SparkR (version 3.1.2)

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(), 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(), repartitionByRange(), repartition(), rollup(), saveAsTable(), schema(), selectExpr(), select(), showDF(), show(), storageLevel(), str(), subset(), summary(), take(), toJSON(), unionAll(), 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))
# }