[jira] [Commented] (SPARK-13337) DataFrame join-on-columns function should support null-safe equal

["Zhong Wang (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-13337?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15172881#comment-15172881 ] 

Zhong Wang commented on SPARK-13337:
------------------------------------

It doesn't help in my case, because it doesn't support null-safe joins. It would be great if there is an interface like:

{code}
def join(right: DataFrame, usingColumns: Seq[String], joinType: String, nullSafe:Boolean): DataFrame
{code}

It works great if the joining tables doesn't contain null values: it can eliminate the null columns generated from outer joins automatically. The general joining methods in your example support null-safe joins perfectly, but it cannot automatically eliminate the null columns, which are generated from outer joins.

Sorry that it is a little bit complicated here. Please let me know if you need a concrete example.

> DataFrame join-on-columns function should support null-safe equal
> -----------------------------------------------------------------
>
>                 Key: SPARK-13337
>                 URL: https://issues.apache.org/jira/browse/SPARK-13337
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 1.6.0
>            Reporter: Zhong Wang
>            Priority: Minor
>
> Currently, the join-on-columns function:
> {code}
> def join(right: DataFrame, usingColumns: Seq[String], joinType: String): DataFrame
> {code}
> performs a null-insafe join. It would be great if there is an option for null-safe join.



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