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Posted to dev@hive.apache.org by "Joydeep Sen Sarma (JIRA)" <ji...@apache.org> on 2009/02/23 21:08:02 UTC

[jira] Assigned: (HIVE-218) predicate on partitioning column is ignored in many places

     [ https://issues.apache.org/jira/browse/HIVE-218?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Joydeep Sen Sarma reassigned HIVE-218:
--------------------------------------

    Assignee: Prasad Chakka

Ashish said this would be resolved by predicate pushdown

> predicate on partitioning column is ignored in many places
> ----------------------------------------------------------
>
>                 Key: HIVE-218
>                 URL: https://issues.apache.org/jira/browse/HIVE-218
>             Project: Hadoop Hive
>          Issue Type: Bug
>          Components: Query Processor
>            Reporter: Joydeep Sen Sarma
>            Assignee: Prasad Chakka
>            Priority: Blocker
>
> We tried two queries yesterday that bought up several problems:
> 1. predicate on partitioning column within a join clause was ignored:
> FROM (FROM xxx a SELECT a.xx, a.yy, a.ds WHERE a.ds=2009-01-05 UNION ALL FROM yyy SELECT b.xx, b.yy, b.ds WHERE b.ds=2009-01-05 UNION ALL FROM zzz c SELECT c.xx, c.yy, c.ds WHERE c.ds=2009-01-05) d JOIN aaa e ON (d.xx=e.xx AND e.ds=2009-01-05) INSERT OVERWRITE TABLE ...
> the plan tried to scan *all* partitions!
> 2. predicate on partitioning clause inside insert clause was ignored (we took the previous query and moved the partition filter to the insert statement)
> FROM (FROM xxx a SELECT a.xx, a.yy, a.ds WHERE a.ds=2009-01-05 UNION ALL FROM yyy SELECT b.xx, b.yy, b.ds WHERE b.ds=2009-01-05 UNION ALL FROM zzz c SELECT c.xx, c.yy, c.ds WHERE c.ds=2009-01-05) d JOIN aaa e ON (d.xx=e.xx ) INSERT OVERWRITE TABLE ... WHERE e.ds=2009-01-05; 
> the plan again tried to scan *all* partitions
> the really bad thing is that we were able to detect this problem only because of metastore inconsistencies - otherwise - we would have merrily scanned all the data. This is really critical to get fixed - because this means that we may actually be scanning tons of unnecessary data in production.

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