repartition {SparkR}R Documentation

Repartition

Description

The following options for repartition are possible:

Usage

## S4 method for signature 'SparkDataFrame'
repartition(x, numPartitions = NULL, col = NULL,
  ...)

Arguments

x

A SparkDataFrame

numPartitions

The number of partitions to use.

col

The column by which the partitioning will be performed.

See Also

Other SparkDataFrame functions: SparkDataFrame-class, [[, agg, arrange, as.data.frame, attach, cache, collect, colnames, coltypes, columns, count, dapply, describe, dim, distinct, dropDuplicates, dropna, drop, dtypes, except, explain, filter, first, group_by, head, histogram, insertInto, intersect, isLocal, join, limit, merge, mutate, ncol, persist, printSchema, registerTempTable, rename, sample, saveAsTable, selectExpr, select, showDF, show, str, take, unionAll, unpersist, withColumn, write.df, write.jdbc, write.json, write.parquet, write.text

Examples

## Not run: 
##D sc <- sparkR.init()
##D sqlContext <- sparkRSQL.init(sc)
##D path <- "path/to/file.json"
##D df <- read.json(sqlContext, path)
##D newDF <- repartition(df, 2L)
##D newDF <- repartition(df, numPartitions = 2L)
##D newDF <- repartition(df, col = df$"col1", df$"col2")
##D newDF <- repartition(df, 3L, col = df$"col1", df$"col2")
## End(Not run)

[Package SparkR version 2.0.0 Index]