join {SparkR}R Documentation

Join

Description

Joins two SparkDataFrames based on the given join expression.

Usage

## S4 method for signature 'SparkDataFrame,SparkDataFrame'
join(x, y, joinExpr = NULL, joinType = NULL)

Arguments

x

A SparkDataFrame

y

A SparkDataFrame

joinExpr

(Optional) The expression used to perform the join. joinExpr must be a Column expression. If joinExpr is omitted, the default, inner join is attempted and an error is thrown if it would be a Cartesian Product. For Cartesian join, use crossJoin instead.

joinType

The type of join to perform, default 'inner'. Must be one of: 'inner', 'cross', 'outer', 'full', 'fullouter', 'full_outer', 'left', 'leftouter', 'left_outer', 'right', 'rightouter', 'right_outer', 'semi', 'leftsemi', 'left_semi', 'anti', 'leftanti', 'left_anti'.

Value

A SparkDataFrame containing the result of the join operation.

Note

join since 1.4.0

See Also

merge crossJoin

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(), 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(), union(), unpersist(), withColumn(), withWatermark(), with(), write.df(), write.jdbc(), write.json(), write.orc(), write.parquet(), write.stream(), write.text()

Examples

## Not run: 
##D sparkR.session()
##D df1 <- read.json(path)
##D df2 <- read.json(path2)
##D join(df1, df2, df1$col1 == df2$col2) # Performs an inner join based on expression
##D join(df1, df2, df1$col1 == df2$col2, "right_outer")
##D join(df1, df2) # Attempts an inner join
## End(Not run)

[Package SparkR version 3.2.0 Index]