HyukjinKwon commented on a change in pull request #33323:
URL: https://github.com/apache/spark/pull/33323#discussion_r669261877
##########
File path: sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala
##########
@@ -981,6 +1006,58 @@ class Dataset[T] private[sql](
join(right, usingColumns, "inner")
}
+ /**
+ * Equi-join with another `DataFrame` using the given column. A cross join
with a predicate
+ * is specified as an inner join. If you would explicitly like to perform a
cross join use the
+ * `crossJoin` method.
+ *
+ * Different from other join functions, the join column will only appear
once in the output,
+ * i.e. similar to SQL's `JOIN USING` syntax.
+ *
+ * @param right Right side of the join operation.
+ * @param usingColumn Name of the column to join on. This column must exist
on both sides.
+ * @param joinType 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`.
+ *
+ * @note If you perform a self-join using this function without aliasing the
input
+ * `DataFrame`s, you will NOT be able to reference any columns after the
join, since
+ * there is no way to disambiguate which side of the join you would like to
reference.
+ *
+ * @group untypedrel
+ * @since 3.1.3
+ */
+ def join(right: Dataset[_], usingColumn: String, joinType: String):
DataFrame = {
+ join(right, Seq(usingColumn), joinType)
+ }
+
+ /**
+ * (Java-specific) Equi-join with another `DataFrame` using the given
columns. A cross join with
+ * a predicate is specified as an inner join. If you would explicitly like
to perform a cross
+ * join use the `crossJoin` method.
+ *
+ * Different from other join functions, the join columns will only appear
once in the output,
+ * i.e. similar to SQL's `JOIN USING` syntax.
+ *
+ * @param right Right side of the join operation.
+ * @param usingColumns Names of the columns to join on. This columns must
exist on both sides.
+ * @param joinType 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`.
+ *
+ * @note If you perform a self-join using this function without aliasing the
input
+ * `DataFrame`s, you will NOT be able to reference any columns after the
join, since
+ * there is no way to disambiguate which side of the join you would like to
reference.
+ *
+ * @group untypedrel
+ * @since 3.1.3
+ */
+ def join(right: Dataset[_], usingColumns: Array[String], joinType: String):
DataFrame = {
+ join(right, usingColumns.toSeq, joinType)
+ }
+
/**
* Equi-join with another `DataFrame` using the given columns. A cross join
with a predicate
Review comment:
Please add "(Scala-specific)" on other methods
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