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Showing content from https://spark.apache.org/docs/latest/api/R/reference/union.html below:

Return a new SparkDataFrame containing the union of rows — union • SparkR

Return a new SparkDataFrame containing the union of rows in this SparkDataFrame and another SparkDataFrame. This is equivalent to UNION ALL in SQL. Input SparkDataFrames can have different schemas (names and data types).

union(x, y)

# S4 method for class 'SparkDataFrame,SparkDataFrame'
union(x, y)

x

A SparkDataFrame

y

A SparkDataFrame

A SparkDataFrame containing the result of the union.

Note: This does not remove duplicate rows across the two SparkDataFrames. Also as standard in SQL, this function resolves columns by position (not by name).

rbind 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(), rbind(), rename(), repartitionByRange(), repartition(), rollup(), sample(), saveAsTable(), schema(), selectExpr(), select(), showDF(), show(), storageLevel(), str(), subset(), summary(), take(), toJSON(), unionAll(), unionByName(), unpersist(), unpivot(), withColumn(), withWatermark(), with(), write.df(), write.jdbc(), write.json(), write.orc(), write.parquet(), write.stream(), write.text()

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