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Posted to dev@hive.apache.org by "Amareshwari Sriramadasu (JIRA)" <ji...@apache.org> on 2013/01/03 06:26:16 UTC

[jira] [Assigned] (HIVE-3652) Join optimization for star schema

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

Amareshwari Sriramadasu reassigned HIVE-3652:
---------------------------------------------

    Assignee:     (was: Amareshwari Sriramadasu)
    
> 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
>
> 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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