[GitHub] [spark] dilipbiswal commented on a change in pull request #24151: [SPARK-26739][SQL][WIP] Standardized Join Types for DataFrames

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dilipbiswal commented on a change in pull request #24151: [SPARK-26739][SQL][WIP] Standardized Join Types for DataFrames
URL: https://github.com/apache/spark/pull/24151#discussion_r267194219
 
 

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 File path: sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala
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 @@ -927,29 +927,28 @@ class Dataset[T] private[sql](
    *
    * @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`, `full_outer`, `left`, `left_outer`,
-   *                 `right`, `right_outer`, `left_semi`, `left_anti`.
-   *
+   * @param joinType Type of join to perform. Default `Inner`. Must be one of the valid JoinType:
+   *                 `Inner`, `Cross`, `FullOuter`, `LeftOuter`, `RightOuter`,
+   *                 `LeftSemi`, `LeftAnti`.
    * @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 2.0.0
    */
-  def join(right: Dataset[_], usingColumns: Seq[String], joinType: String): DataFrame = {
+  def join(right: Dataset[_], usingColumns: Seq[String], joinType: JoinType): DataFrame = {
 
 Review comment:
   Isn't this a breaking change ? Are we allowed to do that ? cc @HyukjinKwon 

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