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https://issues.apache.org/jira/browse/SPARK-32399?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17214426#comment-17214426
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Ruslan Dautkhanov commented on SPARK-32399:
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[~chengsu] thank you for all the Shuffled Hash Join improvements.
I've tested Full Outer Join case using master and found that both SMJ and SHJ
performed exactly the same - 14 minutes of runtime for both types of joins.
One table being just 300k records and another table 25B records / 2Tb of data.
Ran tests multiple times and it's consistent.
What I don't understand about SHJ is - it still seems does a complete shuffling
of the larger table:
!Screen Shot 2020-10-14 at 12.30.07 PM.png|width=583,height=514!
Is this expected?
To be honest, I have not used SHJ as SMJ was a safer bet before all the new
improvements in Spark 3.1. Let me know what I miss. The join is based on a
composite key, so not sure if it has anything to do with this. Thanks!
> Support full outer join in shuffled hash join
> ---------------------------------------------
>
> Key: SPARK-32399
> URL: https://issues.apache.org/jira/browse/SPARK-32399
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
> Affects Versions: 3.1.0
> Reporter: Cheng Su
> Assignee: Cheng Su
> Priority: Minor
> Fix For: 3.1.0
>
> Attachments: Screen Shot 2020-10-14 at 12.30.07 PM.png
>
>
> Currently for SQL full outer join, spark always does a sort merge join no
> matter of how large the join children size are. Inspired by recent discussion
> in [https://github.com/apache/spark/pull/29130#discussion_r456502678] and
> [https://github.com/apache/spark/pull/29181], I think we can support full
> outer join in shuffled hash join in a way that - when looking up stream side
> keys from build side {{HashedRelation}}. Mark this info inside build side
> {{HashedRelation}}, and after reading all rows from stream side, output all
> non-matching rows from build side based on modified {{HashedRelation}}.
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