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Date: Tue, 3 Nov 2015 19:03:28 +0000 (UTC)
From: "Sergey Shelukhin (JIRA)" <jira@apache.org>
To: issues@hive.apache.org
Message-ID: <JIRA.12855369.1439330852000.140322.1446577408243@Atlassian.JIRA>
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Subject: [jira] [Comment Edited] (HIVE-11525) Bucket pruning
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    [ https://issues.apache.org/jira/browse/HIVE-11525?page=3Dcom.atlassian=
.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=3D1498=
7871#comment-14987871 ]=20

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 [partit=
ion] PRUNING or [bucket] MAP JOIN are possible.
> The difference seems to be imposed by design where the PARTITIONing is op=
en/explicit while BUCKETing is discrete/implicit.
> Partitioning seems to be very common if not a standard feature in all cur=
rent 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 feat=
ures available in Hive there should be nothing to prevent leveraging same e=
xisting 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 =E2=80=A6 FROM x WHERE colA=3D123123"
> to read only the relevant bucket file rather than all file-buckets that b=
elong to a table.


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