SparkR (version 2.1.2)

randomSplit: randomSplit

Description

Return a list of randomly split dataframes with the provided weights.

Usage

randomSplit(x, weights, seed)
# S4 method for SparkDataFrame,numeric
randomSplit(x, weights, seed)

Arguments

x

A SparkDataFrame

weights

A vector of weights for splits, will be normalized if they don't sum to 1

seed

A seed to use for random split

See Also

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

Examples

# NOT RUN {
sparkR.session()
df <- createDataFrame(data.frame(id = 1:1000))
df_list <- randomSplit(df, c(2, 3, 5), 0)
# df_list contains 3 SparkDataFrames with each having about 200, 300 and 500 rows respectively
sapply(df_list, count)
# }