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https://issues.apache.org/jira/browse/HIVE-3652?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13490587#comment-13490587
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Amareshwari Sriramadasu commented on HIVE-3652:
-----------------------------------------------

Namit, Are you saying if we enhance MapJoinProcessor to do single map for 
MapJoin followed by MapJoin (as in HIVE-1246)  may not work in auto join 
conversion?

I thought whether it is by providing hint or auto join conversion, it does not 
matter to MapJoinProcessor optimizer. Correct me if I'm wrong. 
                
> 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: 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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