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From "Vikram Dixit K (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (HIVE-3652) Join optimization for star schema
Date Fri, 04 Jan 2013 17:24:12 GMT

     [ https://issues.apache.org/jira/browse/HIVE-3652?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Vikram Dixit K reassigned HIVE-3652:
------------------------------------

    Assignee: Vikram Dixit K
    
> 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
>
> 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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