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From "Hive QA (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HIVE-6430) MapJoin hash table has large memory overhead
Date Sun, 09 Mar 2014 23:20:42 GMT

    [ https://issues.apache.org/jira/browse/HIVE-6430?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13925357#comment-13925357
] 

Hive QA commented on HIVE-6430:
-------------------------------



{color:red}Overall{color}: -1 at least one tests failed

Here are the results of testing the latest attachment:
https://issues.apache.org/jira/secure/attachment/12633496/HIVE-6430.patch

{color:red}ERROR:{color} -1 due to 2 failed/errored test(s), 5373 tests executed
*Failed tests:*
{noformat}
org.apache.hadoop.hive.cli.TestMinimrCliDriver.testCliDriver_bucket_num_reducers
org.apache.hadoop.hive.cli.TestMinimrCliDriver.testCliDriver_infer_bucket_sort_bucketed_table
{noformat}

Test results: http://bigtop01.cloudera.org:8080/job/PreCommit-HIVE-Build/1682/testReport
Console output: http://bigtop01.cloudera.org:8080/job/PreCommit-HIVE-Build/1682/console

Messages:
{noformat}
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: 2 tests failed
{noformat}

This message is automatically generated.

ATTACHMENT ID: 12633496

> MapJoin hash table has large memory overhead
> --------------------------------------------
>
>                 Key: HIVE-6430
>                 URL: https://issues.apache.org/jira/browse/HIVE-6430
>             Project: Hive
>          Issue Type: Improvement
>            Reporter: Sergey Shelukhin
>            Assignee: Sergey Shelukhin
>         Attachments: HIVE-6430.patch
>
>
> Right now, in some queries, I see that storing e.g. 4 ints (2 for key and 2 for row)
can take several hundred bytes, which is ridiculous. I am reducing the size of MJKey and MJRowContainer
in other jiras, but in general we don't need to have java hash table there.  We can either
use primitive-friendly hashtable like the one from HPPC (Apache-licenced), or some variation,
to map primitive keys to single row storage structure without an object per row (similar to
vectorization).



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