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https://issues.apache.org/jira/browse/DRILL-4743?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Gautam Kumar Parai updated DRILL-4743:
--------------------------------------
Description:
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.
For now, the fix is to provide options for controlling the lower and upper
bounds for filter selectivity. The user can use the options
{code}
planner.filter.min_selectivity_estimate_factor
{code}
was:
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.
> 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
> Fix For: 1.8.0
>
>
> 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.
> For now, the fix is to provide options for controlling the lower and upper
> bounds for filter selectivity. The user can use the options
> {code}
> planner.filter.min_selectivity_estimate_factor
> {code}
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