Sample

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 class 'SparkDataFrame'
sample(x, withReplacement = FALSE, fraction, seed)

# S4 method for class '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.

Note

sample since 1.4.0

sample_frac since 1.4.0

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(), dapply(), dapplyCollect(), describe(), dim(), distinct(), drop(), dropDuplicates(), dropna(), dtypes(), except(), exceptAll(), explain(), filter(), first(), gapply(), gapplyCollect(), getNumPartitions(), group_by(), head(), hint(), histogram(), insertInto(), intersect(), intersectAll(), isLocal(), isStreaming(), join(), limit(), localCheckpoint(), merge(), mutate(), ncol(), nrow(), persist(), printSchema(), randomSplit(), rbind(), rename(), repartition(), repartitionByRange(), rollup(), saveAsTable(), schema(), select(), selectExpr(), show(), showDF(), storageLevel(), str(), subset(), summary(), take(), toJSON(), union(), unionAll(), unionByName(), unpersist(), unpivot(), with(), withColumn(), withWatermark(), write.df(), write.jdbc(), write.json(), write.orc(), write.parquet(), write.stream(), write.text()

Examples

if (FALSE) { # \dontrun{
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))
} # }