| saveAsTable {SparkR} | R Documentation |
Save the contents of the DataFrame to a data source as a table
## S4 method for signature 'DataFrame,character,character,character' saveAsTable(df, tableName, source = NULL, mode = "error", ...) saveAsTable(df, tableName, source, mode, ...)
df |
A SparkSQL DataFrame |
tableName |
A name for the table |
source |
A name for external data source |
mode |
One of 'append', 'overwrite', 'error', 'ignore' save mode (it is 'error' by default) |
The data source is specified by the 'source' and a set of options (...). If 'source' is not specified, the default data source configured by spark.sql.sources.default will be used.
Additionally, mode is used to specify the behavior of the save operation when
data already exists in the data source. There are four modes:
append: Contents of this DataFrame are expected to be appended to existing data.
overwrite: Existing data is expected to be overwritten by the contents of this DataFrame.
error: An exception is expected to be thrown.
ignore: The save operation is expected to not save the contents of the DataFrame
and to not change the existing data.
Other DataFrame functions: $,
$<-, select,
select,
select,DataFrame,Column-method,
select,DataFrame,list-method,
selectExpr; DataFrame-class,
dataFrame, groupedData;
[, [, [[,
subset; agg,
agg,
count,GroupedData-method,
summarize, summarize;
arrange, arrange,
arrange, orderBy,
orderBy; as.data.frame,
as.data.frame,DataFrame-method;
attach,
attach,DataFrame-method;
cache; collect;
colnames, colnames,
colnames<-, colnames<-,
columns, names,
names<-; coltypes,
coltypes, coltypes<-,
coltypes<-; columns,
dtypes, printSchema,
schema, schema;
count, nrow;
describe, describe,
describe, summary,
summary,
summary,PipelineModel-method;
dim; distinct,
unique; dropna,
dropna, fillna,
fillna, na.omit,
na.omit; dtypes;
except, except;
explain, explain;
filter, filter,
where, where;
first, first;
groupBy, groupBy,
group_by, group_by;
head; insertInto,
insertInto; intersect,
intersect; isLocal,
isLocal; join;
limit, limit;
merge, merge;
mutate, mutate,
transform; ncol;
persist; printSchema;
rbind, rbind,
unionAll, unionAll;
registerTempTable,
registerTempTable; rename,
rename, withColumnRenamed,
withColumnRenamed;
repartition; sample,
sample, sample_frac,
sample_frac;
saveAsParquetFile,
saveAsParquetFile,
write.parquet, write.parquet;
saveDF, saveDF,
write.df, write.df;
selectExpr; showDF,
showDF; show,
show,
show,GroupedData-method;
take; transform,
withColumn, withColumn;
unpersist; write.json,
write.json
## Not run:
##D sc <- sparkR.init()
##D sqlContext <- sparkRSQL.init(sc)
##D path <- "path/to/file.json"
##D df <- read.json(sqlContext, path)
##D saveAsTable(df, "myfile")
## End(Not run)