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ASF GitHub Bot commented on DRILL-4589: --------------------------------------- Github user hsuanyi commented on a diff in the pull request: https://github.com/apache/drill/pull/468#discussion_r58824883 --- Diff: exec/java-exec/src/main/java/org/apache/drill/exec/planner/FileSystemPartitionDescriptor.java --- @@ -148,13 +139,41 @@ public String getName(int index) { return partitionLabel + index; } - private String getBaseTableLocation() { + protected String getBaseTableLocation() { --- End diff -- I do not find this method being used outside this class. Is it intentional? > 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. -- This message was sent by Atlassian JIRA (v6.3.4#6332)