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Posted to issues@drill.apache.org by "Dechang Gu (JIRA)" <ji...@apache.org> on 2016/05/06 18:20:13 UTC

[jira] [Closed] (DRILL-4589) Reduce planning time for file system partition pruning by reducing filter evaluation overhead

     [ https://issues.apache.org/jira/browse/DRILL-4589?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Dechang Gu closed DRILL-4589.
-----------------------------

Reviewed and verified.  LGTM.

> Reduce planning time for file system partition pruning by reducing filter evaluation overhead
> ---------------------------------------------------------------------------------------------
>
>                 Key: DRILL-4589
>                 URL: https://issues.apache.org/jira/browse/DRILL-4589
>             Project: Apache Drill
>          Issue Type: Bug
>          Components: Query Planning & Optimization
>            Reporter: Jinfeng Ni
>            Assignee: Jinfeng Ni
>             Fix For: 1.7.0
>
>
> When Drill is used to query hundreds of thousands, or even millions of files organized into multi-level directories, user typically will provide a partition filter like  : dir0 = something and dir1 = something2 and .. .  
> For such queries, we saw the query planning time could be unacceptable long, due to three main overheads: 1) to expand and get the list of files, 2) to evaluate the partition filter, 3) to get the metadata, in the case of parquet files for which metadata cache file is not available. 
> DRILL-2517 targets at the 3rd part of overhead. As a follow-up work after DRILL-2517, we plan to reduce the filter evaluation overhead. For now, the partition filter evaluation is applied to file level. In many cases, we saw that the number of leaf subdirectories is significantly lower than that of files. Since all the files under the same leaf subdirecctory share the same directory metadata, we should apply the filter evaluation at the leaf subdirectory. By doing that, we could reduce the cpu overhead to evaluate the filter, and the memory overhead as well.



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