unionByName {SparkR}R Documentation

Return a new SparkDataFrame containing the union of rows, matched by column names


Return a new SparkDataFrame containing the union of rows in this SparkDataFrame and another SparkDataFrame. This is different from union function, and both UNION ALL and UNION DISTINCT in SQL as column positions are not taken into account. Input SparkDataFrames can have different data types in the schema.


unionByName(x, y)

## S4 method for signature 'SparkDataFrame,SparkDataFrame'
unionByName(x, y)



A SparkDataFrame


A SparkDataFrame


Note: This does not remove duplicate rows across the two SparkDataFrames. This function resolves columns by name (not by position).


A SparkDataFrame containing the result of the union.


unionByName since 2.3.0

See Also

rbind union

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, rbind, registerTempTable, rename, repartition, rollup, sample, saveAsTable, schema, selectExpr, select, showDF, show, storageLevel, str, subset, summary, take, toJSON, 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 df1 <- select(createDataFrame(mtcars), "carb", "am", "gear")
##D df2 <- select(createDataFrame(mtcars), "am", "gear", "carb")
##D head(unionByName(df1, df2))
## End(Not run)

[Package SparkR version 2.3.1 Index]