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From "Hive QA (JIRA)" <>
Subject [jira] [Commented] (HIVE-11525) Bucket pruning
Date Wed, 11 Nov 2015 06:22:11 GMT


Hive QA commented on HIVE-11525:

Here are the results of testing the latest attachment:

{color:green}SUCCESS:{color} +1 due to 1 test(s) being added or modified.

{color:red}ERROR:{color} -1 due to 4 failed/errored test(s), 9780 tests executed
*Failed tests:*

Test results:
Console output:
Test logs:

Executing org.apache.hive.ptest.execution.TestCheckPhase
Executing org.apache.hive.ptest.execution.PrepPhase
Executing org.apache.hive.ptest.execution.ExecutionPhase
Executing org.apache.hive.ptest.execution.ReportingPhase
Tests exited with: TestsFailedException: 4 tests failed

This message is automatically generated.

ATTACHMENT ID: 12770978 - PreCommit-HIVE-TRUNK-Build

> Bucket pruning
> --------------
>                 Key: HIVE-11525
>                 URL:
>             Project: Hive
>          Issue Type: Improvement
>          Components: Logical Optimizer
>    Affects Versions: 0.13.0, 0.14.0, 0.13.1, 1.0.0, 1.2.0, 1.1.0, 1.3.0, 2.0.0
>            Reporter: Maciek Kocon
>            Assignee: Gopal V
>         Attachments: HIVE-11525.1.patch, HIVE-11525.2.patch, HIVE-11525.3.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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