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https://issues.apache.org/jira/browse/HIVE-10673?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Jason Dere updated HIVE-10673:
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Attachment: HIVE-10673.8.patch
Fixing failure in tez_smb_1.q - the big table position in
CommonMergeJoinOperator and the ReduceWork were different, they need to be
consistent for the merge join to work properly.
> Dynamically partitioned hash join for Tez
> -----------------------------------------
>
> Key: HIVE-10673
> URL: https://issues.apache.org/jira/browse/HIVE-10673
> Project: Hive
> Issue Type: New Feature
> Components: Query Planning, Query Processor
> Reporter: Jason Dere
> Assignee: Jason Dere
> Attachments: HIVE-10673.1.patch, HIVE-10673.2.patch,
> HIVE-10673.3.patch, HIVE-10673.4.patch, HIVE-10673.5.patch,
> HIVE-10673.6.patch, HIVE-10673.7.patch, HIVE-10673.8.patch
>
>
> Some analysis of shuffle join queries by [~mmokhtar]/[~gopalv] found about
> 2/3 of the CPU was spent during sorting/merging.
> While this does not work for MR, for other execution engines (such as Tez),
> it is possible to create a reduce-side join that uses unsorted inputs in
> order to eliminate the sorting, which may be faster than a shuffle join. To
> join on unsorted inputs, we can use the hash join algorithm to perform the
> join in the reducer. This will require the small tables in the join to fit in
> the reducer/hash table for this to work.
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