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From "Chaitanya Mishra (JIRA)" <j...@apache.org>
Subject [jira] Updated: (HIVE-549) Parallel Execution Mechanism
Date Mon, 30 Nov 2009 21:53:20 GMT

     [ https://issues.apache.org/jira/browse/HIVE-549?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Chaitanya Mishra updated HIVE-549:
----------------------------------

    Affects Version/s: 0.3.0
         Release Note: Adds the feature of launching multiple map-reduce tasks that are not
dependent on each other in parallel. Examples of queries affected would be those including
union-alls, and trees of join operators.
               Status: Patch Available  (was: Open)

> Parallel Execution Mechanism
> ----------------------------
>
>                 Key: HIVE-549
>                 URL: https://issues.apache.org/jira/browse/HIVE-549
>             Project: Hadoop Hive
>          Issue Type: Wish
>          Components: Query Processor
>    Affects Versions: 0.3.0
>            Reporter: Adam Kramer
>            Assignee: Chaitanya Mishra
>         Attachments: HIVE549-v6.patch
>
>
> In a massively parallel database system, it would be awesome to also parallelize some
of the mapreduce phases that our data needs to go through.
> One example that just occurred to me is UNION ALL: when you union two SELECT statements,
effectively you could run those statements in parallel. There's no situation (that I can think
of, but I don't have a formal proof) in which the left statement would rely on the right statement,
or vice versa. So, they could be run at the same time...and perhaps they should be. Or, perhaps
there should be a way to make this happen...PARALLEL UNION ALL? PUNION ALL?

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