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https://issues.apache.org/jira/browse/DRILL-4530?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15208363#comment-15208363
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John Omernik commented on DRILL-4530:
-------------------------------------
This is at least partially related to
https://issues.apache.org/jira/browse/DRILL-3759 and
https://issues.apache.org/jira/browse/DRILL-2517(which was added to 1.6). In
that when you have many partitions, it walks the partitions (and likely
metadata cache files when they exist) and even looks at files in the
directories before the pruning with dir0 and dir1 occurs. I think 2517
addressed some of that, I saw my queries on large parquet tables get much
faster, but still not `A/B/C` fast which requires no walking of directories.
> Improve metadata cache performance for queries with single partition
> ---------------------------------------------------------------------
>
> Key: DRILL-4530
> URL: https://issues.apache.org/jira/browse/DRILL-4530
> Project: Apache Drill
> Issue Type: Improvement
> Components: Query Planning & Optimization
> Affects Versions: 1.6.0
> Reporter: Aman Sinha
> Assignee: Aman Sinha
>
> Consider two types of queries which are run with Parquet metadata caching:
> {noformat}
> query 1:
> SELECT col FROM `A/B/C`;
> query 2:
> SELECT col FROM `A` WHERE dir0 = 'B' AND dir1 = 'C';
> {noformat}
> For a certain dataset, the query1 elapsed time is 1 sec whereas query2
> elapsed time is 9 sec even though both are accessing the same amount of data.
> The user expectation is that they should perform roughly the same. The main
> difference comes from reading the bigger metadata cache file at the root
> level 'A' for query2 and then applying the partitioning filter. query1 reads
> a much smaller metadata cache file at the subdirectory level.
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