repartitionByRange {SparkR}R Documentation

Repartition by range

Description

The following options for repartition by range are possible:

Usage

repartitionByRange(x, ...)

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

Arguments

x

a SparkDataFrame.

...

additional column(s) to be used in the range partitioning.

numPartitions

the number of partitions to use.

col

the column by which the range partitioning will be performed.

Note

repartitionByRange since 2.4.0

See Also

repartition, coalesce

Other SparkDataFrame functions: SparkDataFrame-class, agg, alias, arrange, as.data.frame, attach,SparkDataFrame-method, broadcast, cache, checkpoint, coalesce, collect, colnames, coltypes, createOrReplaceTempView, crossJoin, cube, dapplyCollect, dapply, describe, dim, distinct, dropDuplicates, dropna, drop, dtypes, exceptAll, except, explain, filter, first, gapplyCollect, gapply, getNumPartitions, group_by, head, hint, histogram, insertInto, intersectAll, intersect, isLocal, isStreaming, join, limit, localCheckpoint, merge, mutate, ncol, nrow, persist, printSchema, randomSplit, rbind, rename, repartition, rollup, sample, saveAsTable, schema, selectExpr, select, showDF, show, storageLevel, str, subset, summary, take, toJSON, unionByName, union, unpersist, withColumn, withWatermark, with, write.df, write.jdbc, write.json, write.orc, write.parquet, write.stream, write.text

Examples

## Not run: 
##D sparkR.session()
##D path <- "path/to/file.json"
##D df <- read.json(path)
##D newDF <- repartitionByRange(df, col = df$col1, df$col2)
##D newDF <- repartitionByRange(df, 3L, col = df$col1, df$col2)
## End(Not run)

[Package SparkR version 2.4.3 Index]