[GitHub] [spark] srowen commented on a change in pull request #33323: [SPARK-35739][SQL] Add Java-compatible Dataset.join overloads

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srowen commented on a change in pull request #33323:
URL: https://github.com/apache/spark/pull/33323#discussion_r688972950



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File path: sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala
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@@ -970,7 +995,59 @@ class Dataset[T] private[sql](
   }
 
   /**
-   * Equi-join with another `DataFrame` using the given columns. A cross join with a predicate
+   * 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 3.3.0
+   */
+  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

Review comment:
       I don't mind this at all but I'm also OK with just saying "see the Scala-specific overload' rather than duplicating docs. But I suppose we do this many places so w/e.




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