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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (DRILL-4743) HashJoin's not fully parallelized in query plan
Date Tue, 12 Jul 2016 22:30:20 GMT

    [ https://issues.apache.org/jira/browse/DRILL-4743?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15373828#comment-15373828

ASF GitHub Bot commented on DRILL-4743:

Github user amansinha100 commented on a diff in the pull request:

    --- 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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