SparkR (version 2.4.6)

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

Description

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.

Usage

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

Arguments

x

A SparkDataFrame

y

A SparkDataFrame

Value

A SparkDataFrame containing the result of the union.

Details

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

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(), 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(), 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()

Examples

# NOT RUN {
sparkR.session()
df1 <- select(createDataFrame(mtcars), "carb", "am", "gear")
df2 <- select(createDataFrame(mtcars), "am", "gear", "carb")
head(unionByName(df1, df2))
# }