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https://issues.apache.org/jira/browse/DRILL-5293?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Kunal Khatua closed DRILL-5293.
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Marking as verified and closing.

> Poor performance of Hash Table due to same hash value as distribution below
> ---------------------------------------------------------------------------
>
>                 Key: DRILL-5293
>                 URL: https://issues.apache.org/jira/browse/DRILL-5293
>             Project: Apache Drill
>          Issue Type: Bug
>          Components: Execution - Codegen
>    Affects Versions: 1.8.0
>            Reporter: Boaz Ben-Zvi
>            Assignee: Boaz Ben-Zvi
>              Labels: ready-to-commit
>             Fix For: 1.10.0
>
>
> The computation of the hash value is basically the same whether for the Hash 
> Table (used by Hash Agg, and Hash Join), or for distribution of rows at the 
> exchange. As a result, a specific Hash Table (in a parallel minor fragment) 
> gets only rows "filtered out" by the partition below ("upstream"), so the 
> pattern of this filtering leads to a non uniform usage of the hash buckets in 
> the table.
>   Here is a simplified example: An exchange partitions into TWO (minor 
> fragments), each running a Hash Agg. So the partition sends rows of EVEN hash 
> values to the first, and rows of ODD hash values to the second. Now the first 
> recomputes the _same_ hash value for its Hash table -- and only the even 
> buckets get used !!  (Or with a partition into EIGHT -- possibly only one 
> eighth of the buckets would be used !! ) 
>    This would lead to longer hash chains and thus a _poor performance_ !
> A possible solution -- add a distribution function distFunc (only for 
> partitioning) that takes the hash value and "scrambles" it so that the 
> entropy in all the bits effects the low bits of the output. This function 
> should be applied (in HashPrelUtil) over the generated code that produces the 
> hash value, like:
>    distFunc( hash32(field1, hash32(field2, hash32(field3, 0))) );
> Tested with a huge hash aggregate (64 M rows) and a parallelism of 8 ( 
> planner.width.max_per_node = 8 ); minor fragments 0 and 4 used only 1/8 of 
> their buckets, the others used 1/4 of their buckets.  Maybe the reason for 
> this variance is that distribution is using "hash32AsDouble" and hash agg is 
> using "hash32".  



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