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From "Hyukjin Kwon (Jira)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-19609) Broadcast joins should pushdown join constraints as Filter to the larger relation
Date Tue, 08 Oct 2019 16:10:00 GMT

    [ https://issues.apache.org/jira/browse/SPARK-19609?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16947019#comment-16947019
] 

Hyukjin Kwon commented on SPARK-19609:
--------------------------------------

It was resolved as incomplete as it indicates EOL release and has been inactive more than
a year, as discussed in dev mailing list. Please reopen if you can verify it is still and
issue in Spark 2.4+

> Broadcast joins should pushdown join constraints as Filter to the larger relation
> ---------------------------------------------------------------------------------
>
>                 Key: SPARK-19609
>                 URL: https://issues.apache.org/jira/browse/SPARK-19609
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 2.1.0
>            Reporter: Nick Dimiduk
>            Priority: Major
>              Labels: bulk-closed
>
> For broadcast inner-joins, where the smaller relation is known to be small enough to
materialize on a worker, the set of values for all join columns is known and fits in memory.
Spark should translate these values into a {{Filter}} pushed down to the datasource. The common
join condition of equality, i.e. {{lhs.a == rhs.a}}, can be written as an {{a in ...}} clause.
An example of pushing such filters is already present in the form of {{IsNotNull}} filters
via [~sameerag]'s work on SPARK-12957 subtasks.
> This optimization could even work when the smaller relation does not fit entirely in
memory. This could be done by partitioning the smaller relation into N pieces, applying this
predicate pushdown for each piece, and unioning the results.



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