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From "Zoltan Haindrich (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HIVE-17626) Query reoptimization using cached runtime statistics
Date Wed, 28 Feb 2018 20:30:00 GMT

    [ https://issues.apache.org/jira/browse/HIVE-17626?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16381002#comment-16381002
] 

Zoltan Haindrich commented on HIVE-17626:
-----------------------------------------

test failures are not related


> Query reoptimization using cached runtime statistics
> ----------------------------------------------------
>
>                 Key: HIVE-17626
>                 URL: https://issues.apache.org/jira/browse/HIVE-17626
>             Project: Hive
>          Issue Type: New Feature
>          Components: Logical Optimizer
>    Affects Versions: 3.0.0
>            Reporter: Prasanth Jayachandran
>            Assignee: Zoltan Haindrich
>            Priority: Major
>         Attachments: HIVE-17626.01.patch, HIVE-17626.01wip01.patch, HIVE-17626.02.patch,
HIVE-17626.03.patch, HIVE-17626.04.patch, HIVE-17626.05.patch, runtimestats.patch
>
>
> Something similar to "EXPLAIN ANALYZE" where we annotate explain plan with actual and
estimated statistics. The runtime stats can be cached at query level and subsequent execution
of the same query can make use of the cached statistics from the previous run for better optimization.

> Some use cases,
> 1) re-planning join query (mapjoin failures can be converted to shuffle joins)
> 2) better statistics for table scan operator if dynamic partition pruning is involved
> 3) Better estimates for bloom filter initialization (setting expected entries during
merge)
> This can extended to support wider queries by caching fragments of operator plans scanning
same table(s) or matching some operator sequences.



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