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https://issues.apache.org/jira/browse/SPARK-17570?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15505234#comment-15505234
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Tejas Patil commented on SPARK-17570:
-------------------------------------

ping !!!

> Avoid Hash and Exchange in Sort Merge join if bucketing factor is multiple 
> for tables
> -------------------------------------------------------------------------------------
>
>                 Key: SPARK-17570
>                 URL: https://issues.apache.org/jira/browse/SPARK-17570
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.0.0
>            Reporter: Tejas Patil
>            Priority: Minor
>
> In case of bucketed tables, Spark will avoid doing `Sort` and `Exchange` if 
> the input tables and output table has same number of buckets. However, 
> unequal bucketing will always lead to `Sort` and `Exchange`. If the number of 
> buckets in the output table is a factor of the buckets in the input table, we 
> should be able to avoid `Sort` and `Exchange` and directly join those.
> eg.
> Assume Input1, Input2 and Output be bucketed + sorted tables over the same 
> columns but with different number of buckets. Input1 has 8 buckets, Input1 
> has 4 buckets and Output has 4 buckets. Since hash-partitioning is done using 
> Modulus, if we JOIN buckets (0, 4) of Input1 and buckets (0, 4, 8) of Input2 
> in the same task, it would give the bucket 0 of output table.
> {noformat}
> Input1   (0, 4)      (1, 3)      (2, 5)       (3, 7)
> Input2   (0, 4, 8)   (1, 3, 9)   (2, 5, 10)   (3, 7, 11)
> Output   (0)         (1)         (2)          (3)
> {noformat}



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