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Posted to dev@hive.apache.org by "Tianyuan Fu (JIRA)" <ji...@apache.org> on 2013/10/23 13:47:44 UTC
[jira] [Updated] (HIVE-3952) merge map-job followed by map-reduce
job
[ https://issues.apache.org/jira/browse/HIVE-3952?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Tianyuan Fu updated HIVE-3952:
------------------------------
Description:
Consider the query like:
select count（*）FROM
( select idOne, idTwo, value FROM
bigTable
JOIN
smallTableOne on (bigTable.idOne = smallTableOne.idOne)
) firstjoin
JOIN
smallTableTwo on (firstjoin.idTwo = smallTableTwo.idTwo);
where smallTableOne and smallTableTwo are smaller than hive.auto.convert.join.noconditionaltask.size and
hive.auto.convert.join.noconditionaltask is set to true.
The joins are collapsed into mapjoins, and it leads to a map-only job
(for the map-joins) followed by a map-reduce job (for the group by).
Ideally, the map-only job should be merged with the following map-reduce job.
was:
Consider the query like:
select count(*) FROM
( select idOne, idTwo, value FROM
bigTable
JOIN
smallTableOne on (bigTable.idOne = smallTableOne.idOne)
) firstjoin
JOIN
smallTableTwo on (firstjoin.idTwo = smallTableTwo.idTwo);
where smallTableOne and smallTableTwo are smaller than hive.auto.convert.join.noconditionaltask.size and
hive.auto.convert.join.noconditionaltask is set to true.
The joins are collapsed into mapjoins, and it leads to a map-only job
(for the map-joins) followed by a map-reduce job (for the group by).
Ideally, the map-only job should be merged with the following map-reduce job.
> merge map-job followed by map-reduce job
> ----------------------------------------
>
> Key: HIVE-3952
> URL: https://issues.apache.org/jira/browse/HIVE-3952
> Project: Hive
> Issue Type: Improvement
> Components: Query Processor
> Reporter: Namit Jain
> Assignee: Vinod Kumar Vavilapalli
> Fix For: 0.11.0
>
> Attachments: hive.3952.1.patch, HIVE-3952-20130226.txt, HIVE-3952-20130227.1.txt, HIVE-3952-20130301.txt, HIVE-3952-20130421.txt, HIVE-3952-20130424.txt, HIVE-3952-20130428-branch-0.11-bugfix.txt, HIVE-3952-20130428-branch-0.11.txt, HIVE-3952-20130428-branch-0.11-v2.txt
>
>
> Consider the query like:
> select count（*）FROM
> ( select idOne, idTwo, value FROM
> bigTable
> JOIN
> smallTableOne on (bigTable.idOne = smallTableOne.idOne)
> ) firstjoin
> JOIN
> smallTableTwo on (firstjoin.idTwo = smallTableTwo.idTwo);
> where smallTableOne and smallTableTwo are smaller than hive.auto.convert.join.noconditionaltask.size and
> hive.auto.convert.join.noconditionaltask is set to true.
> The joins are collapsed into mapjoins, and it leads to a map-only job
> (for the map-joins) followed by a map-reduce job (for the group by).
> Ideally, the map-only job should be merged with the following map-reduce job.
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