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Posted to issues@spark.apache.org by "Dongjoon Hyun (Jira)" <ji...@apache.org> on 2020/03/16 19:07:00 UTC

[jira] [Commented] (SPARK-31164) Inconsistent rdd and output partitioning for bucket table when output doesn't contain all bucket columns

    [ https://issues.apache.org/jira/browse/SPARK-31164?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17060433#comment-17060433 ] 

Dongjoon Hyun commented on SPARK-31164:
---------------------------------------

Hi, [~zhenhuawang]. Could you check the older releases like 2.3.4 or 2.2.x together in `Affected Versions`?

> Inconsistent rdd and output partitioning for bucket table when output doesn't contain all bucket columns
> --------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-31164
>                 URL: https://issues.apache.org/jira/browse/SPARK-31164
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.4.5, 3.0.0
>            Reporter: Zhenhua Wang
>            Priority: Major
>
> For a bucketed table, when deciding output partitioning, if the output doesn't contain all bucket columns, the result is `UnknownPartitioning`. But when generating rdd, current Spark uses `createBucketedReadRDD` because it doesn't check if the output contains all bucket columns. So the rdd and its output partitioning are inconsistent.



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