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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 Mon, 18 Jul 2016 19:02:20 GMT

    [ https://issues.apache.org/jira/browse/DRILL-4743?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15382838#comment-15382838

ASF GitHub Bot commented on DRILL-4743:

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

    --- Diff: exec/java-exec/src/main/java/org/apache/drill/exec/planner/physical/PlannerSettings.java
    @@ -212,6 +219,14 @@ public static long getInitialPlanningMemorySize() {
    +  public double getFilterMinSelectivityEstimateFactor() {
    +    return options.getOption(FILTER_MIN_SELECTIVITY_ESTIMATE_FACTOR.getOptionName()).float_val;
    --- End diff --
    Make the option validators above typed:
    `public static final FloatValidator FILTER_MIN_SELECTIVITY_ESTIMATE_FACTOR ...`
    and change this line to:
    `return options.getOption(FILTER_MIN_SELECTIVITY_ESTIMATE_FACTOR);`
    Same for the other option.

> 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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