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From "Sergey Shelukhin (JIRA)" <j...@apache.org>
Subject [jira] [Comment Edited] (HIVE-11525) Bucket pruning
Date Tue, 03 Nov 2015 19:03:28 GMT

    [ https://issues.apache.org/jira/browse/HIVE-11525?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14987871#comment-14987871
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Sergey Shelukhin edited comment on HIVE-11525 at 11/3/15 7:03 PM:
------------------------------------------------------------------

out file is missing according to test results


was (Author: sershe):
out file is missing according to test results

> Bucket pruning
> --------------
>
>                 Key: HIVE-11525
>                 URL: https://issues.apache.org/jira/browse/HIVE-11525
>             Project: Hive
>          Issue Type: Improvement
>          Components: Logical Optimizer
>    Affects Versions: 0.13.0, 0.14.0, 0.13.1, 1.0.0, 1.1.0
>            Reporter: Maciek Kocon
>            Assignee: Gopal V
>              Labels: gsoc2015
>         Attachments: HIVE-11525.1.patch, HIVE-11525.WIP.patch
>
>
> Logically and functionally bucketing and partitioning are quite similar - both provide
mechanism to segregate and separate the table's data based on its content. Thanks to that
significant further optimisations like [partition] PRUNING or [bucket] MAP JOIN are possible.
> The difference seems to be imposed by design where the PARTITIONing is open/explicit
while BUCKETing is discrete/implicit.
> Partitioning seems to be very common if not a standard feature in all current RDBMS while
BUCKETING seems to be HIVE specific only.
> In a way BUCKETING could be also called by "hashing" or simply "IMPLICIT PARTITIONING".
> Regardless of the fact that these two are recognised as two separate features available
in Hive there should be nothing to prevent leveraging same existing query/join optimisations
across the two.
> BUCKET pruning
> Enable partition PRUNING equivalent optimisation for queries on BUCKETED tables
> Simplest example is for queries like:
> "SELECT … FROM x WHERE colA=123123"
> to read only the relevant bucket file rather than all file-buckets that belong to a table.



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