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https://issues.apache.org/jira/browse/HIVE-11110?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14735779#comment-14735779
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Laljo John Pullokkaran commented on HIVE-11110:
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When a predicate involves deterministic & non deterministic udfs, the
deterministic pieces needs to be pulled out.
Example: select a.* from srcpart a where rand(1) < 0.1 and a.ds = '2008-04-08'
and not(key > 50 or key < 10) and a.hr like '%2';
This should be rewritten to push a.ds = '2008-04-08' and not(key > 50 or key <
10) and a.hr like '%2';
> Reorder applyPreJoinOrderingTransforms, add NotNULL/FilterMerge rules,
> improve Filter selectivity estimation
> ------------------------------------------------------------------------------------------------------------
>
> Key: HIVE-11110
> URL: https://issues.apache.org/jira/browse/HIVE-11110
> Project: Hive
> Issue Type: Bug
> Components: CBO
> Reporter: Jesus Camacho Rodriguez
> Assignee: Laljo John Pullokkaran
> Attachments: HIVE-11110-branch-1.2.patch, HIVE-11110.1.patch,
> HIVE-11110.2.patch, HIVE-11110.4.patch, HIVE-11110.5.patch,
> HIVE-11110.6.patch, HIVE-11110.7.patch, HIVE-11110.8.patch,
> HIVE-11110.9.patch, HIVE-11110.91.patch, HIVE-11110.patch
>
>
> Query
> {code}
> select count(*)
> from store_sales
> ,store_returns
> ,date_dim d1
> ,date_dim d2
> where d1.d_quarter_name = '2000Q1'
> and d1.d_date_sk = ss_sold_date_sk
> and ss_customer_sk = sr_customer_sk
> and ss_item_sk = sr_item_sk
> and ss_ticket_number = sr_ticket_number
> and sr_returned_date_sk = d2.d_date_sk
> and d2.d_quarter_name in ('2000Q1','2000Q2','2000Q3’);
> {code}
> The store_sales table is partitioned on ss_sold_date_sk, which is also used
> in a join clause. The join clause should add a filter “filterExpr:
> ss_sold_date_sk is not null”, which should get pushed the MetaStore when
> fetching the stats. Currently this is not done in CBO planning, which results
> in the stats from __HIVE_DEFAULT_PARTITION__ to be fetched and considered in
> the optimization phase. In particular, this increases the NDV for the join
> columns and may result in wrong planning.
> Including HiveJoinAddNotNullRule in the optimization phase solves this issue.
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