join

Joins two DataFrame object by join columns.

join(otherDf, type = JoinType.Inner) [ { joinColumns } ]

joinColumns: JoinDsl.(LeftDataFrame) -> Columns

interface JoinDsl: LeftDataFrame {
    
    val right: RightDataFrame
    
    fun DataColumn.match(rightColumn: DataColumn)
}

joinColumns is a column selector that defines column mapping for join:

df.join(other) { name match right.fullName }

df.join(other) { "name" match "fullName" }

If mapped columns have the same name, just select join columns from the left DataFrame:

df.join(other) { name and city }

df.join(other, "name", "city")

If joinColumns is not specified, columns with the same name from both DataFrame objects will be used as join columns:

df.join(other)

Join types

Supported join types:

Inner (default) — only matched rows from left and right DataFrame objects
Filter — only matched rows from left DataFrame
Left — all rows from left DataFrame, mismatches from right DataFrame filled with null
Right — all rows from right DataFrame, mismatches from left DataFrame filled with null
Full — all rows from left and right DataFrame objects, any mismatches filled with null
Exclude — only mismatched rows from left DataFrame

For every join type there is a shortcut operation:

df.innerJoin(other) { name and city }
df.leftJoin(other) { name and city }
df.rightJoin(other) { name and city }
df.fullJoin(other) { name and city }
df.excludeJoin(other) { name and city }

df.innerJoin(other, "name", "city")
df.leftJoin(other, "name", "city")
df.rightJoin(other, "name", "city")
df.fullJoin(other, "name", "city")
df.excludeJoin(other, "name", "city")

20 May 2025