interface in org.apache.spark.sql.streaming
-
:: Experimental ::
- GroupStateTimeout - Class in org.apache.spark.sql.streaming
-
Represents the type of timeouts possible for the Dataset operations
`mapGroupsWithState` and `flatMapGroupsWithState`.
- GroupStateTimeout() - Constructor for class org.apache.spark.sql.streaming.GroupStateTimeout
-
- 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 is greater than 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 is greater than or equal to 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 that persists across restarts from checkpoint data.
- id() - Method in class org.apache.spark.sql.streaming.StreamingQueryListener.QueryStartedEvent
-
- id() - Method in class org.apache.spark.sql.streaming.StreamingQueryListener.QueryTerminatedEvent
-
- id() - Method in class org.apache.spark.sql.streaming.StreamingQueryProgress
-
- 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 ::
- Identity$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Identity$
-
- 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.
- 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.
- ifPartitionNotExists() - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- imageFields() - Static method in class org.apache.spark.ml.image.ImageSchema
-
- ImageSchema - Class in org.apache.spark.ml.image
-
:: Experimental ::
Defines the image schema and methods to read and manipulate images.
- ImageSchema() - Constructor for class org.apache.spark.ml.image.ImageSchema
-
- imageSchema() - Static method in class org.apache.spark.ml.image.ImageSchema
-
DataFrame with a single column of images named "image" (nullable)
- 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
- implicits$() - Constructor for class org.apache.spark.sql.SparkSession.implicits$
-
- implicits$() - Constructor for class org.apache.spark.sql.SQLContext.implicits$
-
- 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$.NodeData
-
- impurity() - Method in class org.apache.spark.mllib.tree.model.InformationGainStats
-
- impurity() - Method in class org.apache.spark.mllib.tree.model.Node
-
- impurityStats() - Method in class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData
-
- Imputer - Class in org.apache.spark.ml.feature
-
:: Experimental ::
Imputation estimator for completing missing values, either using the mean or the median
of the columns in which the missing values are located.
- Imputer(String) - Constructor for class org.apache.spark.ml.feature.Imputer
-
- Imputer() - Constructor for class org.apache.spark.ml.feature.Imputer
-
- ImputerModel - Class in org.apache.spark.ml.feature
-
:: Experimental ::
Model fitted by
Imputer
.
- In() - Static method in class org.apache.spark.graphx.EdgeDirection
-
Edges arriving at a vertex.
- In - Class in org.apache.spark.sql.sources
-
A filter that evaluates to true
iff the attribute evaluates to one of the values in the array.
- In(String, Object[]) - Constructor for class org.apache.spark.sql.sources.In
-
- INACTIVE() - Static method in class org.apache.spark.streaming.scheduler.ReceiverState
-
- inArray(Object) - Static method in class org.apache.spark.ml.param.ParamValidators
-
Check for value in an allowed set of values.
- inArray(List<T>) - Static method in class org.apache.spark.ml.param.ParamValidators
-
Check for value in an allowed set of values.
- InBlock$() - Constructor for class org.apache.spark.ml.recommendation.ALS.InBlock$
-
- IncompatibleMergeException - Exception in org.apache.spark.util.sketch
-
- IncompatibleMergeException(String) - Constructor for exception org.apache.spark.util.sketch.IncompatibleMergeException
-
- incrementFetchedPartitions(int) - Static method in class org.apache.spark.metrics.source.HiveCatalogMetrics
-
- incrementFileCacheHits(int) - Static method in class org.apache.spark.metrics.source.HiveCatalogMetrics
-
- incrementFilesDiscovered(int) - Static method in class org.apache.spark.metrics.source.HiveCatalogMetrics
-
- incrementHiveClientCalls(int) - Static method in class org.apache.spark.metrics.source.HiveCatalogMetrics
-
- incrementParallelListingJobCount(int) - Static method in class org.apache.spark.metrics.source.HiveCatalogMetrics
-
- 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$
-
- INDETERMINATE() - Static method in class org.apache.spark.rdd.DeterministicLevel
-
- 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
-
The index of this task within its task set.
- index() - Method in class org.apache.spark.status.api.v1.TaskData
-
- index(String) - Method in class org.apache.spark.util.kvstore.KVStoreView
-
Iterates according to the given index.
- 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.
- indexName(String) - Static method in class org.apache.spark.ui.jobs.ApiHelper
-
- 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(String) - Constructor for class org.apache.spark.ml.feature.IndexToString
-
- 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
-
- indices() - Method in class org.apache.spark.util.kvstore.KVTypeInfo
-
- inferSchema(SparkSession, Map<String, String>, Seq<FileStatus>) - Method in class org.apache.spark.sql.hive.execution.HiveFileFormat
-
- inferSchema(CatalogTable) - Static method in class org.apache.spark.sql.hive.HiveUtils
-
Infers the schema for Hive serde tables and returns the CatalogTable with the inferred schema.
- inferSchema(SparkSession, Map<String, String>, Seq<FileStatus>) - Method in class org.apache.spark.sql.hive.orc.OrcFileFormat
-
- info() - Method in class org.apache.spark.status.LiveRDD
-
- info() - Method in class org.apache.spark.status.LiveStage
-
- info() - Method in class org.apache.spark.status.LiveTask
-
- 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$.NodeData
-
- InformationGainStats - Class in org.apache.spark.mllib.tree.model
-
:: DeveloperApi ::
Information gain statistics for each split
param: gain information gain value
param: impurity current node impurity
param: leftImpurity left node impurity
param: rightImpurity right node impurity
param: leftPredict left node predict
param: rightPredict right node predict
- InformationGainStats(double, double, double, double, Predict, Predict) - Constructor for class org.apache.spark.mllib.tree.model.InformationGainStats
-
- init() - Static method in class org.apache.spark.sql.types.StructType
-
- initcap(Column) - Static method in class org.apache.spark.sql.functions
-
Returns a new string column by converting the first letter of each word to uppercase.
- initCause(Throwable) - Static method in exception org.apache.spark.sql.AnalysisException
-
- initDaemon(Logger) - Static method in class org.apache.spark.util.Utils
-
Utility function that should be called early in main()
for daemons to set up some common
diagnostic state.
- initHadoopOutputMetrics(TaskContext) - Static method in class org.apache.spark.internal.io.SparkHadoopWriterUtils
-
- initialHash() - Method in class org.apache.spark.rdd.DefaultPartitionCoalescer
-
- initialize(double, double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Binomial$
-
- 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
-
- initializeLogging(boolean, boolean) - Method in interface org.apache.spark.internal.Logging
-
- initializeLogIfNecessary(boolean) - Method in interface org.apache.spark.internal.Logging
-
- initializeLogIfNecessary(boolean, boolean) - Method in interface org.apache.spark.internal.Logging
-
- 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
-
- initOutputFormat(JobContext) - Method in class org.apache.spark.internal.io.HadoopWriteConfigUtil
-
- 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
-
- initWriter(TaskAttemptContext, int) - Method in class org.apache.spark.internal.io.HadoopWriteConfigUtil
-
- injectCheckRule(Function1<SparkSession, Function1<LogicalPlan, BoxedUnit>>) - Method in class org.apache.spark.sql.SparkSessionExtensions
-
Inject an check analysis
Rule
builder into the
SparkSession
.
- injectOptimizerRule(Function1<SparkSession, Rule<LogicalPlan>>) - Method in class org.apache.spark.sql.SparkSessionExtensions
-
- injectParser(Function2<SparkSession, ParserInterface, ParserInterface>) - Method in class org.apache.spark.sql.SparkSessionExtensions
-
- injectPlannerStrategy(Function1<SparkSession, SparkStrategy>) - Method in class org.apache.spark.sql.SparkSessionExtensions
-
- injectPostHocResolutionRule(Function1<SparkSession, Rule<LogicalPlan>>) - Method in class org.apache.spark.sql.SparkSessionExtensions
-
- injectResolutionRule(Function1<SparkSession, Rule<LogicalPlan>>) - Method in class org.apache.spark.sql.SparkSessionExtensions
-
Inject an analyzer resolution
Rule
builder into the
SparkSession
.
- InMemoryStore - Class in org.apache.spark.util.kvstore
-
Implementation of KVStore that keeps data deserialized in memory.
- InMemoryStore() - Constructor for class org.apache.spark.util.kvstore.InMemoryStore
-
- 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.
- InProcessLauncher - Class in org.apache.spark.launcher
-
In-process launcher for Spark applications.
- InProcessLauncher() - Constructor for class org.apache.spark.launcher.InProcessLauncher
-
- input() - Method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- INPUT() - Static method in class org.apache.spark.ui.ToolTips
-
- input$() - Constructor for class org.apache.spark.InternalAccumulator.input$
-
- 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_FORMAT() - Static method in class org.apache.spark.sql.hive.execution.HiveOptions
-
- INPUT_METRICS_PREFIX() - Static method in class org.apache.spark.InternalAccumulator
-
- INPUT_RECORDS() - Static method in class org.apache.spark.status.TaskIndexNames
-
- INPUT_SIZE() - Static method in class org.apache.spark.status.TaskIndexNames
-
- inputBytes() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
-
- inputBytes() - Method in class org.apache.spark.status.api.v1.StageData
-
- inputCol() - Static method in class org.apache.spark.ml.feature.Binarizer
-
- inputCol() - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
-
- inputCol() - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- 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.MinHashLSH
-
- inputCol() - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- 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
-
Deprecated.
- 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.VectorSizeHint
-
- 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
-
- inputCol() - Method in interface org.apache.spark.ml.param.shared.HasInputCol
-
Param for input column name.
- inputCols() - Static method in class org.apache.spark.ml.feature.Bucketizer
-
- inputCols() - Static method in class org.apache.spark.ml.feature.FeatureHasher
-
- inputCols() - Static method in class org.apache.spark.ml.feature.Imputer
-
- inputCols() - Static method in class org.apache.spark.ml.feature.ImputerModel
-
- inputCols() - Static method in class org.apache.spark.ml.feature.Interaction
-
- inputCols() - Static method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
-
- inputCols() - Static method in class org.apache.spark.ml.feature.OneHotEncoderModel
-
- inputCols() - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- inputCols() - Static method in class org.apache.spark.ml.feature.VectorAssembler
-
- inputCols() - Method in interface org.apache.spark.ml.param.shared.HasInputCols
-
Param for input column names.
- 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
-
- InputFileBlockHolder - Class in org.apache.spark.rdd
-
This holds file names of the current Spark task.
- InputFileBlockHolder() - Constructor for class org.apache.spark.rdd.InputFileBlockHolder
-
- 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.hive.execution.HiveOptions
-
- 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
-
- inputRecords() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
-
- inputRecords() - Method in class org.apache.spark.status.api.v1.StageData
-
- inputRowFormat() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- inputRowFormatMap() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- inputRowsPerSecond() - Method in class org.apache.spark.sql.streaming.SourceProgress
-
- inputRowsPerSecond() - Method in class org.apache.spark.sql.streaming.StreamingQueryProgress
-
The aggregate (across all sources) rate of data arriving.
- 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.InsertIntoHiveDirCommand
-
- inputSet() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- inputSet() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- inputSize() - Method in class org.apache.spark.status.api.v1.streaming.BatchInfo
-
- 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
-
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.
- InsertIntoHiveDirCommand - Class in org.apache.spark.sql.hive.execution
-
Command for writing the results of query
to file system.
- InsertIntoHiveDirCommand(boolean, CatalogStorageFormat, LogicalPlan, boolean, Seq<String>) - Constructor for class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- InsertIntoHiveTable - Class in org.apache.spark.sql.hive.execution
-
Command for writing data out to a Hive table.
- InsertIntoHiveTable(CatalogTable, Map<String, Option<String>>, LogicalPlan, boolean, boolean, Seq<String>) - 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
-
- 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
-
- instantiate(String, String, String, boolean) - Static method in class org.apache.spark.internal.io.FileCommitProtocol
-
Instantiates a FileCommitProtocol using the given className.
- 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
-
- intAccumulator(int, String) - Method in class org.apache.spark.api.java.JavaSparkContext
-
- IntAccumulatorParam$() - Constructor for class org.apache.spark.AccumulatorParam.IntAccumulatorParam$
-
Deprecated.
- 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
-
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.LinearSVCModel
-
- intercept() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
The model intercept for "binomial" logistic regression.
- 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
-
- interceptVector() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- 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.output$ - Class in org.apache.spark
-
- InternalAccumulator.shuffleRead$ - Class in org.apache.spark
-
- InternalAccumulator.shuffleWrite$ - Class in org.apache.spark
-
- InternalNode - Class in org.apache.spark.ml.tree
-
Internal Decision Tree node.
- 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$3(RDD<T>, Partitioner) - Static method in class org.apache.spark.rdd.UnionRDD
-
- intervalMs() - Method in class org.apache.spark.sql.streaming.ProcessingTime
-
Deprecated.
- IntParam - Class in org.apache.spark.ml.param
-
:: DeveloperApi ::
Specialized version of Param[Int]
for Java.
- IntParam(String, String, String, Function1<Object, Object>) - Constructor for class org.apache.spark.ml.param.IntParam
-
- IntParam(String, String, String) - Constructor for class org.apache.spark.ml.param.IntParam
-
- IntParam(Identifiable, String, String, Function1<Object, Object>) - Constructor for class org.apache.spark.ml.param.IntParam
-
- IntParam(Identifiable, String, String) - Constructor for class org.apache.spark.ml.param.IntParam
-
- IntParam - Class in org.apache.spark.util
-
An extractor object for parsing strings into integers.
- IntParam() - Constructor for class org.apache.spark.util.IntParam
-
- invalidateSerializedMapOutputStatusCache() - Method in class org.apache.spark.ShuffleStatus
-
Clears the cached serialized map output statuses.
- invalidateStatsCache() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- invalidateStatsCache() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- invalidateStatsCache() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- inverse() - Method in class org.apache.spark.ml.feature.DCT
-
Indicates whether to perform the inverse DCT (true) or forward DCT (false).
- inverse(double[], int) - Static method in class org.apache.spark.mllib.linalg.CholeskyDecomposition
-
Computes the inverse of a real symmetric positive definite matrix A
using the Cholesky factorization A = U**T*U.
- Inverse$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Inverse$
-
- 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
-
- ioEncryptionKey() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.SparkAppConfig
-
- ioschema() - Method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- 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
-
Returns true
if this query is actively running.
- isActive() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
-
- isActive() - Method in class org.apache.spark.status.api.v1.streaming.ReceiverInfo
-
- isActive() - Method in class org.apache.spark.status.LiveExecutor
-
- 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.
- isBlacklisted() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
-
- isBlacklisted() - Method in class org.apache.spark.status.LiveExecutor
-
- 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.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
-
- isCascadingTruncateTable() - Method in class org.apache.spark.sql.jdbc.AggregatedDialect
-
- isCascadingTruncateTable() - Static method in class org.apache.spark.sql.jdbc.DB2Dialect
-
- isCascadingTruncateTable() - Static method in class org.apache.spark.sql.jdbc.DerbyDialect
-
- isCascadingTruncateTable() - Method in class org.apache.spark.sql.jdbc.JdbcDialect
-
Return Some[true] iff TRUNCATE TABLE
causes cascading default.
- isCascadingTruncateTable() - Static method in class org.apache.spark.sql.jdbc.MsSqlServerDialect
-
- isCascadingTruncateTable() - Static method in class org.apache.spark.sql.jdbc.MySQLDialect
-
- isCascadingTruncateTable() - Static method in class org.apache.spark.sql.jdbc.NoopDialect
-
- isCascadingTruncateTable() - Static method in class org.apache.spark.sql.jdbc.OracleDialect
-
- isCascadingTruncateTable() - Static method in class org.apache.spark.sql.jdbc.PostgresDialect
-
- isCascadingTruncateTable() - Static method in class org.apache.spark.sql.jdbc.TeradataDialect
-
- 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
-
- isCliSessionState() - Static method in class org.apache.spark.sql.hive.HiveUtils
-
Check current Thread's SessionState type
- isColMajor() - Method in interface org.apache.spark.ml.linalg.Matrix
-
Indicates whether the values backing this matrix are arranged in column major order.
- 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.
- isDataAvailable() - Method in class org.apache.spark.sql.streaming.StreamingQueryStatus
-
- 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.LinearSVC
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- 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.ClusteringEvaluator
-
- 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.BucketedRandomProjectionLSH
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- 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.FeatureHasher
-
- 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.Imputer
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.ImputerModel
-
- 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.MinHashLSH
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- 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
-
Deprecated.
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.feature.OneHotEncoderModel
-
- 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.VectorSizeHint
-
- 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<?>) - Static method in class org.apache.spark.ml.fpm.FPGrowth
-
- isDefined(Param<?>) - Static method in class org.apache.spark.ml.fpm.FPGrowthModel
-
- 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.
- isFile(Path) - Static method in class org.apache.spark.ml.image.SamplePathFilter
-
- 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.ClusteringEvaluator
-
- 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).
- isLocal() - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- 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.
- isNullAt(int) - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
-
- isNullAt(int) - Method in class org.apache.spark.sql.vectorized.ColumnarArray
-
- isNullAt(int) - Method in class org.apache.spark.sql.vectorized.ColumnarRow
-
- isNullAt(int) - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Returns whether the value at rowId 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
-
- isOpen() - Method in class org.apache.spark.storage.CountingWritableChannel
-
- 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.
- isOutputSpecValidationEnabled(SparkConf) - Static method in class org.apache.spark.internal.io.SparkHadoopWriterUtils
-
- 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.
- isRowMajor() - Method in interface org.apache.spark.ml.linalg.Matrix
-
Indicates whether the values backing this matrix are arranged in row major order.
- isRunningLocally() - Method in class org.apache.spark.TaskContext
-
- 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.LinearSVC
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- 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.ClusteringEvaluator
-
- 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.BucketedRandomProjectionLSH
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- 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.FeatureHasher
-
- 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.Imputer
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.ImputerModel
-
- 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.MinHashLSH
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- 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
-
Deprecated.
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.feature.OneHotEncoderModel
-
- 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.VectorSizeHint
-
- 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<?>) - Static method in class org.apache.spark.ml.fpm.FPGrowth
-
- isSet(Param<?>) - Static method in class org.apache.spark.ml.fpm.FPGrowthModel
-
- 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
-
- isStreaming() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- isStreaming() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- 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.
- isTraceEnabled() - Method in interface org.apache.spark.internal.Logging
-
- 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
-
- isTriggerActive() - Method in class org.apache.spark.sql.streaming.StreamingQueryStatus
-
- 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
-
Returns false if this accumulator instance has any values in it.
- isZero() - Method in class org.apache.spark.util.DoubleAccumulator
-
Returns false if this accumulator has had any values added to it or the sum is non-zero.
- isZero() - Method in class org.apache.spark.util.LegacyAccumulatorWrapper
-
- isZero() - Method in class org.apache.spark.util.LongAccumulator
-
Returns false if this accumulator has had any values added to it or the sum is non-zero.
- 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
-
- itemsCol() - Static method in class org.apache.spark.ml.fpm.FPGrowth
-
- itemsCol() - Static method in class org.apache.spark.ml.fpm.FPGrowthModel
-
- 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
-
- iterator() - Method in class org.apache.spark.status.RDDPartitionSeq
-
- IV_LENGTH_IN_BYTES() - Static method in class org.apache.spark.security.CryptoStreamUtils
-
- 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() - 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.LinearSVC
-
- labelCol() - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- 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() - Method in class org.apache.spark.ml.classification.LogisticRegressionSummaryImpl
-
- 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() - Method in interface org.apache.spark.ml.param.shared.HasLabelCol
-
Param for label column name.
- 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
-
Class that represents the features and label of a data point.
- 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 interface org.apache.spark.ml.classification.LogisticRegressionSummary
-
Returns the sequence of labels in ascending order.
- 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
-
- 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(Object) - Method in class org.apache.spark.util.kvstore.KVStoreView
-
Stops iteration at the given value of the chosen index (inclusive).
- 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.status.api.v1.streaming.ReceiverInfo
-
- lastError() - Method in class org.apache.spark.streaming.scheduler.ReceiverInfo
-
- lastErrorMessage() - Method in class org.apache.spark.status.api.v1.streaming.ReceiverInfo
-
- lastErrorMessage() - Method in class org.apache.spark.streaming.scheduler.ReceiverInfo
-
- lastErrorTime() - Method in class org.apache.spark.status.api.v1.streaming.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
-
- lastProgress() - Method in interface org.apache.spark.sql.streaming.StreamingQuery
-
- lastStageNameAndDescription(org.apache.spark.status.AppStatusStore, JobData) - Static method in class org.apache.spark.ui.jobs.ApiHelper
-
- lastUpdate() - Method in class org.apache.spark.status.LiveRDDDistribution
-
- lastUpdated() - Method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
-
- Latest() - Constructor for class org.apache.spark.streaming.kinesis.KinesisInitialPositions.Latest
-
- 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.
- LAUNCH_TIME() - Static method in class org.apache.spark.status.TaskIndexNames
-
- LAUNCHING() - Static method in class org.apache.spark.TaskState
-
- LaunchTask(org.apache.spark.util.SerializableBuffer) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.LaunchTask
-
- LaunchTask$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.LaunchTask$
-
- 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
-
Latent Dirichlet Allocation (LDA), a topic model designed for text documents.
- 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
-
- 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.
- 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 character length of a given string or number of bytes of a binary string.
- length() - Method in interface org.apache.spark.sql.Row
-
Number of elements in the Row.
- length() - Method in class org.apache.spark.sql.types.CharType
-
- length() - Method in class org.apache.spark.sql.types.HiveStringType
-
- length() - Method in class org.apache.spark.sql.types.StructType
-
- length() - Method in class org.apache.spark.sql.types.VarcharType
-
- length() - Method in class org.apache.spark.status.RDDPartitionSeq
-
- 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
-
- LevelDB - Class in org.apache.spark.util.kvstore
-
Implementation of KVStore that uses LevelDB as the underlying data store.
- LevelDB(File) - Constructor for class org.apache.spark.util.kvstore.LevelDB
-
- LevelDB(File, KVStoreSerializer) - Constructor for class org.apache.spark.util.kvstore.LevelDB
-
- LevelDB.TypeAliases - Class in org.apache.spark.util.kvstore
-
Needs to be public for Jackson.
- 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
-
- LinearSVC - Class in org.apache.spark.ml.classification
-
:: Experimental ::
- LinearSVC(String) - Constructor for class org.apache.spark.ml.classification.LinearSVC
-
- LinearSVC() - Constructor for class org.apache.spark.ml.classification.LinearSVC
-
- LinearSVCModel - Class in org.apache.spark.ml.classification
-
:: Experimental ::
Linear SVM Model trained by
LinearSVC
- 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
-
- Link$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Link$
-
- linkPower() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- linkPower() - 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/view or temporary view.
- listColumns(String, String) - Method in class org.apache.spark.sql.catalog.Catalog
-
Returns a list of columns for the given table/view in the specified database.
- listDatabases() - Method in class org.apache.spark.sql.catalog.Catalog
-
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.
- 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/views in the current database.
- listTables(String) - Method in class org.apache.spark.sql.catalog.Catalog
-
Returns a list of tables/views 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
-
- LIVE_ENTITY_UPDATE_PERIOD() - Static method in class org.apache.spark.status.config
-
- LiveEntityHelpers - Class in org.apache.spark.status
-
- LiveEntityHelpers() - Constructor for class org.apache.spark.status.LiveEntityHelpers
-
- LiveExecutor - Class in org.apache.spark.status
-
- LiveExecutor(String, long) - Constructor for class org.apache.spark.status.LiveExecutor
-
- LiveExecutorStageSummary - Class in org.apache.spark.status
-
- LiveExecutorStageSummary(int, int, String) - Constructor for class org.apache.spark.status.LiveExecutorStageSummary
-
- LiveJob - Class in org.apache.spark.status
-
- LiveJob(int, String, Option<Date>, Seq<Object>, Option<String>, int) - Constructor for class org.apache.spark.status.LiveJob
-
- LiveRDD - Class in org.apache.spark.status
-
- LiveRDD(RDDInfo) - Constructor for class org.apache.spark.status.LiveRDD
-
- LiveRDDDistribution - Class in org.apache.spark.status
-
- LiveRDDDistribution(LiveExecutor) - Constructor for class org.apache.spark.status.LiveRDDDistribution
-
- LiveRDDPartition - Class in org.apache.spark.status
-
- LiveRDDPartition(String) - Constructor for class org.apache.spark.status.LiveRDDPartition
-
- LiveStage - Class in org.apache.spark.status
-
- LiveStage() - Constructor for class org.apache.spark.status.LiveStage
-
- LiveTask - Class in org.apache.spark.status
-
- LiveTask(TaskInfo, int, int, Option<Object>) - Constructor for class org.apache.spark.status.LiveTask
-
- 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.LinearSVC
-
- load(String) - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- 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.ClusteringEvaluator
-
- 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.BucketedRandomProjectionLSH
-
- load(String) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- 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.FeatureHasher
-
- 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.Imputer
-
- load(String) - Static method in class org.apache.spark.ml.feature.ImputerModel
-
- 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.MinHashLSH
-
- load(String) - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- 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
-
Deprecated.
- load(String) - Static method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
-
- load(String) - Static method in class org.apache.spark.ml.feature.OneHotEncoderModel
-
- 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.VectorSizeHint
-
- 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.fpm.FPGrowth
-
- load(String) - Static method in class org.apache.spark.ml.fpm.FPGrowthModel
-
- 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
-
- load(String, String) - Method in class org.apache.spark.sql.SQLContext
-
- load(String, Map<String, String>) - Method in class org.apache.spark.sql.SQLContext
-
- load(String, Map<String, String>) - Method in class org.apache.spark.sql.SQLContext
-
- load(String, StructType, Map<String, String>) - Method in class org.apache.spark.sql.SQLContext
-
- load(String, StructType, Map<String, String>) - Method in class org.apache.spark.sql.SQLContext
-
- load() - Method in class org.apache.spark.sql.streaming.DataStreamReader
-
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
-
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.
- Loader<M extends Saveable> - Interface in org.apache.spark.mllib.util
-
:: DeveloperApi ::
- loadExtensions(Class<T>, Seq<String>, SparkConf) - Static method in class org.apache.spark.util.Utils
-
Create instances of extension classes.
- 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
-
- localBytesRead() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetrics
-
- localCanonicalHostName() - Static method in class org.apache.spark.util.Utils
-
Get the local machine's FQDN.
- 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
-
- localCheckpoint() - Method in class org.apache.spark.sql.Dataset
-
Eagerly locally checkpoints a Dataset and return the new Dataset.
- localCheckpoint(boolean) - Method in class org.apache.spark.sql.Dataset
-
Locally checkpoints a Dataset and return the new Dataset.
- 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.
- LOCALITY() - Static method in class org.apache.spark.status.TaskIndexNames
-
- localityAwareTasks() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RequestExecutors
-
- localitySummary() - Method in class org.apache.spark.status.LiveStage
-
- 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
-
Local (non-distributed) model fitted by
LDA
.
- 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
-
- location() - Method in class org.apache.spark.ui.storage.ExecutorStreamSummary
-
- locations() - Method in class org.apache.spark.storage.BlockManagerMessages.BlockLocationsAndStatus
-
- locationUri() - Method in class org.apache.spark.sql.catalog.Database
-
- log() - Method in interface org.apache.spark.internal.Logging
-
- 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.
- Log$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Log$
-
- 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.
- log_() - Method in interface org.apache.spark.internal.Logging
-
- logDebug(Function0<String>) - Method in interface org.apache.spark.internal.Logging
-
- logDebug(Function0<String>, Throwable) - Method in interface org.apache.spark.internal.Logging
-
- logDeprecationWarning(String) - Static method in class org.apache.spark.SparkConf
-
Logs a warning message if the given config key is deprecated.
- logError(Function0<String>) - Method in interface org.apache.spark.internal.Logging
-
- logError(Function0<String>, Throwable) - Method in interface org.apache.spark.internal.Logging
-
- logEvent() - Method in interface org.apache.spark.scheduler.SparkListenerEvent
-
- Logging - Interface in org.apache.spark.internal
-
Utility trait for classes that want to log data.
- logInfo(Function0<String>) - Method in interface org.apache.spark.internal.Logging
-
- logInfo(Function0<String>, Throwable) - Method in interface org.apache.spark.internal.Logging
-
- 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
-
:: Experimental ::
Abstraction for logistic regression results for a given model.
- LogisticRegressionSummaryImpl - Class in org.apache.spark.ml.classification
-
Multiclass logistic regression results for a given model.
- LogisticRegressionSummaryImpl(Dataset<Row>, String, String, String, String) - Constructor for class org.apache.spark.ml.classification.LogisticRegressionSummaryImpl
-
- LogisticRegressionTrainingSummary - Interface in org.apache.spark.ml.classification
-
:: Experimental ::
Abstraction for multiclass logistic regression training results.
- LogisticRegressionTrainingSummaryImpl - Class in org.apache.spark.ml.classification
-
Multiclass logistic regression training results.
- LogisticRegressionTrainingSummaryImpl(Dataset<Row>, String, String, String, String, double[]) - Constructor for class org.apache.spark.ml.classification.LogisticRegressionTrainingSummaryImpl
-
- 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
-
- Logit$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Logit$
-
- logLikelihood(Dataset<?>) - Static method in class org.apache.spark.ml.clustering.DistributedLDAModel
-
- logLikelihood() - Method in class org.apache.spark.ml.clustering.ExpectationAggregator
-
- logLikelihood() - Method in class org.apache.spark.ml.clustering.GaussianMixtureSummary
-
- 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
-
- logName() - Method in interface org.apache.spark.internal.Logging
-
- 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
-
Java-friendly version of RandomRDDs.logNormalRDD
.
- logNormalJavaRDD(JavaSparkContext, double, double, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
RandomRDDs.logNormalJavaRDD
with the default seed.
- logNormalJavaRDD(JavaSparkContext, double, double, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
RandomRDDs.logNormalJavaRDD
with the default number of partitions and the default seed.
- logNormalJavaVectorRDD(JavaSparkContext, double, double, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
Java-friendly version of RandomRDDs.logNormalVectorRDD
.
- logNormalJavaVectorRDD(JavaSparkContext, double, double, long, int, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
RandomRDDs.logNormalJavaVectorRDD
with the default seed.
- logNormalJavaVectorRDD(JavaSparkContext, double, double, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
RandomRDDs.logNormalJavaVectorRDD
with the default number of partitions and
the default seed.
- 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 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 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(SparkListenerLogStart) - Static method in class org.apache.spark.util.JsonProtocol
-
- logTrace(Function0<String>) - Method in interface org.apache.spark.internal.Logging
-
- logTrace(Function0<String>, Throwable) - Method in interface org.apache.spark.internal.Logging
-
- 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
-
- logWarning(Function0<String>) - Method in interface org.apache.spark.internal.Logging
-
- logWarning(Function0<String>, Throwable) - Method in interface org.apache.spark.internal.Logging
-
- 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 average of 64-bit integers.
- LongAccumulator() - Constructor for class org.apache.spark.util.LongAccumulator
-
- LongAccumulatorParam$() - Constructor for class org.apache.spark.AccumulatorParam.LongAccumulatorParam$
-
Deprecated.
- longMetric(String) - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- 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
-
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 interface org.apache.spark.ml.param.shared.HasLoss
-
Param for the loss function to be optimized.
- loss() - Method in class org.apache.spark.ml.regression.AFTAggregator
-
- loss() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
- loss() - Static method in class org.apache.spark.ml.regression.LinearRegressionModel
-
- 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.
- lowerBoundsOnCoefficients() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- lowerBoundsOnCoefficients() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- lowerBoundsOnIntercepts() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- lowerBoundsOnIntercepts() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- LowPrioritySQLImplicits - Interface in org.apache.spark.sql
-
Lower priority implicit methods for converting Scala objects into
Dataset
s.
- lpad(Column, int, String) - Static method in class org.apache.spark.sql.functions
-
Left-pad the string column with pad to a length of len.
- lt(double) - Static method in class org.apache.spark.ml.param.ParamValidators
-
Check if value is less than 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 is less than or equal to upperBound
- ltrim(Column) - Static method in class org.apache.spark.sql.functions
-
Trim the spaces from left end for the specified string value.
- ltrim(Column, String) - Static method in class org.apache.spark.sql.functions
-
Trim the specified character string from left end for the specified string column.
- 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.InsertIntoHiveDirCommand
-
- 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.ScriptTransformationExec
-
- 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.
- makeHref(boolean, String, String) - Static method in class org.apache.spark.ui.UIUtils
-
Return the correct Href after checking if master is running in the
reverse proxy mode or not.
- makeProgressBar(int, int, int, int, Map<String, Object>, 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.InsertIntoHiveDirCommand
-
- 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.ScriptTransformationExec
-
- map(Function1<A, B>, CanBuildFrom<Repr, B, That>) - Static method in class org.apache.spark.sql.types.StructType
-
- map(Function<T, U>) - Static method in class org.apache.spark.streaming.api.java.JavaDStream
-
- map(Function<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.
- map(Function<T, U>) - Static method in class org.apache.spark.streaming.api.java.JavaInputDStream
-
- map(Function<T, U>) - Static method in class org.apache.spark.streaming.api.java.JavaPairDStream
-
- map(Function<T, U>) - Static method in class org.apache.spark.streaming.api.java.JavaPairInputDStream
-
- map(Function<T, U>) - Static method in class org.apache.spark.streaming.api.java.JavaPairReceiverInputDStream
-
- map(Function<T, U>) - 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.
- map_keys(Column) - Static method in class org.apache.spark.sql.functions
-
Returns an unordered array containing the keys of the map.
- map_values(Column) - Static method in class org.apache.spark.sql.functions
-
Returns an unordered array containing the values of the map.
- 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.InsertIntoHiveDirCommand
-
- 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.ScriptTransformationExec
-
- 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
-
- mapExpressions(Function1<Expression, Expression>) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- mapExpressions(Function1<Expression, Expression>) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- mapExpressions(Function1<Expression, Expression>) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- mapExpressions(Function1<Expression, Expression>) - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- 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
-
(Scala-specific)
Applies the given function to each group of data.
- mapGroups(MapGroupsFunction<K, V, U>, Encoder<U>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
-
(Java-specific)
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.
- mapGroupsWithState(Function3<K, Iterator<V>, GroupState<S>, U>, Encoder<S>, Encoder<U>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
-
::Experimental::
(Scala-specific)
Applies the given function to each group of data, while maintaining a user-defined per-group
state.
- mapGroupsWithState(GroupStateTimeout, Function3<K, Iterator<V>, GroupState<S>, U>, Encoder<S>, Encoder<U>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
-
::Experimental::
(Scala-specific)
Applies the given function to each group of data, while maintaining a user-defined per-group
state.
- mapGroupsWithState(MapGroupsWithStateFunction<K, V, S, U>, Encoder<S>, Encoder<U>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
-
::Experimental::
(Java-specific)
Applies the given function to each group of data, while maintaining a user-defined per-group
state.
- mapGroupsWithState(MapGroupsWithStateFunction<K, V, S, U>, Encoder<S>, Encoder<U>, GroupStateTimeout) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
-
::Experimental::
(Java-specific)
Applies the given function to each group of data, while maintaining a user-defined per-group
state.
- MapGroupsWithStateFunction<K,V,S,R> - Interface in org.apache.spark.api.java.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$2() - Static method in class org.apache.spark.rdd.UnionRDD
-
- mapPartitionsWithIndexInternal$default$2() - Static method in class org.apache.spark.api.r.RRDD
-
- mapPartitionsWithIndexInternal$default$2() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- mapPartitionsWithIndexInternal$default$2() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- mapPartitionsWithIndexInternal$default$2() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- mapPartitionsWithIndexInternal$default$2() - Static method in class org.apache.spark.graphx.VertexRDD
-
- mapPartitionsWithIndexInternal$default$2() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- mapPartitionsWithIndexInternal$default$2() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- mapPartitionsWithIndexInternal$default$2() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- mapPartitionsWithIndexInternal$default$2() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- mapPartitionsWithIndexInternal$default$2() - Static method in class org.apache.spark.rdd.UnionRDD
-
- mapPartitionsWithIndexInternal$default$3() - Static method in class org.apache.spark.api.r.RRDD
-
- mapPartitionsWithIndexInternal$default$3() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- mapPartitionsWithIndexInternal$default$3() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- mapPartitionsWithIndexInternal$default$3() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- mapPartitionsWithIndexInternal$default$3() - Static method in class org.apache.spark.graphx.VertexRDD
-
- mapPartitionsWithIndexInternal$default$3() - Static method in class org.apache.spark.rdd.HadoopRDD
-
- mapPartitionsWithIndexInternal$default$3() - Static method in class org.apache.spark.rdd.JdbcRDD
-
- mapPartitionsWithIndexInternal$default$3() - Static method in class org.apache.spark.rdd.NewHadoopRDD
-
- mapPartitionsWithIndexInternal$default$3() - Static method in class org.apache.spark.rdd.PartitionPruningRDD
-
- mapPartitionsWithIndexInternal$default$3() - 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
-
- mapStatuses() - Method in class org.apache.spark.ShuffleStatus
-
MapStatus for each partition.
- 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
-
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(Function1<V, W>, Encoder<W>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
-
- mapValues(MapFunction<V, W>, Encoder<W>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
-
- 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.storage.BufferReleasingInputStream
-
- 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
-
- 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(Column, Column) - Static method in class org.apache.spark.ml.stat.Summarizer
-
- max(Column) - Static method in class org.apache.spark.ml.stat.Summarizer
-
- 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(long) - Method in class org.apache.spark.util.kvstore.KVStoreView
-
Stops iteration after a number of elements has been retrieved.
- max() - Method in class org.apache.spark.util.StatCounter
-
- MAX_FEATURES_FOR_NORMAL_SOLVER() - Static method in class org.apache.spark.ml.regression.LinearRegression
-
When using LinearRegression.solver
== "normal", the solver must limit the number of
features to at most this number.
- 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_RETAINED_DEAD_EXECUTORS() - Static method in class org.apache.spark.status.config
-
- MAX_RETAINED_JOBS() - Static method in class org.apache.spark.status.config
-
- MAX_RETAINED_ROOT_NODES() - Static method in class org.apache.spark.status.config
-
- MAX_RETAINED_STAGES() - Static method in class org.apache.spark.status.config
-
- MAX_RETAINED_TASKS_PER_STAGE() - Static method in class org.apache.spark.status.config
-
- 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
-
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.rdd.DeterministicLevel
-
- 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.LinearSVC
-
- maxIter() - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- 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() - Method in interface org.apache.spark.ml.param.shared.HasMaxIter
-
Param for maximum number of iterations (>= 0).
- 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
-
Deprecated.
Return the max memory can be used by this block manager.
- maxMemory() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
-
- maxMemory() - Method in class org.apache.spark.status.LiveExecutor
-
- maxMemory() - Method in class org.apache.spark.storage.StorageStatus
-
Deprecated.
- 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
-
- 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.
- maxOffHeapMem() - Method in class org.apache.spark.scheduler.SparkListenerBlockManagerAdded
-
- maxOffHeapMem() - Method in class org.apache.spark.storage.StorageStatus
-
Deprecated.
- maxOffHeapMemSize() - Method in class org.apache.spark.storage.BlockManagerMessages.RegisterBlockManager
-
- maxOnHeapMem() - Method in class org.apache.spark.scheduler.SparkListenerBlockManagerAdded
-
- maxOnHeapMem() - Method in class org.apache.spark.storage.StorageStatus
-
Deprecated.
- maxOnHeapMemSize() - Method in class org.apache.spark.storage.BlockManagerMessages.RegisterBlockManager
-
- maxReplicas() - Method in class org.apache.spark.storage.BlockManagerMessages.ReplicateBlock
-
- maxRows() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- maxRows() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- maxRows() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- maxRowsPerPartition() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- maxRowsPerPartition() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- maxRowsPerPartition() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- 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
-
- maxTasks() - Method in class org.apache.spark.status.LiveExecutor
-
- maxVal() - Method in class org.apache.spark.graphx.lib.SVDPlusPlus.Conf
-
- maybeUpdateOutputMetrics(OutputMetrics, Function0<Object>, long) - Static method in class org.apache.spark.internal.io.SparkHadoopWriterUtils
-
- 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(Column, Column) - Static method in class org.apache.spark.ml.stat.Summarizer
-
- mean(Column) - Static method in class org.apache.spark.ml.stat.Summarizer
-
- 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.ml.clustering.ExpectationAggregator
-
- 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".
- MEM_SPILL() - Static method in class org.apache.spark.status.TaskIndexNames
-
- 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
-
- memoryCost(int, int) - Static method in class org.apache.spark.mllib.feature.PCAUtil
-
- MemoryEntry<T> - Interface in org.apache.spark.storage.memory
-
- memoryManager() - Method in class org.apache.spark.SparkEnv
-
- memoryMetrics() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
-
- MemoryMetrics - Class in org.apache.spark.status.api.v1
-
- 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
-
- memoryUsed() - Method in class org.apache.spark.status.LiveExecutor
-
- memoryUsed() - Method in class org.apache.spark.status.LiveRDD
-
- memoryUsed() - Method in class org.apache.spark.status.LiveRDDDistribution
-
- memoryUsed() - Method in class org.apache.spark.status.LiveRDDPartition
-
- memoryUsedBytes() - Method in class org.apache.spark.sql.streaming.StateOperatorProgress
-
- memRemaining() - Method in class org.apache.spark.storage.StorageStatus
-
Deprecated.
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
-
Deprecated.
Return the memory used by this block manager.
- memUsedByRdd(int) - Method in class org.apache.spark.storage.StorageStatus
-
Deprecated.
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(ExpectationAggregator) - Method in class org.apache.spark.ml.clustering.ExpectationAggregator
-
Merge another ExpectationAggregator, update the weights, means and covariances
for each distributions, and update the log likelihood.
- 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(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
-
- mergeOffsets(PartitionOffset[]) - Method in interface org.apache.spark.sql.sources.v2.reader.streaming.ContinuousReader
-
Merge partitioned offsets coming from
ContinuousDataReader
instances for each
partition to a single global offset.
- mergeValue() - Method in class org.apache.spark.Aggregator
-
- message() - Method in class org.apache.spark.FetchFailed
-
- message() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutorFailed
-
- message() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RemoveWorker
-
- 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
-
- message() - Method in class org.apache.spark.sql.streaming.StreamingQueryStatus
-
- 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 - Class in org.apache.spark.sql.types
-
Metadata is a wrapper over Map[String, Any] that limits the value type to simple ones: Boolean,
Long, Double, String, Metadata, Array[Boolean], Array[Long], Array[Double], Array[String], and
Array[Metadata].
- 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
-
- 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(String, Function2<Object, Object, Object>) - Constructor for class org.apache.spark.mllib.stat.test.ChiSqTest.Method
-
- method() - Method in class org.apache.spark.mllib.stat.test.ChiSqTestResult
-
- Method$() - Constructor for class org.apache.spark.mllib.stat.test.ChiSqTest.Method$
-
- 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_FILE_CACHE_HITS() - Static method in class org.apache.spark.metrics.source.HiveCatalogMetrics
-
Tracks the total number of files served from the file status cache instead of discovered.
- METRIC_FILES_DISCOVERED() - Static method in class org.apache.spark.metrics.source.HiveCatalogMetrics
-
Tracks the total number of files discovered off of the filesystem by InMemoryFileIndex.
- 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_HIVE_CLIENT_CALLS() - Static method in class org.apache.spark.metrics.source.HiveCatalogMetrics
-
Tracks the total number of Hive client calls (e.g.
- METRIC_PARALLEL_LISTING_JOB_COUNT() - Static method in class org.apache.spark.metrics.source.HiveCatalogMetrics
-
Tracks the total number of Spark jobs launched for parallel file listing.
- METRIC_PARTITIONS_FETCHED() - Static method in class org.apache.spark.metrics.source.HiveCatalogMetrics
-
Tracks the total number of partition metadata entries fetched via the client api.
- 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.ClusteringEvaluator
-
param for metric name in evaluation
(supports "silhouette"
(default))
- 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
-
- metricRegistry() - Static method in class org.apache.spark.metrics.source.HiveCatalogMetrics
-
- metrics(String...) - Static method in class org.apache.spark.ml.stat.Summarizer
-
Given a list of metrics, provides a builder that it turns computes metrics from a column.
- metrics(Seq<String>) - Static method in class org.apache.spark.ml.stat.Summarizer
-
Given a list of metrics, provides a builder that it turns computes metrics from a column.
- metrics() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- metrics() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- metrics() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- metrics() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- metrics() - Method in class org.apache.spark.status.LiveExecutorStageSummary
-
- metrics() - Method in class org.apache.spark.status.LiveStage
-
- 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
-
- MicroBatchReader - Interface in org.apache.spark.sql.sources.v2.reader.streaming
-
- MicroBatchReadSupport - Interface in org.apache.spark.sql.sources.v2
-
- 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(Column, Column) - Static method in class org.apache.spark.ml.stat.Summarizer
-
- min(Column) - Static method in class org.apache.spark.ml.stat.Summarizer
-
- 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
-
- minConfidence() - Static method in class org.apache.spark.ml.fpm.FPGrowth
-
- minConfidence() - Static method in class org.apache.spark.ml.fpm.FPGrowthModel
-
- 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
-
- MinHashLSH - Class in org.apache.spark.ml.feature
-
:: Experimental ::
- MinHashLSH(String) - Constructor for class org.apache.spark.ml.feature.MinHashLSH
-
- MinHashLSH() - Constructor for class org.apache.spark.ml.feature.MinHashLSH
-
- MinHashLSHModel - Class in org.apache.spark.ml.feature
-
:: Experimental ::
- MINIMUM_ADJUSTED_SCALE() - Static method in class org.apache.spark.sql.types.DecimalType
-
- 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
-
- minSupport() - Static method in class org.apache.spark.ml.fpm.FPGrowth
-
- minSupport() - Static method in class org.apache.spark.ml.fpm.FPGrowthModel
-
- 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, greater than or equal to 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.InsertIntoHiveDirCommand
-
- missingInput() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- missingInput() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- missingValue() - Static method in class org.apache.spark.ml.feature.Imputer
-
- missingValue() - Static method in class org.apache.spark.ml.feature.ImputerModel
-
- 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
-
Trait for objects that provide MLReader
.
- MLReader<T> - Class in org.apache.spark.ml.util
-
Abstract class for utility classes that can load ML instances.
- 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 MLLib.
- 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
-
Trait for classes that provide MLWriter
.
- MLWriter - Class in org.apache.spark.ml.util
-
Abstract class for utility classes that can save ML instances.
- 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.
- mode() - Method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- Model<M extends Model<M>> - Class in org.apache.spark.ml
-
- Model() - Constructor for class org.apache.spark.ml.Model
-
- 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.internal.io.FileCommitProtocol.EmptyTaskCommitMessage$
-
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.evaluation.SquaredEuclideanSilhouette.ClusterStats$
-
Static reference to the singleton instance of this Scala object.
- MODULE$ - Static variable in class org.apache.spark.ml.feature.Word2VecModel.Word2VecModelWriter$
-
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.FamilyAndLink$
-
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.regression.GeneralizedLinearRegression.Tweedie$
-
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.KillExecutorsOnHost$
-
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.RemoveWorker$
-
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.RetrieveSparkAppConfig$
-
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.SparkAppConfig$
-
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.scheduler.cluster.CoarseGrainedClusterMessages.UpdateDelegationTokens$
-
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.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.BlockLocationsAndStatus$
-
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.GetLocationsAndStatus$
-
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.ReplicateBlock$
-
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.ui.JettyUtils.ServletParams$
-
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
-
- 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() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
-
- 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
-
Classification model based on the Multilayer Perceptron.
- MultilayerPerceptronClassifier - Class in org.apache.spark.ml.classification
-
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(BlockMatrix, int) - 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
-
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, greater than or equal to 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$.Data - Class in org.apache.spark.mllib.classification
-
Model data for model import/export
- NaiveBayesModel.SaveLoadV2_0$ - Class in org.apache.spark.mllib.classification
-
- NaiveBayesModel.SaveLoadV2_0$.Data - Class in org.apache.spark.mllib.classification
-
Model data for model import/export
- name() - Method in class org.apache.spark.Accumulable
-
Deprecated.
- name() - Static method in class org.apache.spark.Accumulator
-
Deprecated.
- name() - Static method in class org.apache.spark.api.java.JavaDoubleRDD
-
- name() - Static method in class org.apache.spark.api.java.JavaPairRDD
-
- name() - Static method in class org.apache.spark.api.java.JavaRDD
-
- name() - Method in interface org.apache.spark.api.java.JavaRDDLike
-
- name() - Static method in class org.apache.spark.api.r.RRDD
-
- name() - Static method in class org.apache.spark.graphx.EdgeRDD
-
- name() - Static method in class org.apache.spark.graphx.impl.EdgeRDDImpl
-
- name() - Static method in class org.apache.spark.graphx.impl.VertexRDDImpl
-
- name() - Static method in class org.apache.spark.graphx.VertexRDD
-
- name() - Method in class org.apache.spark.ml.attribute.Attribute
-
Name of the attribute.
- name() - Method in class org.apache.spark.ml.attribute.AttributeGroup
-
- NAME() - Static method in class org.apache.spark.ml.attribute.AttributeKeys
-
- name() - Method in class org.apache.spark.ml.attribute.AttributeType
-
- name() - Method in class org.apache.spark.ml.attribute.BinaryAttribute
-
- name() - Method in class org.apache.spark.ml.attribute.NominalAttribute
-
- name() - Method in class org.apache.spark.ml.attribute.NumericAttribute
-
- name() - Static method in class org.apache.spark.ml.attribute.UnresolvedAttribute
-
- name() - Static method in class org.apache.spark.ml.param.DoubleParam
-
- name() - Static method in class org.apache.spark.ml.param.FloatParam
-
- name() - Method in class org.apache.spark.ml.param.Param
-
- name() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gamma$
-
- name() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gaussian$
-
- name() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Identity$
-
- name() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Inverse$
-
- name() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Log$
-
- name() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Poisson$
-
- name() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Sqrt$
-
- 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.AsyncEventQueue
-
- 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 user-specified name of the query, or null if not specified.
- name() - Method in class org.apache.spark.sql.streaming.StreamingQueryListener.QueryStartedEvent
-
- name() - Method in class org.apache.spark.sql.streaming.StreamingQueryProgress
-
- name(String) - Method in class org.apache.spark.sql.TypedColumn
-
- 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.status.api.v1.streaming.OutputOperationInfo
-
- 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 is greater than 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 is greater than 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
-
- NATURAL_INDEX_NAME - Static variable in annotation type org.apache.spark.util.kvstore.KVIndex
-
- 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 to UTF8String
java.lang.Decimal to Decimal
- needsReconfiguration() - Method in interface org.apache.spark.sql.sources.v2.reader.streaming.ContinuousReader
-
The execution engine will call this method in every epoch to determine if new reader
factories need to be generated, which may be required if for example the underlying
source system has had partitions added or removed.
- negate(Column) - Static method in class org.apache.spark.sql.functions
-
Unary minus, i.e.
- newAccumulatorInfos(Iterable<AccumulableInfo>) - Static method in class org.apache.spark.status.LiveEntityHelpers
-
- 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
-
Smarter version of newApiHadoopFile
that uses class tags to figure out the classes of keys,
values and the org.apache.hadoop.mapreduce.InputFormat
(new MapReduce API) so that user
don't need to pass them directly.
- 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.
- newDateEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- 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.
- NewHadoopMapPartitionsWithSplitRDD$() - Constructor for class org.apache.spark.rdd.NewHadoopRDD.NewHadoopMapPartitionsWithSplitRDD$
-
- 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
-
- 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
-
- newJavaDecimalEncoder() - 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
-
- newMapEncoder(TypeTags.TypeTag<T>) - 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 interface org.apache.spark.sql.LowPrioritySQLImplicits
-
- newProductSeqEncoder(TypeTags.TypeTag<A>) - Method in class org.apache.spark.sql.SQLImplicits
-
- newScalaDecimalEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- newSequenceEncoder(TypeTags.TypeTag<T>) - 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.
- newSetEncoder(TypeTags.TypeTag<T>) - Method in class org.apache.spark.sql.SQLImplicits
-
Notice that we serialize Set
to Catalyst array.
- 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
-
- newTaskTempFile(TaskAttemptContext, Option<String>, String) - Method in class org.apache.spark.internal.io.FileCommitProtocol
-
Notifies the commit protocol to add a new file, and gets back the full path that should be
used.
- newTaskTempFile(TaskAttemptContext, Option<String>, String) - Method in class org.apache.spark.internal.io.HadoopMapReduceCommitProtocol
-
- newTaskTempFileAbsPath(TaskAttemptContext, String, String) - Method in class org.apache.spark.internal.io.FileCommitProtocol
-
Similar to newTaskTempFile(), but allows files to committed to an absolute output location.
- newTaskTempFileAbsPath(TaskAttemptContext, String, String) - Method in class org.apache.spark.internal.io.HadoopMapReduceCommitProtocol
-
- 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.
- newTimeStampEncoder() - Method in class org.apache.spark.sql.SQLImplicits
-
- next() - Method in class org.apache.spark.InterruptibleIterator
-
- next() - Method in interface org.apache.spark.mllib.clustering.LDAOptimizer
-
- next() - Method in interface org.apache.spark.sql.sources.v2.reader.DataReader
-
Proceed to next record, returns false if there is no more records.
- next() - Method in class org.apache.spark.status.LiveRDDPartition
-
- next(int) - Method in interface org.apache.spark.util.kvstore.KVStoreIterator
-
Retrieve multiple elements from the store.
- 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
-
- NioBufferedFileInputStream - Class in org.apache.spark.io
-
InputStream
implementation which uses direct buffer
to read a file to avoid extra copy of data between Java and
native memory which happens when using BufferedInputStream
.
- NioBufferedFileInputStream(File, int) - Constructor for class org.apache.spark.io.NioBufferedFileInputStream
-
- NioBufferedFileInputStream(File) - Constructor for class org.apache.spark.io.NioBufferedFileInputStream
-
- nioByteBuffer() - Method in class org.apache.spark.storage.EncryptedManagedBuffer
-
- 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
-
- 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() - Method in class org.apache.spark.scheduler.BlacklistedExecutor
-
- NODE_LOCAL() - Static method in class org.apache.spark.scheduler.TaskLocality
-
- nodeBlacklist() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RequestExecutors
-
- NodeData(int, double, double, double[], double, int, int, DecisionTreeModelReadWrite.SplitData) - Constructor for class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData
-
- nodeData() - Method in class org.apache.spark.ml.tree.EnsembleModelReadWrite.EnsembleNodeData
-
- 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$.NodeData
-
- NodeData$() - Constructor for class org.apache.spark.ml.tree.DecisionTreeModelReadWrite.NodeData$
-
- 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.InsertIntoHiveDirCommand
-
- nodeName() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- nodeName() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- 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
-
Java-friendly version of RandomRDDs.normalRDD
.
- normalJavaRDD(JavaSparkContext, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
RandomRDDs.normalJavaRDD
with the default seed.
- normalJavaRDD(JavaSparkContext, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
RandomRDDs.normalJavaRDD
with the default number of partitions and the default seed.
- normalJavaVectorRDD(JavaSparkContext, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
Java-friendly version of RandomRDDs.normalVectorRDD
.
- normalJavaVectorRDD(JavaSparkContext, long, int, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
RandomRDDs.normalJavaVectorRDD
with the default seed.
- normalJavaVectorRDD(JavaSparkContext, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
RandomRDDs.normalJavaVectorRDD
with the default number of partitions and the default seed.
- 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(Column, Column) - Static method in class org.apache.spark.ml.stat.Summarizer
-
- normL1(Column) - Static method in class org.apache.spark.ml.stat.Summarizer
-
- 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(Column, Column) - Static method in class org.apache.spark.ml.stat.Summarizer
-
- normL2(Column) - Static method in class org.apache.spark.ml.stat.Summarizer
-
- 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.
- NoTimeout() - Static method in class org.apache.spark.sql.streaming.GroupStateTimeout
-
No timeout.
- 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.expressions.UserDefinedFunction
-
Returns true when the UDF can return a nullable value.
- 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
-
- NullHypothesis$() - Constructor for class org.apache.spark.mllib.stat.test.ChiSqTest.NullHypothesis$
-
- NullHypothesis$() - Constructor for class org.apache.spark.mllib.stat.test.KolmogorovSmirnovTest.NullHypothesis$
-
- NullType - Static variable in class org.apache.spark.sql.types.DataTypes
-
Gets the NullType object.
- NullType - Class in org.apache.spark.sql.types
-
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.
- numActiveBatches() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
-
- numActiveOutputOps() - Method in class org.apache.spark.status.api.v1.streaming.BatchInfo
-
- numActiveReceivers() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
-
- 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
-
- 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
-
- numAttributes() - Method in class org.apache.spark.ml.attribute.AttributeGroup
-
- numAvailableOutputs() - Method in class org.apache.spark.ShuffleStatus
-
Number of partitions that have shuffle outputs.
- numberedTreeString() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- numberedTreeString() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- numberedTreeString() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- numberedTreeString() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- numBins() - Method in class org.apache.spark.mllib.evaluation.BinaryClassificationMetrics
-
- numBlocks() - Method in class org.apache.spark.storage.StorageStatus
-
Deprecated.
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
-
- numBucketsArray() - 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.GBTClassificationModel
-
- numClasses() - Method in class org.apache.spark.ml.classification.LinearSVCModel
-
- numClasses() - Method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- numClasses() - Method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- 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
-
- numCols() - Method in class org.apache.spark.sql.vectorized.ColumnarBatch
-
Returns the number of columns that make up this batch.
- numCompletedIndices() - Method in class org.apache.spark.status.api.v1.JobData
-
- numCompletedIndices() - Method in class org.apache.spark.status.api.v1.StageData
-
- numCompletedOutputOps() - Method in class org.apache.spark.status.api.v1.streaming.BatchInfo
-
- numCompletedStages() - Method in class org.apache.spark.status.api.v1.JobData
-
- 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
-
- numCompleteTasks() - Method in class org.apache.spark.status.api.v1.StageData
-
- numEdges() - Method in class org.apache.spark.graphx.GraphOps
-
The number of edges in the graph.
- numElements() - Method in class org.apache.spark.sql.vectorized.ColumnarArray
-
- numElements() - Method in class org.apache.spark.sql.vectorized.ColumnarMap
-
- 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
-
Numeric data types.
- NumericType() - Constructor for class org.apache.spark.sql.types.NumericType
-
- numFailedOutputOps() - Method in class org.apache.spark.status.api.v1.streaming.BatchInfo
-
- numFailedStages() - Method in class org.apache.spark.status.api.v1.JobData
-
- 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
-
- 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.LinearSVCModel
-
- 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.FeatureHasher
-
Number of features.
- 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() - 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
-
- numFields() - Method in class org.apache.spark.sql.vectorized.ColumnarRow
-
- numFolds() - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- numFolds() - Static method in class org.apache.spark.ml.tuning.CrossValidatorModel
-
- numHashTables() - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
-
- numHashTables() - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- numHashTables() - Static method in class org.apache.spark.ml.feature.MinHashLSH
-
- numHashTables() - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- numInactiveReceivers() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
-
- numInputRows() - Method in class org.apache.spark.sql.streaming.SourceProgress
-
- numInputRows() - Method in class org.apache.spark.sql.streaming.StreamingQueryProgress
-
The aggregate (across all sources) number of records processed in a trigger.
- numInstances() - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionSummary
-
Number of instances in DataFrame predictions.
- 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
-
- numKilledTasks() - Method in class org.apache.spark.status.api.v1.JobData
-
- numKilledTasks() - Method in class org.apache.spark.status.api.v1.StageData
-
- 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(Column, Column) - Static method in class org.apache.spark.ml.stat.Summarizer
-
- numNonZeros(Column) - Static method in class org.apache.spark.ml.stat.Summarizer
-
- 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.
- numNulls() - Method in class org.apache.spark.sql.vectorized.ArrowColumnVector
-
- numNulls() - Method in class org.apache.spark.sql.vectorized.ColumnVector
-
Returns the number of nulls in this column vector.
- numOfPoints() - Method in class org.apache.spark.ml.evaluation.SquaredEuclideanSilhouette.ClusterStats
-
- 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() - Static method in class org.apache.spark.ml.fpm.FPGrowth
-
- numPartitions() - Static method in class org.apache.spark.ml.fpm.FPGrowthModel
-
- 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 interface org.apache.spark.sql.sources.v2.reader.partitioning.Partitioning
-
- 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.
- numProcessedRecords() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
-
- numRddBlocks() - Method in class org.apache.spark.storage.StorageStatus
-
Deprecated.
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
-
Deprecated.
Return the number of blocks that belong to the given RDD in O(1) time.
- numReceivedRecords() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
-
- numReceivers() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
-
- 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
-
- numRetainedCompletedBatches() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
-
- 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
-
- numRows() - Method in interface org.apache.spark.sql.sources.v2.reader.Statistics
-
- numRows() - Method in class org.apache.spark.sql.vectorized.ColumnarBatch
-
Returns the number of rows for read, including filtered rows.
- numRowsTotal() - Method in class org.apache.spark.sql.streaming.StateOperatorProgress
-
- numRowsUpdated() - Method in class org.apache.spark.sql.streaming.StateOperatorProgress
-
- 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
-
- numSkippedTasks() - Method in class org.apache.spark.status.api.v1.JobData
-
- numSpilledStages() - Method in class org.apache.spark.SpillListener
-
- numStreamBlocks() - Method in class org.apache.spark.ui.storage.ExecutorStreamSummary
-
- 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.status.api.v1.StageData
-
- 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
-
- numTotalCompletedBatches() - Method in class org.apache.spark.status.api.v1.streaming.StreamingStatistics
-
- numTotalOutputOps() - Method in class org.apache.spark.status.api.v1.streaming.BatchInfo
-
- numTrees() - Method in class org.apache.spark.ml.classification.GBTClassificationModel
-
Number of trees in ensemble
- numTrees() - Static method in class org.apache.spark.ml.classification.RandomForestClassificationModel
-
- 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() - Static method in class org.apache.spark.ml.regression.RandomForestRegressionModel
-
- 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.
- obj() - Method in class org.apache.spark.internal.io.FileCommitProtocol.TaskCommitMessage
-
- 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.BinaryLogisticRegressionTrainingSummaryImpl
-
- 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.classification.LogisticRegressionTrainingSummaryImpl
-
- objectiveHistory() - Method in class org.apache.spark.ml.regression.LinearRegressionTrainingSummary
-
- ObjectStreamClassMethods(ObjectStreamClass) - Constructor for class org.apache.spark.serializer.SerializationDebugger.ObjectStreamClassMethods
-
- ObjectStreamClassMethods$() - Constructor for class org.apache.spark.serializer.SerializationDebugger.ObjectStreamClassMethods$
-
- ObjectType - Class in org.apache.spark.sql.types
-
- ObjectType(Class<?>) - Constructor for class org.apache.spark.sql.types.ObjectType
-
- ocvTypes() - Static method in class org.apache.spark.ml.image.ImageSchema
-
(Scala-specific) OpenCV type mapping supported
- 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
-
- offHeapCacheSize() - Method in class org.apache.spark.storage.StorageStatus
-
Deprecated.
Return the memory used by off-heap caching RDDs
- offHeapMemoryRemaining() - Method in class org.apache.spark.status.api.v1.RDDDataDistribution
-
- offHeapMemoryUsed() - Method in class org.apache.spark.status.api.v1.RDDDataDistribution
-
- offHeapMemRemaining() - Method in class org.apache.spark.storage.StorageStatus
-
Deprecated.
Return the off-heap memory remaining in this block manager.
- offHeapMemUsed() - Method in class org.apache.spark.storage.StorageStatus
-
Deprecated.
Return the off-heap memory used by this block manager.
- offHeapUsed() - Method in class org.apache.spark.status.LiveRDDDistribution
-
- Offset - Class in org.apache.spark.sql.sources.v2.reader.streaming
-
- Offset() - Constructor for class org.apache.spark.sql.sources.v2.reader.streaming.Offset
-
- offsetBytes(String, long, 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>, Seq<Object>, long, long) - Static method in class org.apache.spark.util.Utils
-
Return a string containing data across a set of files.
- offsetCol() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegression
-
- offsetCol() - Static method in class org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
-
- 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
-
- 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
-
- 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
-
- 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
-
- 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
-
- Once() - Static method in class org.apache.spark.sql.streaming.Trigger
-
A trigger that process only one batch of data in a streaming query then terminates
the query.
- 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
-
- OneHotEncoder(String) - Constructor for class org.apache.spark.ml.feature.OneHotEncoder
-
Deprecated.
- OneHotEncoder() - Constructor for class org.apache.spark.ml.feature.OneHotEncoder
-
Deprecated.
- OneHotEncoderCommon - Class in org.apache.spark.ml.feature
-
Provides some helper methods used by both OneHotEncoder
and OneHotEncoderEstimator
.
- OneHotEncoderCommon() - Constructor for class org.apache.spark.ml.feature.OneHotEncoderCommon
-
- OneHotEncoderEstimator - 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.
- OneHotEncoderEstimator(String) - Constructor for class org.apache.spark.ml.feature.OneHotEncoderEstimator
-
- OneHotEncoderEstimator() - Constructor for class org.apache.spark.ml.feature.OneHotEncoderEstimator
-
- OneHotEncoderModel - Class in org.apache.spark.ml.feature
-
param: categorySizes Original number of categories for each feature being encoded.
- 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
-
- 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
-
- onExecutorBlacklisted(SparkListenerExecutorBlacklisted) - Method in class org.apache.spark.scheduler.SparkListener
-
- onExecutorBlacklisted(SparkListenerExecutorBlacklisted) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- onExecutorBlacklisted(SparkListenerExecutorBlacklisted) - Method in class org.apache.spark.SparkFirehoseListener
-
- 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
-
- 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
-
- onExecutorUnblacklisted(SparkListenerExecutorUnblacklisted) - Method in class org.apache.spark.scheduler.SparkListener
-
- onExecutorUnblacklisted(SparkListenerExecutorUnblacklisted) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- onExecutorUnblacklisted(SparkListenerExecutorUnblacklisted) - Method in class org.apache.spark.SparkFirehoseListener
-
- 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.
- onHeapCacheSize() - Method in class org.apache.spark.storage.StorageStatus
-
Deprecated.
Return the memory used by on-heap caching RDDs
- onHeapMemoryRemaining() - Method in class org.apache.spark.status.api.v1.RDDDataDistribution
-
- onHeapMemoryUsed() - Method in class org.apache.spark.status.api.v1.RDDDataDistribution
-
- onHeapMemRemaining() - Method in class org.apache.spark.storage.StorageStatus
-
Deprecated.
Return the on-heap memory remaining in this block manager.
- onHeapMemUsed() - Method in class org.apache.spark.storage.StorageStatus
-
Deprecated.
Return the on-heap memory used by this block manager.
- onHeapUsed() - Method in class org.apache.spark.status.LiveRDDDistribution
-
- 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
-
- 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
-
- OnlineLDAOptimizer - Class in org.apache.spark.mllib.clustering
-
:: DeveloperApi ::
- OnlineLDAOptimizer() - Constructor for class org.apache.spark.mllib.clustering.OnlineLDAOptimizer
-
- onNodeBlacklisted(SparkListenerNodeBlacklisted) - Method in class org.apache.spark.scheduler.SparkListener
-
- onNodeBlacklisted(SparkListenerNodeBlacklisted) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- onNodeBlacklisted(SparkListenerNodeBlacklisted) - Method in class org.apache.spark.SparkFirehoseListener
-
- onNodeUnblacklisted(SparkListenerNodeUnblacklisted) - Method in class org.apache.spark.scheduler.SparkListener
-
- onNodeUnblacklisted(SparkListenerNodeUnblacklisted) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- onNodeUnblacklisted(SparkListenerNodeUnblacklisted) - Method in class org.apache.spark.SparkFirehoseListener
-
- 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.QueryProgressEvent) - Method in class org.apache.spark.sql.streaming.StreamingQueryListener
-
Called when there is some status update (ingestion rate updated, etc.)
- onQueryStarted(StreamingQueryListener.QueryStartedEvent) - Method in class org.apache.spark.sql.streaming.StreamingQueryListener
-
Called when a query is started.
- onQueryTerminated(StreamingQueryListener.QueryTerminatedEvent) - 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
- onSpeculativeTaskSubmitted(SparkListenerSpeculativeTaskSubmitted) - Method in class org.apache.spark.scheduler.SparkListener
-
- onSpeculativeTaskSubmitted(SparkListenerSpeculativeTaskSubmitted) - Static method in class org.apache.spark.scheduler.StatsReportListener
-
- onSpeculativeTaskSubmitted(SparkListenerSpeculativeTaskSubmitted) - Method in class org.apache.spark.SparkFirehoseListener
-
- 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
-
- 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
-
- 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.
- onStreamingStarted(StreamingListenerStreamingStarted) - Static method in class org.apache.spark.streaming.scheduler.StatsReportListener
-
- onStreamingStarted(StreamingListenerStreamingStarted) - Method in interface org.apache.spark.streaming.scheduler.StreamingListener
-
Called when the streaming has been started
- 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.
- onTaskCommit(FileCommitProtocol.TaskCommitMessage) - Method in class org.apache.spark.internal.io.FileCommitProtocol
-
Called on the driver after a task commits.
- onTaskCommit(FileCommitProtocol.TaskCommitMessage) - Static method in class org.apache.spark.internal.io.HadoopMapReduceCommitProtocol
-
- 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
-
- 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
-
- 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
-
- 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
-
- 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.
- open(File, M, ClassTag<M>) - Static method in class org.apache.spark.status.KVUtils
-
Open or create a LevelDB store.
- 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.ml.util.MLWriter
-
Adds an option to the underlying MLWriter.
- 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
-
Adds an input option for the underlying data source.
- option(String, boolean) - Method in class org.apache.spark.sql.streaming.DataStreamReader
-
Adds an input option for the underlying data source.
- option(String, long) - Method in class org.apache.spark.sql.streaming.DataStreamReader
-
Adds an input option for the underlying data source.
- option(String, double) - Method in class org.apache.spark.sql.streaming.DataStreamReader
-
Adds an input option for the underlying data source.
- option(String, String) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
-
Adds an output option for the underlying data source.
- option(String, boolean) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
-
Adds an output option for the underlying data source.
- option(String, long) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
-
Adds an output option for the underlying data source.
- option(String, double) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
-
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
-
(Scala-specific) Adds input options for the underlying data source.
- options(Map<String, String>) - Method in class org.apache.spark.sql.streaming.DataStreamReader
-
(Java-specific) Adds input options for the underlying data source.
- options(Map<String, String>) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
-
(Scala-specific) Adds output options for the underlying data source.
- options(Map<String, String>) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
-
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 ORC files 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 ORC files 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(String) - Method in class org.apache.spark.sql.streaming.DataStreamReader
-
Loads a ORC file stream, returning the result as a DataFrame
.
- 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 SearchArgument
s, which are used for ORC predicate push-down.
- OrcFilters() - Constructor for class org.apache.spark.sql.hive.orc.OrcFilters
-
- 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 - package org.apache.spark.internal
-
- org.apache.spark.internal.config - package org.apache.spark.internal.config
-
- org.apache.spark.internal.io - package org.apache.spark.internal.io
-
- 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 programmatically.
- org.apache.spark.mapred - package org.apache.spark.mapred
-
- org.apache.spark.metrics.sink - package org.apache.spark.metrics.sink
-
- 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.fpm - package org.apache.spark.ml.fpm
-
- org.apache.spark.ml.image - package org.apache.spark.ml.image
-
- 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 - package org.apache.spark.ml.stat
-
- 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.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.jdbc - package org.apache.spark.sql.jdbc
-
- org.apache.spark.sql.sources - package org.apache.spark.sql.sources
-
- org.apache.spark.sql.sources.v2 - package org.apache.spark.sql.sources.v2
-
- org.apache.spark.sql.sources.v2.reader - package org.apache.spark.sql.sources.v2.reader
-
- org.apache.spark.sql.sources.v2.reader.partitioning - package org.apache.spark.sql.sources.v2.reader.partitioning
-
- org.apache.spark.sql.sources.v2.reader.streaming - package org.apache.spark.sql.sources.v2.reader.streaming
-
- org.apache.spark.sql.sources.v2.writer - package org.apache.spark.sql.sources.v2.writer
-
- org.apache.spark.sql.sources.v2.writer.streaming - package org.apache.spark.sql.sources.v2.writer.streaming
-
- 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.sql.vectorized - package org.apache.spark.sql.vectorized
-
- org.apache.spark.status - package org.apache.spark.status
-
- org.apache.spark.status.api.v1 - package org.apache.spark.status.api.v1
-
- org.apache.spark.status.api.v1.streaming - package org.apache.spark.status.api.v1.streaming
-
- 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.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.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.kvstore - package org.apache.spark.util.kvstore
-
- 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.InsertIntoHiveDirCommand
-
- origin() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- origin() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- 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$5(RDD<Tuple2<Object, U>>, Function3<Object, VD, Option<U>, VD2>) - Static method in class org.apache.spark.graphx.impl.GraphImpl
-
- output() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- output() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- output() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- output() - Method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- OUTPUT() - Static method in class org.apache.spark.ui.ToolTips
-
- output$() - Constructor for class org.apache.spark.InternalAccumulator.output$
-
- OUTPUT_FORMAT() - Static method in class org.apache.spark.sql.hive.execution.HiveOptions
-
- OUTPUT_METRICS_PREFIX() - Static method in class org.apache.spark.InternalAccumulator
-
- OUTPUT_RECORDS() - Static method in class org.apache.spark.status.TaskIndexNames
-
- OUTPUT_SIZE() - Static method in class org.apache.spark.status.TaskIndexNames
-
- outputBytes() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
-
- outputBytes() - Method in class org.apache.spark.status.api.v1.StageData
-
- outputCol() - Static method in class org.apache.spark.ml.feature.Binarizer
-
- outputCol() - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSH
-
- outputCol() - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- 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.FeatureHasher
-
- 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.MinHashLSH
-
- outputCol() - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- 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
-
Deprecated.
- 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
-
- outputCol() - Method in interface org.apache.spark.ml.param.shared.HasOutputCol
-
Param for output column name.
- outputCols() - Static method in class org.apache.spark.ml.feature.Bucketizer
-
- outputCols() - Static method in class org.apache.spark.ml.feature.Imputer
-
- outputCols() - Static method in class org.apache.spark.ml.feature.ImputerModel
-
- outputCols() - Static method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
-
- outputCols() - Static method in class org.apache.spark.ml.feature.OneHotEncoderModel
-
- outputCols() - Static method in class org.apache.spark.ml.feature.QuantileDiscretizer
-
- outputCols() - Method in interface org.apache.spark.ml.param.shared.HasOutputCols
-
Param for output column names.
- outputColumnNames() - Method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- outputColumnNames() - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- outputColumnNames() - Method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- outputColumns() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- outputColumns() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- outputColumns() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- 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 output value type.
- outputFormat() - Method in class org.apache.spark.sql.hive.execution.HiveOptions
-
- 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
-
- outputMode(OutputMode) - Method in class org.apache.spark.sql.streaming.DataStreamWriter
-
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
-
Specifies how data of a streaming DataFrame/Dataset is written to a streaming sink.
- OutputMode - Class in org.apache.spark.sql.streaming
-
OutputMode describes 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.status.api.v1.streaming
-
- 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
-
- outputOpId() - Method in class org.apache.spark.status.api.v1.streaming.OutputOperationInfo
-
- outputOrdering() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- outputPartitioning() - Method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- outputPartitioning() - Method in interface org.apache.spark.sql.sources.v2.reader.SupportsReportPartitioning
-
Returns the output data partitioning that this reader guarantees.
- outputRecords() - Method in class org.apache.spark.status.api.v1.ExecutorStageSummary
-
- outputRecords() - Method in class org.apache.spark.status.api.v1.StageData
-
- 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.InsertIntoHiveDirCommand
-
- outputSet() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- outputSet() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- over(WindowSpec) - Method in class org.apache.spark.sql.Column
-
Defines a windowing column.
- over() - Method in class org.apache.spark.sql.Column
-
Defines an 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.InsertIntoHiveDirCommand
-
- 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.
- p(int) - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- p(int) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- p(int) - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- p(int) - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- 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
-
- parallelism() - Static method in class org.apache.spark.ml.classification.OneVsRest
-
- parallelism() - Static method in class org.apache.spark.ml.tuning.CrossValidator
-
- parallelism() - Static method in class org.apache.spark.ml.tuning.TrainValidationSplit
-
- 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.LinearSVC
-
- params() - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- 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.ClusteringEvaluator
-
- 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.BucketedRandomProjectionLSH
-
- params() - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- 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.FeatureHasher
-
- 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.Imputer
-
- params() - Static method in class org.apache.spark.ml.feature.ImputerModel
-
- 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.MinHashLSH
-
- params() - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- 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
-
Deprecated.
- params() - Static method in class org.apache.spark.ml.feature.OneHotEncoderEstimator
-
- params() - Static method in class org.apache.spark.ml.feature.OneHotEncoderModel
-
- 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.VectorSizeHint
-
- 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() - Static method in class org.apache.spark.ml.fpm.FPGrowth
-
- params() - Static method in class org.apache.spark.ml.fpm.FPGrowthModel
-
- 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.LinearSVCModel
-
- 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.BucketedRandomProjectionLSHModel
-
- 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.ImputerModel
-
- parent() - Static method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- parent() - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- parent() - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- parent() - Static method in class org.apache.spark.ml.feature.OneHotEncoderModel
-
- 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() - Static method in class org.apache.spark.ml.fpm.FPGrowthModel
-
- 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(Object) - Method in class org.apache.spark.util.kvstore.KVStoreView
-
Defines the value of the parent index when iterating over a child index.
- 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_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- parent_$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_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.feature.BucketedRandomProjectionLSHModel
-
- parent_$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.ImputerModel
-
- 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.MinHashLSHModel
-
- 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.OneHotEncoderModel
-
- 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_$eq(Estimator<M>) - Static method in class org.apache.spark.ml.fpm.FPGrowthModel
-
- parent_$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.
- parentState() - Static method in class org.apache.spark.sql.hive.HiveSessionStateBuilder
-
- 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
-
Loads a Parquet file stream, returning the result as a DataFrame
.
- parquetFile(String...) - Method in class org.apache.spark.sql.SQLContext
-
- parquetFile(Seq<String>) - Method in class org.apache.spark.sql.SQLContext
-
- 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
-
- 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.
- 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(String) - Method in class org.apache.spark.status.LiveRDD
-
- 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 Partition
s
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.
- Partitioning - Interface in org.apache.spark.sql.sources.v2.reader.partitioning
-
- PartitionLocations(RDD<?>) - Constructor for class org.apache.spark.rdd.DefaultPartitionCoalescer.PartitionLocations
-
- PartitionOffset - Interface in org.apache.spark.sql.sources.v2.reader.streaming
-
Used for per-partition offsets in continuous processing.
- PartitionPruningRDD<T> - Class in org.apache.spark.rdd
-
:: DeveloperApi ::
An 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.EdgePartition1D$ - Class in org.apache.spark.graphx
-
Assigns edges to partitions using only the source vertex ID, colocating edges with the same
source.
- 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.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.
- 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.
- PCAUtil - Class in org.apache.spark.mllib.feature
-
- PCAUtil() - Constructor for class org.apache.spark.mllib.feature.PCAUtil
-
- 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
-
- PEAK_MEM() - Static method in class org.apache.spark.status.TaskIndexNames
-
- peakExecutionMemory() - Method in class org.apache.spark.status.api.v1.TaskMetricDistributions
-
- peakExecutionMemory() - Method in class org.apache.spark.status.api.v1.TaskMetrics
-
- 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
-
- percent_rank() - Static method in class org.apache.spark.sql.functions
-
Window function: returns the relative rank (i.e.
- percentile() - Static method in class org.apache.spark.ml.feature.ChiSqSelector
-
- percentile() - Static method in class org.apache.spark.ml.feature.ChiSqSelectorModel
-
- percentile() - Method in class org.apache.spark.mllib.feature.ChiSqSelector
-
- 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
-
- 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 performs the specified aggregation.
- pivot(String, Seq<Object>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
-
Pivots a column of the current DataFrame
and performs the specified aggregation.
- pivot(String, List<Object>) - Method in class org.apache.spark.sql.RelationalGroupedDataset
-
(Java-specific) Pivots a column of the current DataFrame
and performs the specified
aggregation.
- PivotType$() - Constructor for class org.apache.spark.sql.RelationalGroupedDataset.PivotType$
-
- 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
-
- POISON_PILL() - Static method in class org.apache.spark.scheduler.AsyncEventQueue
-
- Poisson$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Poisson$
-
- 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
-
Java-friendly version of RandomRDDs.poissonRDD
.
- poissonJavaRDD(JavaSparkContext, double, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
RandomRDDs.poissonJavaRDD
with the default seed.
- poissonJavaRDD(JavaSparkContext, double, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
RandomRDDs.poissonJavaRDD
with the default number of partitions and the default seed.
- poissonJavaVectorRDD(JavaSparkContext, double, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
Java-friendly version of RandomRDDs.poissonVectorRDD
.
- poissonJavaVectorRDD(JavaSparkContext, double, long, int, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
RandomRDDs.poissonJavaVectorRDD
with the default seed.
- poissonJavaVectorRDD(JavaSparkContext, double, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
RandomRDDs.poissonJavaVectorRDD
with the default number of partitions and the default seed.
- 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
-
- popStdev() - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Compute the population standard deviation of this RDD's elements.
- popStdev() - Method in class org.apache.spark.rdd.DoubleRDDFunctions
-
Compute the population standard deviation of this RDD's elements.
- popStdev() - Method in class org.apache.spark.util.StatCounter
-
Return the population standard deviation of the values.
- popVariance() - Method in class org.apache.spark.api.java.JavaDoubleRDD
-
Compute the population variance of this RDD's elements.
- popVariance() - Method in class org.apache.spark.rdd.DoubleRDDFunctions
-
Compute the population variance of this RDD's elements.
- popVariance() - Method in class org.apache.spark.util.StatCounter
-
Return the population variance of the values.
- 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
-
- 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.
- posexplode_outer(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.
- position() - Method in class org.apache.spark.storage.ReadableChannelFileRegion
-
- positioned(Function0<Parsers.Parser<T>>) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- post(SparkListenerEvent) - Method in class org.apache.spark.scheduler.AsyncEventQueue
-
- Postfix$() - Constructor for class org.apache.spark.mllib.fpm.PrefixSpan.Postfix$
-
- PostgresDialect - Class in org.apache.spark.sql.jdbc
-
- PostgresDialect() - Constructor for class org.apache.spark.sql.jdbc.PostgresDialect
-
- postToAll(E) - Static method in class org.apache.spark.scheduler.AsyncEventQueue
-
- 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$ - Class in org.apache.spark.mllib.clustering
-
- 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
-
- pr() - Method in interface 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, p) prepended to it, where p is the precision
associated with the lowest recall on the curve.
- 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
-
- 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.
- precisionByLabel() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
-
Returns precision for each label (category).
- precisionByThreshold() - Method in interface 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
-
- PredictData(double, double) - Constructor for class org.apache.spark.mllib.tree.model.DecisionTreeModel.SaveLoadV1_0$.PredictData
-
- 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.LinearSVC
-
- predictionCol() - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- predictionCol() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- predictionCol() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- predictionCol() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
-
Field in "predictions" which gives the prediction of each class.
- predictionCol() - Method in class org.apache.spark.ml.classification.LogisticRegressionSummaryImpl
-
- 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() - Method in class org.apache.spark.ml.clustering.ClusteringSummary
-
- predictionCol() - Static method in class org.apache.spark.ml.clustering.GaussianMixture
-
- predictionCol() - Static method in class org.apache.spark.ml.clustering.GaussianMixtureModel
-
- predictionCol() - Static method in class org.apache.spark.ml.clustering.KMeans
-
- predictionCol() - Static method in class org.apache.spark.ml.clustering.KMeansModel
-
- predictionCol() - Static method in class org.apache.spark.ml.evaluation.ClusteringEvaluator
-
- 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.fpm.FPGrowth
-
- predictionCol() - Static method in class org.apache.spark.ml.fpm.FPGrowthModel
-
- predictionCol() - Method in interface org.apache.spark.ml.param.shared.HasPredictionCol
-
Param for prediction column name.
- 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 interface org.apache.spark.ml.classification.LogisticRegressionSummary
-
Dataframe output by the model's transform
method.
- predictions() - Method in class org.apache.spark.ml.classification.LogisticRegressionSummaryImpl
-
- predictions() - Method in class org.apache.spark.ml.clustering.ClusteringSummary
-
- 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
-
- preferredLocations() - Method in interface org.apache.spark.sql.sources.v2.reader.DataReaderFactory
-
The preferred locations where the data reader returned by this reader factory can run faster,
but Spark does not guarantee to run the data reader on these locations.
- Prefix$() - Constructor for class org.apache.spark.mllib.fpm.PrefixSpan.Prefix$
-
- 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.Postfix$ - Class in org.apache.spark.mllib.fpm
-
- PrefixSpan.Prefix$ - Class in org.apache.spark.mllib.fpm
-
- 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
-
- 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.ScriptTransformationExec
-
- 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.execution.HiveFileFormat
-
- 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.InsertIntoHiveDirCommand
-
- prettyJson() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- prettyJson() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- prettyJson() - Method in class org.apache.spark.sql.streaming.SinkProgress
-
The pretty (i.e.
- prettyJson() - Method in class org.apache.spark.sql.streaming.SourceProgress
-
The pretty (i.e.
- prettyJson() - Method in class org.apache.spark.sql.streaming.StateOperatorProgress
-
The pretty (i.e.
- prettyJson() - Method in class org.apache.spark.sql.streaming.StreamingQueryProgress
-
The pretty (i.e.
- prettyJson() - Method in class org.apache.spark.sql.streaming.StreamingQueryStatus
-
The pretty (i.e.
- 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() - Static method in class org.apache.spark.sql.types.CharType
-
- 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.HiveStringType
-
- 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.ObjectType
-
- 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
-
- prettyJson() - Static method in class org.apache.spark.sql.types.VarcharType
-
- prettyPrint() - Method in class org.apache.spark.streaming.Duration
-
- prev() - Method in class org.apache.spark.rdd.ShuffledRDD
-
- prev() - Method in class org.apache.spark.status.LiveRDDPartition
-
- 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.InsertIntoHiveDirCommand
-
- printSchema() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- printSchema() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- 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
-
- printStats() - Method in class org.apache.spark.streaming.scheduler.StatsReportListener
-
- printTreeString() - Method in class org.apache.spark.sql.types.StructType
-
- prioritize(BlockManagerId, Seq<BlockManagerId>, HashSet<BlockManagerId>, BlockId, int) - Method in class org.apache.spark.storage.BasicBlockReplicationPolicy
-
Method to prioritize a bunch of candidate peers of a block manager.
- prioritize(BlockManagerId, Seq<BlockManagerId>, HashSet<BlockManagerId>, BlockId, int) - Method in interface org.apache.spark.storage.BlockReplicationPolicy
-
Method to prioritize a bunch of candidate peers of a block
- prioritize(BlockManagerId, Seq<BlockManagerId>, HashSet<BlockManagerId>, BlockId, int) - Method in class org.apache.spark.storage.RandomBlockReplicationPolicy
-
Method to prioritize a bunch of candidate peers of a block.
- 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() - 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.GBTClassificationModel
-
- probabilityCol() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- 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() - Method in class org.apache.spark.ml.classification.LogisticRegressionSummaryImpl
-
- probabilityCol() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassificationModel
-
- probabilityCol() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- 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
-
- probabilityCol() - Method in interface org.apache.spark.ml.param.shared.HasProbabilityCol
-
Param for Column name for predicted class conditional probabilities.
- Probit$() - Constructor for class org.apache.spark.ml.regression.GeneralizedLinearRegression.Probit$
-
- 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.
- processedRowsPerSecond() - Method in class org.apache.spark.sql.streaming.SourceProgress
-
- processedRowsPerSecond() - Method in class org.apache.spark.sql.streaming.StreamingQueryProgress
-
The aggregate (across all sources) rate at which Spark is processing data.
- 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
-
- ProcessingTime(long) - Constructor for class org.apache.spark.sql.streaming.ProcessingTime
-
Deprecated.
- ProcessingTime(long) - Static method in class org.apache.spark.sql.streaming.Trigger
-
A trigger policy that runs a query periodically based on an interval in processing time.
- ProcessingTime(long, TimeUnit) - Static method in class org.apache.spark.sql.streaming.Trigger
-
(Java-friendly)
A trigger policy that runs a query periodically based on an interval in processing time.
- ProcessingTime(Duration) - Static method in class org.apache.spark.sql.streaming.Trigger
-
(Scala-friendly)
A trigger policy that runs a query periodically based on an interval in processing time.
- ProcessingTime(String) - Static method in class org.apache.spark.sql.streaming.Trigger
-
A trigger policy that runs a query periodically based on an interval in processing time.
- processingTime() - Method in class org.apache.spark.status.api.v1.streaming.BatchInfo
-
- ProcessingTimeTimeout() - Static method in class org.apache.spark.sql.streaming.GroupStateTimeout
-
Timeout based on processing time.
- 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.InsertIntoHiveDirCommand
-
- producedAttributes() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- producedAttributes() - Method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- 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.BlacklistedExecutor
-
- 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.SparkListenerExecutorBlacklisted
-
- 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.SparkListenerExecutorUnblacklisted
-
- 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.SparkListenerLogStart
-
- productArity() - Static method in class org.apache.spark.scheduler.SparkListenerNodeBlacklisted
-
- productArity() - Static method in class org.apache.spark.scheduler.SparkListenerNodeUnblacklisted
-
- productArity() - Static method in class org.apache.spark.scheduler.SparkListenerSpeculativeTaskSubmitted
-
- 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.InsertIntoHiveDirCommand
-
- productArity() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- productArity() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- productArity() - Static method in class org.apache.spark.sql.hive.RelationConversions
-
- 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.jdbc.TeradataDialect
-
- 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
-
Deprecated.
- productArity() - Static method in class org.apache.spark.sql.types.ArrayType
-
- productArity() - Static method in class org.apache.spark.sql.types.CharType
-
- 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.ObjectType
-
- 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.sql.types.VarcharType
-
- productArity() - Static method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
-
- productArity() - Static method in class org.apache.spark.status.api.v1.ApplicationInfo
-
- 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.kinesis.DefaultCredentials
-
- 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.StreamingListenerStreamingStarted
-
- 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.BlacklistedExecutor
-
- 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.SparkListenerExecutorBlacklisted
-
- 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.SparkListenerExecutorUnblacklisted
-
- 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.SparkListenerLogStart
-
- productElement(int) - Static method in class org.apache.spark.scheduler.SparkListenerNodeBlacklisted
-
- productElement(int) - Static method in class org.apache.spark.scheduler.SparkListenerNodeUnblacklisted
-
- productElement(int) - Static method in class org.apache.spark.scheduler.SparkListenerSpeculativeTaskSubmitted
-
- 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.InsertIntoHiveDirCommand
-
- 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.ScriptTransformationExec
-
- productElement(int) - Static method in class org.apache.spark.sql.hive.RelationConversions
-
- 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.jdbc.TeradataDialect
-
- 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
-
Deprecated.
- productElement(int) - Static method in class org.apache.spark.sql.types.ArrayType
-
- productElement(int) - Static method in class org.apache.spark.sql.types.CharType
-
- 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.ObjectType
-
- 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.sql.types.VarcharType
-
- productElement(int) - Static method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
-
- productElement(int) - Static method in class org.apache.spark.status.api.v1.ApplicationInfo
-
- 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.kinesis.DefaultCredentials
-
- 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.StreamingListenerStreamingStarted
-
- 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.BlacklistedExecutor
-
- 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.SparkListenerExecutorBlacklisted
-
- 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.SparkListenerExecutorUnblacklisted
-
- 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.SparkListenerLogStart
-
- productIterator() - Static method in class org.apache.spark.scheduler.SparkListenerNodeBlacklisted
-
- productIterator() - Static method in class org.apache.spark.scheduler.SparkListenerNodeUnblacklisted
-
- productIterator() - Static method in class org.apache.spark.scheduler.SparkListenerSpeculativeTaskSubmitted
-
- 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.InsertIntoHiveDirCommand
-
- productIterator() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- productIterator() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- productIterator() - Static method in class org.apache.spark.sql.hive.RelationConversions
-
- 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.jdbc.TeradataDialect
-
- 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
-
Deprecated.
- productIterator() - Static method in class org.apache.spark.sql.types.ArrayType
-
- productIterator() - Static method in class org.apache.spark.sql.types.CharType
-
- 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.ObjectType
-
- 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.sql.types.VarcharType
-
- productIterator() - Static method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
-
- productIterator() - Static method in class org.apache.spark.status.api.v1.ApplicationInfo
-
- 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.kinesis.DefaultCredentials
-
- 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.StreamingListenerStreamingStarted
-
- 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.BlacklistedExecutor
-
- 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.SparkListenerExecutorBlacklisted
-
- 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.SparkListenerExecutorUnblacklisted
-
- 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.SparkListenerLogStart
-
- productPrefix() - Static method in class org.apache.spark.scheduler.SparkListenerNodeBlacklisted
-
- productPrefix() - Static method in class org.apache.spark.scheduler.SparkListenerNodeUnblacklisted
-
- productPrefix() - Static method in class org.apache.spark.scheduler.SparkListenerSpeculativeTaskSubmitted
-
- 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.InsertIntoHiveDirCommand
-
- productPrefix() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- productPrefix() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- productPrefix() - Static method in class org.apache.spark.sql.hive.RelationConversions
-
- 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.jdbc.TeradataDialect
-
- 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
-
Deprecated.
- productPrefix() - Static method in class org.apache.spark.sql.types.ArrayType
-
- productPrefix() - Static method in class org.apache.spark.sql.types.CharType
-
- 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.ObjectType
-
- 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.sql.types.VarcharType
-
- productPrefix() - Static method in class org.apache.spark.status.api.v1.ApplicationAttemptInfo
-
- productPrefix() - Static method in class org.apache.spark.status.api.v1.ApplicationInfo
-
- 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.kinesis.DefaultCredentials
-
- 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.StreamingListenerStreamingStarted
-
- 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
-
- progress() - Method in class org.apache.spark.sql.streaming.StreamingQueryListener.QueryProgressEvent
-
- project(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Binomial$
-
- project(double) - Method in class org.apache.spark.ml.regression.GeneralizedLinearRegression.Gaussian$
-
- 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
-
- provider() - Static method in class org.apache.spark.streaming.kinesis.DefaultCredentials
-
- proxyBase() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.AddWebUIFilter
-
- pruneColumns(StructType) - Method in interface org.apache.spark.sql.sources.v2.reader.SupportsPushDownRequiredColumns
-
Applies column pruning w.r.t.
- PrunedFilteredScan - Interface in org.apache.spark.sql.sources
-
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
-
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.
- pushCatalystFilters(Expression[]) - Method in interface org.apache.spark.sql.sources.v2.reader.SupportsPushDownCatalystFilters
-
Pushes down filters, and returns filters that need to be evaluated after scanning.
- pushedCatalystFilters() - Method in interface org.apache.spark.sql.sources.v2.reader.SupportsPushDownCatalystFilters
-
- pushedFilters() - Method in interface org.apache.spark.sql.sources.v2.reader.SupportsPushDownFilters
-
- pushFilters(Filter[]) - Method in interface org.apache.spark.sql.sources.v2.reader.SupportsPushDownFilters
-
Pushes down filters, and returns filters that need to be evaluated after scanning.
- 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.
- r2adj() - Method in class org.apache.spark.ml.regression.LinearRegressionSummary
-
Returns Adjusted R^2^, the adjusted coefficient of determination.
- RACK_LOCAL() - Static method in class org.apache.spark.scheduler.TaskLocality
-
- radians(Column) - Static method in class org.apache.spark.sql.functions
-
Converts an angle measured in degrees to an approximately equivalent angle measured in radians.
- radians(String) - Static method in class org.apache.spark.sql.functions
-
Converts an angle measured in degrees to an approximately equivalent angle measured in radians.
- 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 independent and identically distributed (i.i.d.) samples
from U[0.0, 1.0].
- rand() - Static method in class org.apache.spark.sql.functions
-
Generate a random column with independent and identically distributed (i.i.d.) samples
from U[0.0, 1.0].
- 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 independent and identically distributed (i.i.d.) samples from
the standard normal distribution.
- randn() - Static method in class org.apache.spark.sql.functions
-
Generate a column with independent and identically distributed (i.i.d.) samples from
the standard normal distribution.
- random() - Method in class org.apache.spark.ml.image.SamplePathFilter
-
- RANDOM() - Static method in class org.apache.spark.mllib.clustering.KMeans
-
- random() - Static method in class org.apache.spark.util.Utils
-
- RandomBlockReplicationPolicy - Class in org.apache.spark.storage
-
- RandomBlockReplicationPolicy() - Constructor for class org.apache.spark.storage.RandomBlockReplicationPolicy
-
- 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
-
- RandomForestClassifier - Class in org.apache.spark.ml.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
-
- RandomForestRegressor - Class in org.apache.spark.ml.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
-
:: DeveloperApi ::
RandomRDDs.randomJavaRDD
with the default seed.
- randomJavaRDD(JavaSparkContext, RandomDataGenerator<T>, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
:: DeveloperApi ::
RandomRDDs.randomJavaRDD
with the default seed & numPartitions
- randomJavaVectorRDD(JavaSparkContext, RandomDataGenerator<Object>, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
:: DeveloperApi ::
Java-friendly version of RandomRDDs.randomVectorRDD
.
- randomJavaVectorRDD(JavaSparkContext, RandomDataGenerator<Object>, long, int, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
:: DeveloperApi ::
RandomRDDs.randomJavaVectorRDD
with the default seed.
- randomJavaVectorRDD(JavaSparkContext, RandomDataGenerator<Object>, long, int) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
:: DeveloperApi ::
RandomRDDs.randomJavaVectorRDD
with the default number of partitions and the default seed.
- 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$2() - Static method in class org.apache.spark.rdd.UnionRDD
-
- randomSplitAsList(double[], long) - Method in class org.apache.spark.sql.Dataset
-
Returns a Java list that contains randomly split Dataset with the provided weights.
- randomVectorRDD(SparkContext, RandomDataGenerator<Object>, long, int, int, long) - Static method in class org.apache.spark.mllib.random.RandomRDDs
-
:: DeveloperApi ::
Generates an RDD[Vector] with vectors containing i.i.d.
samples produced by the
input RandomDataGenerator.
- RandomVertexCut$() - Constructor for class org.apache.spark.graphx.PartitionStrategy.RandomVertexCut$
-
- 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) - Static method in class org.apache.spark.sql.expressions.Window
-
Creates a
WindowSpec
with the frame boundaries defined,
from
start
(inclusive) to
end
(inclusive).
- rangeBetween(Column, Column) - Static method in class org.apache.spark.sql.expressions.Window
-
Creates a
WindowSpec
with the frame boundaries defined,
from
start
(inclusive) to
end
(inclusive).
- rangeBetween(long, long) - Method in class org.apache.spark.sql.expressions.WindowSpec
-
Defines the frame boundaries, from start
(inclusive) to end
(inclusive).
- rangeBetween(Column, Column) - 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, int, Ordering<K>, ClassTag<K>) - Constructor for class org.apache.spark.RangePartitioner
-
- 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(ID, ID, float) - Constructor for class org.apache.spark.ml.recommendation.ALS.Rating
-
- 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
-
- Rating$() - Constructor for class org.apache.spark.ml.recommendation.ALS.Rating$
-
- RatingBlock$() - Constructor for class org.apache.spark.ml.recommendation.ALS.RatingBlock$
-
- ratingCol() - Static method in class org.apache.spark.ml.recommendation.ALS
-
- ratioParam() - Static method in class org.apache.spark.ml.image.SamplePathFilter
-
- 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.GBTClassificationModel
-
- rawPredictionCol() - Static method in class org.apache.spark.ml.classification.GBTClassifier
-
- rawPredictionCol() - Static method in class org.apache.spark.ml.classification.LinearSVC
-
- rawPredictionCol() - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- 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.MultilayerPerceptronClassificationModel
-
- rawPredictionCol() - Static method in class org.apache.spark.ml.classification.MultilayerPerceptronClassifier
-
- 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
-
- rawPredictionCol() - Method in interface org.apache.spark.ml.param.shared.HasRawPredictionCol
-
Param for raw prediction (a.k.a.
- 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
-
- RBackendAuthHandler - Class in org.apache.spark.api.r
-
Authentication handler for connections from the R process.
- RBackendAuthHandler(String) - Constructor for class org.apache.spark.api.r.RBackendAuthHandler
-
- 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.status.LiveExecutor
-
- rddBlocks() - Method in class org.apache.spark.storage.StorageStatus
-
Deprecated.
Return the RDD blocks stored in this block manager.
- rddBlocksById(int) - Method in class org.apache.spark.storage.StorageStatus
-
Deprecated.
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
-
- rddIds() - Method in class org.apache.spark.status.api.v1.StageData
-
- 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
-
- 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
-
- RDDPartitionSeq - Class in org.apache.spark.status
-
A custom sequence of partitions based on a mutable linked list.
- RDDPartitionSeq() - Constructor for class org.apache.spark.status.RDDPartitionSeq
-
- 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
-
Deprecated.
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.NioBufferedFileInputStream
-
- read(byte[], int, int) - Method in class org.apache.spark.io.NioBufferedFileInputStream
-
- read() - Method in class org.apache.spark.io.ReadAheadInputStream
-
- read(byte[], int, int) - Method in class org.apache.spark.io.ReadAheadInputStream
-
- 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.LinearSVCModel
-
- 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.BucketedRandomProjectionLSHModel
-
- 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.ImputerModel
-
- read() - Static method in class org.apache.spark.ml.feature.MaxAbsScalerModel
-
- read() - Static method in class org.apache.spark.ml.feature.MinHashLSHModel
-
- read() - Static method in class org.apache.spark.ml.feature.MinMaxScalerModel
-
- read() - Static method in class org.apache.spark.ml.feature.OneHotEncoderModel
-
- 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.fpm.FPGrowthModel
-
- 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(Class<T>, Object) - Method in class org.apache.spark.util.kvstore.InMemoryStore
-
- read(Class<T>, Object) - Method in interface org.apache.spark.util.kvstore.KVStore
-
Read a specific instance of an object.
- read(Class<T>, Object) - Method in class org.apache.spark.util.kvstore.LevelDB
-
- ReadableChannelFileRegion - Class in org.apache.spark.storage
-
- ReadableChannelFileRegion(ReadableByteChannel, long) - Constructor for class org.apache.spark.storage.ReadableChannelFileRegion
-
- ReadAheadInputStream - Class in org.apache.spark.io
-
InputStream
implementation which asynchronously reads ahead from the underlying input
stream when specified amount of data has been read from the current buffer.
- ReadAheadInputStream(InputStream, int, int) - Constructor for class org.apache.spark.io.ReadAheadInputStream
-
Creates a ReadAheadInputStream
with the specified buffer size and read-ahead
threshold
- 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, JVMObjectTracker) - 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
-
- readFrom(ConfigReader) - Method in class org.apache.spark.internal.config.ConfigEntryWithDefault
-
- readFrom(ConfigReader) - Method in class org.apache.spark.internal.config.ConfigEntryWithDefaultFunction
-
- readFrom(ConfigReader) - Method in class org.apache.spark.internal.config.ConfigEntryWithDefaultString
-
- readFrom(InputStream) - Static method in class org.apache.spark.util.sketch.BloomFilter
-
- readFrom(InputStream) - Static method in class org.apache.spark.util.sketch.CountMinSketch
-
- readFrom(byte[]) - Static method in class org.apache.spark.util.sketch.CountMinSketch
-
- readImages(String) - Static method in class org.apache.spark.ml.image.ImageSchema
-
Read the directory of images from the local or remote source
- readImages(String, SparkSession, boolean, int, boolean, double, long) - Static method in class org.apache.spark.ml.image.ImageSchema
-
Read the directory of images from the local or remote source
- 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, JVMObjectTracker) - Static method in class org.apache.spark.api.r.SerDe
-
- readMap(DataInputStream, JVMObjectTracker) - Static method in class org.apache.spark.api.r.SerDe
-
- readObject(DataInputStream, JVMObjectTracker) - 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>, boolean) - Static method in class org.apache.spark.sql.hive.orc.OrcFileOperator
-
- readSchema() - Method in interface org.apache.spark.sql.sources.v2.reader.DataSourceReader
-
Returns the actual schema of this data source reader, which may be different from the physical
schema of the underlying storage, as column pruning or other optimizations may happen.
- readSqlObject(DataInputStream, char) - Static method in class org.apache.spark.sql.api.r.SQLUtils
-
- readStream() - Method in class org.apache.spark.sql.SparkSession
-
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
-
- ReadSupport - Interface in org.apache.spark.sql.sources.v2
-
- ReadSupportWithSchema - Interface in org.apache.spark.sql.sources.v2
-
- readTime(DataInputStream) - Static method in class org.apache.spark.api.r.SerDe
-
- readTypedObject(DataInputStream, char, JVMObjectTracker) - 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.KillTask
-
- reason() - Method in class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RemoveExecutor
-
- reason() - Method in class org.apache.spark.scheduler.local.KillTask
-
- reason() - Method in class org.apache.spark.scheduler.SparkListenerExecutorRemoved
-
- reason() - Method in class org.apache.spark.scheduler.SparkListenerTaskEnd
-
- reason() - Method in class org.apache.spark.TaskKilled
-
- reason() - Method in exception org.apache.spark.TaskKilledException
-
- 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
-
- 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)
- recallByLabel() - Method in interface org.apache.spark.ml.classification.LogisticRegressionSummary
-
Returns recall for each label (category).
- recallByThreshold() - Method in interface 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.status.api.v1.streaming
-
- 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.
- recentProgress() - Method in interface org.apache.spark.sql.streaming.StreamingQuery
-
- recommendForAllItems(int) - Method in class org.apache.spark.ml.recommendation.ALSModel
-
Returns top numUsers
users recommended for each item, for all items.
- recommendForAllUsers(int) - Method in class org.apache.spark.ml.recommendation.ALSModel
-
Returns top numItems
items recommended for each user, for all users.
- recommendForItemSubset(Dataset<?>, int) - Method in class org.apache.spark.ml.recommendation.ALSModel
-
Returns top numUsers
users recommended for each item id in the input data set.
- recommendForUserSubset(Dataset<?>, int) - Method in class org.apache.spark.ml.recommendation.ALSModel
-
Returns top numItems
items recommended for each user id in the input data set.
- 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_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
-
- 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
-
- recordWriter(OutputStream, Configuration) - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- recordWriterClass() - Method in class org.apache.spark.sql.hive.execution.HiveScriptIOSchema
-
- recoverPartitions(String) - Method in class org.apache.spark.sql.catalog.Catalog
-
Recovers all the partitions in the directory of a table and update the catalog.
- RecursiveFlag - Class in org.apache.spark.ml.image
-
- RecursiveFlag() - Constructor for class org.apache.spark.ml.image.RecursiveFlag
-
- recursiveList(File) - Static method in class org.apache.spark.util.Utils
-
Lists files recursively.
- redact(SparkConf, Seq<Tuple2<String, String>>) - Static method in class org.apache.spark.util.Utils
-
Redact the sensitive values in the given map.
- redact(Option<Regex>, Seq<Tuple2<String, String>>) - Static method in class org.apache.spark.util.Utils
-
Redact the sensitive values in the given map.
- redact(Option<Regex>, String) - Static method in class org.apache.spark.util.Utils
-
Redact the sensitive information in the given string.
- redact(Map<String, String>) - Static method in class org.apache.spark.util.Utils
-
Looks up the redaction regex from within the key value pairs and uses it to redact the rest
of the key value pairs.
- REDIRECT_CONNECTOR_NAME() - Static method in class org.apache.spark.ui.JettyUtils
-
- redirectError() - Method in class org.apache.spark.launcher.SparkLauncher
-
Specifies that stderr in spark-submit should be redirected to stdout.
- redirectError(ProcessBuilder.Redirect) - Method in class org.apache.spark.launcher.SparkLauncher
-
Redirects error output to the specified Redirect.
- redirectError(File) - Method in class org.apache.spark.launcher.SparkLauncher
-
Redirects error output to the specified File.
- redirectOutput(ProcessBuilder.Redirect) - Method in class org.apache.spark.launcher.SparkLauncher
-
Redirects standard output to the specified Redirect.
- redirectOutput(File) - Method in class org.apache.spark.launcher.SparkLauncher
-
Redirects error output to the specified File.
- redirectToLog(String) - Method in class org.apache.spark.launcher.SparkLauncher
-
Sets all output to be logged and redirected to a logger with the specified name.
- 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
-
(Scala-specific)
Reduces the elements of each group of data using the specified binary function.
- reduceGroups(ReduceFunction<V>) - Method in class org.apache.spark.sql.KeyValueGroupedDataset
-
(Java-specific)
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.InsertIntoHiveDirCommand
-
- references() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- references() - Static method in class org.apache.spark.sql.hive.execution.ScriptTransformationExec
-
- references() - Method in class org.apache.spark.sql.sources.And
-
- references() - Method in class org.apache.spark.sql.sources.EqualNullSafe
-
- references() - Method in class org.apache.spark.sql.sources.EqualTo
-
- references() - Method in class org.apache.spark.sql.sources.Filter
-
List of columns that are referenced by this filter.
- references() - Method in class org.apache.spark.sql.sources.GreaterThan
-
- references() - Method in class org.apache.spark.sql.sources.GreaterThanOrEqual
-
- references() - Method in class org.apache.spark.sql.sources.In
-
- references() - Method in class org.apache.spark.sql.sources.IsNotNull
-
- references() - Method in class org.apache.spark.sql.sources.IsNull
-
- references() - Method in class org.apache.spark.sql.sources.LessThan
-
- references() - Method in class org.apache.spark.sql.sources.LessThanOrEqual
-
- references() - Method in class org.apache.spark.sql.sources.Not
-
- references() - Method in class org.apache.spark.sql.sources.Or
-
- references() - Method in class org.apache.spark.sql.sources.StringContains
-
- references() - Method in class org.apache.spark.sql.sources.StringEndsWith
-
- references() - Method in class org.apache.spark.sql.sources.StringStartsWith
-
- refresh() - Static method in class org.apache.spark.sql.hive.execution.CreateHiveTableAsSelectCommand
-
- refresh() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveDirCommand
-
- refresh() - Static method in class org.apache.spark.sql.hive.execution.InsertIntoHiveTable
-
- refreshByPath(String) - Method in class org.apache.spark.sql.catalog.Catalog
-
Invalidates and refreshes all the cached data (and the associated metadata) for any Dataset
that contains the given data source path.
- refreshTable(String) - Method in class org.apache.spark.sql.catalog.Catalog
-
Invalidates and refreshes all the cached data and 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.
- regex(Regex) - Static method in class org.apache.spark.ml.feature.RFormulaParser
-
- regexFromString(String, String) - Static method in class org.apache.spark.internal.config.ConfigHelpers
-
- 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.
- regexp_replace(Column, Column, Column) - 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
-
Registers a user-defined aggregate function (UDAF).
- register(String, UserDefinedFunction) - Method in class org.apache.spark.sql.UDFRegistration
-
Registers a user-defined function (UDF), for a UDF that's already defined using the Dataset
API (i.e.
- register(String, Function0<RT>, TypeTags.TypeTag<RT>) - Method in class org.apache.spark.sql.UDFRegistration
-
Registers a deterministic 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
-
Registers a deterministic 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
-
Registers a deterministic 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
-
Registers a deterministic 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
-
Registers a deterministic 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
-
Registers a deterministic 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
-
Registers a deterministic 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
-
Registers a deterministic 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
-
Registers a deterministic 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
-
Registers a deterministic 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
-
Registers a deterministic 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
-
Registers a deterministic 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
-
Registers a deterministic 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
-
Registers a deterministic 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
-
Registers a deterministic 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
-
Registers a deterministic 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
-
Registers a deterministic 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
-
Registers a deterministic 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
-
Registers a deterministic 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
-
Registers a deterministic 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
-
Registers a deterministic 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
-
Registers a deterministic 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
-
Registers a deterministic Scala closure of 22 arguments as user-defined function (UDF).
- register(String, UDF0<?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a deterministic Java UDF0 instance as user-defined function (UDF).
- register(String, UDF1<?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a deterministic Java UDF1 instance as user-defined function (UDF).
- register(String, UDF2<?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a deterministic Java UDF2 instance as user-defined function (UDF).
- register(String, UDF3<?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a deterministic Java UDF3 instance as user-defined function (UDF).
- register(String, UDF4<?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a deterministic Java UDF4 instance as user-defined function (UDF).
- register(String, UDF5<?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a deterministic Java UDF5 instance as user-defined function (UDF).
- register(String, UDF6<?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a deterministic Java UDF6 instance as user-defined function (UDF).
- register(String, UDF7<?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a deterministic Java UDF7 instance as user-defined function (UDF).
- register(String, UDF8<?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a deterministic Java UDF8 instance as user-defined function (UDF).
- register(String, UDF9<?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a deterministic Java UDF9 instance as user-defined function (UDF).
- register(String, UDF10<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a deterministic Java UDF10 instance as user-defined function (UDF).
- register(String, UDF11<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a deterministic Java UDF11 instance as user-defined function (UDF).
- register(String, UDF12<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a deterministic Java UDF12 instance as user-defined function (UDF).
- register(String, UDF13<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a deterministic Java UDF13 instance as user-defined function (UDF).
- register(String, UDF14<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a deterministic Java UDF14 instance as user-defined function (UDF).
- register(String, UDF15<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a deterministic Java UDF15 instance as user-defined function (UDF).
- register(String, UDF16<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a deterministic Java UDF16 instance as user-defined function (UDF).
- register(String, UDF17<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a deterministic Java UDF17 instance as user-defined function (UDF).
- register(String, UDF18<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a deterministic Java UDF18 instance as user-defined function (UDF).
- register(String, UDF19<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a deterministic Java UDF19 instance as user-defined function (UDF).
- register(String, UDF20<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a deterministic Java UDF20 instance as user-defined function (UDF).
- register(String, UDF21<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a deterministic Java UDF21 instance as user-defined function (UDF).
- register(String, UDF22<?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?>, DataType) - Method in class org.apache.spark.sql.UDFRegistration
-
Register a deterministic Java UDF22 instance as user-defined function (UDF).
- 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
- RegisterBlockManager(BlockManagerId, long, long, org.apache.spark.rpc.RpcEndpointRef) - Constructor for class org.apache.spark.storage.BlockManagerMessages.RegisterBlockManager
-
- RegisterBlockManager$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.RegisterBlockManager$
-
- registerClasses(Kryo) - Method in interface org.apache.spark.serializer.KryoRegistrator
-
- RegisterClusterManager(org.apache.spark.rpc.RpcEndpointRef) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterClusterManager
-
- RegisterClusterManager$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterClusterManager$
-
- 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
.
- RegisteredExecutor$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisteredExecutor$
-
- RegisterExecutor(String, org.apache.spark.rpc.RpcEndpointRef, String, int, Map<String, String>) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutor
-
- RegisterExecutor$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutor$
-
- RegisterExecutorFailed(String) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutorFailed
-
- RegisterExecutorFailed$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RegisterExecutorFailed$
-
- registerKryoClasses(SparkConf) - Static method in class org.apache.spark.graphx.GraphXUtils
-
Registers classes that GraphX uses with Kryo.
- registerKryoClasses(SparkContext) - Static method in class org.apache.spark.ml.evaluation.SquaredEuclideanSilhouette
-
- 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
-
- 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
-
- regParam() - Static method in class org.apache.spark.ml.classification.LinearSVC
-
- regParam() - Static method in class org.apache.spark.ml.classification.LinearSVCModel
-
- regParam() - Static method in class org.apache.spark.ml.classification.LogisticRegression
-
- regParam() - Static method in class org.apache.spark.ml.classification.LogisticRegressionModel
-
- regParam() - Method in interface org.apache.spark.ml.param.shared.HasRegParam
-
Param for regularization parameter (>= 0).
- 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
groupBy
,
cube
or
rollup
(and also
pivot
).
- RelationalGroupedDataset.CubeType$ - Class in org.apache.spark.sql
-
To indicate it's the CUBE
- RelationalGroupedDataset.GroupByType$ - Class in org.apache.spark.sql
-
To indicate it's the GroupBy
- RelationalGroupedDataset.PivotType$ - Class in org.apache.spark.sql
-
- RelationalGroupedDataset.RollupType$ - Class in org.apache.spark.sql
-
To indicate it's the ROLLUP
- RelationConversions - Class in org.apache.spark.sql.hive
-
Relation conversion from metastore relations to data source relations for better performance
- RelationConversions(SQLConf, HiveSessionCatalog) - Constructor for class org.apache.spark.sql.hive.RelationConversions
-
- RelationProvider - Interface in org.apache.spark.sql.sources
-
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
-
- release() - Method in class org.apache.spark.storage.EncryptedManagedBuffer
-
- 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$
-
- REMOTE_BYTES_READ_TO_DISK() - 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
-
- remoteBytesRead() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetricDistributions
-
- remoteBytesRead() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetrics
-
- remoteBytesReadToDisk() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetricDistributions
-
- remoteBytesReadToDisk() - Method in class org.apache.spark.status.api.v1.ShuffleReadMetrics
-
- 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() - Method in interface org.apache.spark.sql.streaming.GroupState
-
Remove this state.
- 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
-
- RemoveBlock(BlockId) - Constructor for class org.apache.spark.storage.BlockManagerMessages.RemoveBlock
-
- RemoveBlock$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.RemoveBlock$
-
- RemoveBroadcast(long, boolean) - Constructor for class org.apache.spark.storage.BlockManagerMessages.RemoveBroadcast
-
- RemoveBroadcast$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.RemoveBroadcast$
-
- removeDistribution(LiveExecutor) - Method in class org.apache.spark.status.LiveRDD
-
- RemoveExecutor(String, org.apache.spark.scheduler.ExecutorLossReason) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RemoveExecutor
-
- RemoveExecutor(String) - Constructor for class org.apache.spark.storage.BlockManagerMessages.RemoveExecutor
-
- RemoveExecutor$() - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RemoveExecutor$
-
- RemoveExecutor$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.RemoveExecutor$
-
- removeFromDriver() - Method in class org.apache.spark.storage.BlockManagerMessages.RemoveBroadcast
-
- removeListener(L) - Static method in class org.apache.spark.scheduler.AsyncEventQueue
-
- removeListener(StreamingQueryListener) - Method in class org.apache.spark.sql.streaming.StreamingQueryManager
-
- removeListenerOnError(SparkListenerInterface) - Method in class org.apache.spark.scheduler.AsyncEventQueue
-
- removeMapOutput(int, BlockManagerId) - Method in class org.apache.spark.ShuffleStatus
-
Remove the map output which was served by the specified block manager.
- removeOutputsByFilter(Function1<BlockManagerId, Object>) - Method in class org.apache.spark.ShuffleStatus
-
Removes all shuffle outputs which satisfies the filter.
- removeOutputsOnExecutor(String) - Method in class org.apache.spark.ShuffleStatus
-
Removes all map outputs associated with the specified executor.
- removeOutputsOnHost(String) - Method in class org.apache.spark.ShuffleStatus
-
Removes all shuffle outputs associated with this host.
- removePartition(String) - Method in class org.apache.spark.status.LiveRDD
-
- removePartition(LiveRDDPartition) - Method in class org.apache.spark.status.RDDPartitionSeq
-
- RemoveRdd(int) - Constructor for class org.apache.spark.storage.BlockManagerMessages.RemoveRdd
-
- RemoveRdd$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.RemoveRdd$
-
- removeReason() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
-
- removeReason() - Method in class org.apache.spark.status.LiveExecutor
-
- removeSelfEdges() - Method in class org.apache.spark.graphx.GraphOps
-
Remove self edges.
- RemoveShuffle(int) - Constructor for class org.apache.spark.storage.BlockManagerMessages.RemoveShuffle
-
- RemoveShuffle$() - Constructor for class org.apache.spark.storage.BlockManagerMessages.RemoveShuffle$
-
- 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.
- removeSparkListener(SparkListenerInterface) - Method in class org.apache.spark.SparkContext
-
:: DeveloperApi ::
Deregister the listener from Spark's listener bus.
- removeTime() - Method in class org.apache.spark.status.api.v1.ExecutorSummary
-
- removeTime() - Method in class org.apache.spark.status.LiveExecutor
-
- RemoveWorker(String, String, String) - Constructor for class org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RemoveWorker
-
- Remo