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https://issues.apache.org/jira/browse/HIVE-14257?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15380365#comment-15380365
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Gopal V edited comment on HIVE-14257 at 7/16/16 12:32 AM:
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The {{SyntheticJoinPredicate}} is actually in place to indicate these
relationships. However those are not leveraged for anything other than the DPP
runtime.
RedundantDynamicPruningConditionsRemoval removes them for all non-partitioned
columns.
was (Author: gopalv):
The {{SyntheticJoinPredicate}} is actually in place to indicate these
relationships. However those are not leveraged for anything other than the DPP
runtime.
> CBO: Push Join through Groupby to trigger shuffle reductions
> ------------------------------------------------------------
>
> Key: HIVE-14257
> URL: https://issues.apache.org/jira/browse/HIVE-14257
> Project: Hive
> Issue Type: Improvement
> Components: CBO
> Reporter: Gopal V
>
> Similar to the optimizations in hive, already which push aggregates through a
> join (hive.transpose.aggr.join=true).
> {code}
> select count(v) from (select d_year, count(ss_item_sk) as v from store_sales,
> date_dim where ss_sold_date_sk=d_Date_sk group by d_year) w, date_dim d where
> d.d_year = w.d_year and d_date_sk = 1;
> {code}
> currently produces an entire aggregate of all years before discarding all of
> that (because obviously, there's no data for d_date_sk=1;
> This particular example is a simplified version of TPC-DS Query59's join
> condition, which can have a reduction in scans by applying the d_month_seq
> between 1185 and 1185 + 11 into the wss alias.
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