rbind {SparkR}R Documentation

Union two or more SparkDataFrames


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


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

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



additional SparkDataFrame(s).


currently not used (put here to match the signature of the base implementation).


a SparkDataFrame.


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


A SparkDataFrame containing the result of the union.


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, 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, registerTempTable, rename, repartition, rollup, sample, 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


## Not run: 
##D sparkR.session()
##D unions <- rbind(df, df2, df3, df4)
## End(Not run)

[Package SparkR version 2.3.1 Index]