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https://issues.apache.org/jira/browse/DRILL-4743?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15373828#comment-15373828
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ASF GitHub Bot commented on DRILL-4743:
---------------------------------------
Github user amansinha100 commented on a diff in the pull request:
https://github.com/apache/drill/pull/534#discussion_r70534443
--- Diff:
exec/java-exec/src/main/java/org/apache/drill/exec/planner/physical/PlannerSettings.java
---
@@ -81,6 +83,11 @@
new RangeLongValidator("planner.identifier_max_length", 128 /* A
minimum length is needed because option names are identifiers themselves */,
Integer.MAX_VALUE,
DEFAULT_IDENTIFIER_MAX_LENGTH);
+ public static final OptionValidator
FILTER_MIN_SELECTIVITY_ESTIMATE_FACTOR = new
MinRangeDoubleValidator("planner.filter.min_selectivity_estimate_factor",
--- End diff --
On second thoughts, I agree with keeping it as it is.
> HashJoin's not fully parallelized in query plan
> -----------------------------------------------
>
> Key: DRILL-4743
> URL: https://issues.apache.org/jira/browse/DRILL-4743
> Project: Apache Drill
> Issue Type: Bug
> Affects Versions: 1.5.0
> Reporter: Gautam Kumar Parai
> Assignee: Gautam Kumar Parai
> Labels: doc-impacting
>
> The underlying problem is filter selectivity under-estimate for a query with
> complicated predicates e.g. deeply nested and/or predicates. This leads to
> under parallelization of the major fragment doing the join.
> To really resolve this problem we need table/column statistics to correctly
> estimate the selectivity. However, in the absence of statistics OR even when
> existing statistics are insufficient to get a correct estimate of selectivity
> this will serve as a workaround.
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