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From "Amareshwari Sriramadasu (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HIVE-3652) Join optimization for star schema
Date Mon, 05 Nov 2012 08:35:12 GMT

    [ https://issues.apache.org/jira/browse/HIVE-3652?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13490506#comment-13490506
] 

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

"If we have series of MapJoinOperators, and the Operator tree has MapJoin followed by MapJoin",
then we can run all the map joins in single query. Some of this already solved by HIVE-1246.
I think we need to do some more changes to accept queries of the following form also :


select /*+ MAPJOIN(b,c) */ from FACT a join DIM1 b on a.k1=b.k1 JOIN DIM2 c on a.k2=c.k2

or 

select /*+ MAPJOIN(b,c) */ from FACT a join DIM1 b on a.k1=b.k1 JOIN DIM2 c on b.k2=c.k2
                
> 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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