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.
Usagesample(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
A SparkDataFrame
Sampling with replacement or not
The (rough) sample target fraction
Randomness seed value. Default is a random seed.
sample since 1.4.0
sample_frac since 1.4.0
See alsoOther 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()
, unpivot()
, withColumn()
, withWatermark()
, with()
, write.df()
, write.jdbc()
, write.json()
, write.orc()
, write.parquet()
, write.stream()
, write.text()
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