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From "Amareshwari Sriramadasu (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HIVE-3652) Join optimization for star schema
Date Wed, 13 Feb 2013 08:22:15 GMT

    [ https://issues.apache.org/jira/browse/HIVE-3652?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13577403#comment-13577403
] 

Amareshwari Sriramadasu commented on HIVE-3652:
-----------------------------------------------

Seems I figured it out. The hive.auto.convert.join.noconditionaltask.size is not the number
of rows. When i changed hive.auto.convert.join.noconditionaltask.size value in the attached
tests, it is launching one MR job. Will upload the patch again to add tests.
                
> Join optimization for star schema
> ---------------------------------
>
>                 Key: HIVE-3652
>                 URL: https://issues.apache.org/jira/browse/HIVE-3652
>             Project: Hive
>          Issue Type: Improvement
>          Components: Query Processor
>            Reporter: Amareshwari Sriramadasu
>            Assignee: Vikram Dixit K
>             Fix For: 0.11.0
>
>         Attachments: HIVE-3652-tests.patch
>
>
> Currently, if we join one fact table with multiple dimension tables, it results in multiple
mapreduce jobs for each join with dimension table, because join would be on different keys
for each dimension. 
> Usually all the dimension tables will be small and can fit into memory and so map-side
join can used to join with fact table.
> In this issue I want to look at optimizing such query to generate single mapreduce job
sothat mapper loads dimension tables into memory and joins with fact table on different keys
as well.

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