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https://issues.apache.org/jira/browse/DRILL-4119?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15020665#comment-15020665
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Aman Sinha commented on DRILL-4119:
-----------------------------------
Yes, it would be useful to have a suite for the hashing. The number of
combinations is large: num_data_types x nullability x num_hash_function_types
(32bit, 64bit, AsDouble variations). Plus, the nature of the data itself - we
need real world data for testing the quality of the distribution. Let me see
if I can at least have a minimal test suite with some sample of the above
combinations. I may end up creating a separate JIRA.
> Skew in hash distribution for varchar (and possibly other) types of data
> ------------------------------------------------------------------------
>
> Key: DRILL-4119
> URL: https://issues.apache.org/jira/browse/DRILL-4119
> Project: Apache Drill
> Issue Type: Bug
> Components: Functions - Drill
> Affects Versions: 1.3.0
> Reporter: Aman Sinha
> Assignee: Aman Sinha
>
> We are seeing substantial skew for an Id column that contains varchar data of
> length 32. It is easily reproducible by a group-by query:
> {noformat}
> Explain plan for SELECT SomeId From table GROUP BY SomeId;
> ...
> 01-02 HashAgg(group=[{0}])
> 01-03 Project(SomeId=[$0])
> 01-04 HashToRandomExchange(dist0=[[$0]])
> 02-01 UnorderedMuxExchange
> 03-01 Project(SomeId=[$0],
> E_X_P_R_H_A_S_H_F_I_E_L_D=[castInt(hash64AsDouble($0))])
> 03-02 HashAgg(group=[{0}])
> 03-03 Project(SomeId=[$0])
> {noformat}
> The string id happens to be of the following type:
> {noformat}
> e4b4388e8865819126cb0e4dcaa7261d
> {noformat}
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