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https://issues.apache.org/jira/browse/DRILL-4363?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15142269#comment-15142269
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ASF GitHub Bot commented on DRILL-4363:
---------------------------------------
Github user jinfengni commented on a diff in the pull request:
https://github.com/apache/drill/pull/371#discussion_r52565738
--- Diff:
exec/java-exec/src/main/java/org/apache/drill/exec/store/parquet/ParquetGroupScan.java
---
@@ -485,12 +486,14 @@ public void populatePruningVector(ValueVector v, int
index, SchemaPath column, S
private EndpointByteMap byteMap;
private int rowGroupIndex;
private String root;
+ private long rowCount;
@JsonCreator
public RowGroupInfo(@JsonProperty("path") String path,
@JsonProperty("start") long start,
- @JsonProperty("length") long length,
@JsonProperty("rowGroupIndex") int rowGroupIndex) {
+ @JsonProperty("length") long length,
@JsonProperty("rowGroupIndex") int rowGroupIndex, long rowCount) {
--- End diff --
Add the comment.
Pass -1 as rowCount in an unused method
TestAffinityCalculator.buildRowGroups(). That is just to make code compile.
> Apply row count based pruning for parquet table in LIMIT n query
> ----------------------------------------------------------------
>
> Key: DRILL-4363
> URL: https://issues.apache.org/jira/browse/DRILL-4363
> Project: Apache Drill
> Issue Type: Improvement
> Reporter: Jinfeng Ni
> Assignee: Aman Sinha
> Fix For: 1.6.0
>
>
> In interactive data exploration use case, one common and probably first query
> that users would use is " SELECT * from table LIMIT n", where n is a small
> number. Such query will give user idea about the columns in the table.
> Normally, user would expect such query should be completed in very short
> time, since it's just asking for small amount of rows, without any
> sort/aggregation.
> When table is small, there is no big problem for Drill. However, when the
> table is extremely large, Drill's response time is not as fast as what user
> would expect.
> In case of parquet table, it seems that query planner could do a bit better
> job : by applying row count based pruning for such LIMIT n query. The
> pruning is kind of similar to what partition pruning will do, except that it
> uses row count, in stead of partition column values. Since row count is
> available in parquet table, it's possible to do such pruning.
> The benefit of doing such pruning is clear: 1) for small "n", such pruning
> would end up with a few parquet files, in stead of thousands, or millions of
> files to scan. 2) execution probably does not have to put scan into multiple
> minor fragments and start reading the files concurrently, which will cause
> big IO overhead. 3) the physical plan itself is much smaller, since it does
> not include the long list of parquet files, reduce rpc cost of sending the
> fragment plans to multiple drillbits, and the overhead to
> serialize/deserialize the fragment plans.
>
>
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