rbind: Union two or more SparkDataFrames

In SparkR: R Front End for 'Apache Spark'

Description

Union two or more SparkDataFrames by row. As in R's rbind, this method requires that the input SparkDataFrames have the same column names.

Usage

rbind(..., deparse.level = 1)

## S4 method for signature 'SparkDataFrame'
rbind(x, ..., deparse.level = 1)

Arguments

...	additional SparkDataFrame(s).
deparse.level	currently not used (put here to match the signature of the base implementation).
x	a SparkDataFrame.

Details

Note: This does not remove duplicate rows across the two SparkDataFrames.

Value

A SparkDataFrame containing the result of the union.

Note

rbind since 1.5.0

See Also

union unionByName

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(), rename(), repartitionByRange(), repartition(), rollup(), sample(), 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()
unions <- rbind(df, df2, df3, df4)

## End(Not run)

SparkR documentation built on June 3, 2021, 5:05 p.m.