[jira] [Resolved] (SPARK-12336) Outer join using multiple columns results in wrong nullability

["Davies Liu (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-12336?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Davies Liu resolved SPARK-12336.
--------------------------------
       Resolution: Fixed
    Fix Version/s: 2.0.0

https://github.com/apache/spark/pull/10333

> Outer join using multiple columns results in wrong nullability
> --------------------------------------------------------------
>
>                 Key: SPARK-12336
>                 URL: https://issues.apache.org/jira/browse/SPARK-12336
>             Project: Spark
>          Issue Type: Sub-task
>          Components: SQL
>    Affects Versions: 1.4.1, 1.5.2, 1.6.0, 2.0.0
>            Reporter: Cheng Lian
>            Assignee: Davies Liu
>             Fix For: 2.0.0
>
>
> When joining two DataFrames using multiple columns, a temporary inner join is used to compute join output. Then a real join operator is created and projected. However, the final projection list is based on the inner join rather than real join operator. When the real join operator is an outer join, nullability of the final projection can be wrong, since outer join may alter nullability of its child plan(s).



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