SparkR (version 2.3.0)

sample: Sample

Description

Return a sampled subset of this SparkDataFrame using a random seed. Note: this is not guaranteed to provide exactly the fraction specified of the total count of of the given SparkDataFrame.

Usage

sample(x, withReplacement = FALSE, fraction, seed)
sample_frac(x, withReplacement = FALSE, fraction, seed)
# S4 method for SparkDataFrame
sample(x, withReplacement = FALSE, fraction, seed)
# S4 method for SparkDataFrame
sample_frac(x, withReplacement = FALSE, fraction,
  seed)

Arguments

x

A SparkDataFrame

withReplacement

Sampling with replacement or not

fraction

The (rough) sample target fraction

seed

Randomness seed value. Default is a random seed.

See Also

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, except, explain, filter, first, gapplyCollect, gapply, getNumPartitions, group_by, head, hint, histogram, insertInto, intersect, isLocal, isStreaming, join, limit, localCheckpoint, merge, mutate, ncol, nrow, persist, printSchema, randomSplit, rbind, registerTempTable, rename, repartition, rollup, 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 {
sparkR.session()
path <- "path/to/file.json"
df <- read.json(path)
collect(sample(df, fraction = 0.5))
collect(sample(df, FALSE, 0.5))
collect(sample(df, TRUE, 0.5, seed = 3))
# }