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https://issues.apache.org/jira/browse/DRILL-4589?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15236181#comment-15236181
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Jinfeng Ni commented on DRILL-4589:
-----------------------------------
Copied comment from pull request.
This patch does not reduce the cost of filter evaluation per row. Rather, it
reduces the number of rows on which the filter evaluation is performed.
> 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
>
> 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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