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https://issues.apache.org/jira/browse/ARROW-6659?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16947901#comment-16947901
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Kyle McCarthy commented on ARROW-6659:
--------------------------------------

Do you have a specific solution in mind? I was thinking that this could be done 
by pulling some of the logic out from the partitions method in the 
HashAggregateExec, but also it probably could work with generics.

> [Rust] [DataFusion] Refactor of HashAggregateExec to support custom merge
> -------------------------------------------------------------------------
>
>                 Key: ARROW-6659
>                 URL: https://issues.apache.org/jira/browse/ARROW-6659
>             Project: Apache Arrow
>          Issue Type: Sub-task
>          Components: Rust, Rust - DataFusion
>            Reporter: Andy Grove
>            Priority: Major
>
> HashAggregateExec current creates one HashPartition per input partition for 
> the initial aggregate per partition, and then explicitly calls MergeExec and 
> then creates another HashPartition for the final reduce operation.
> This is fine for in-memory queries in DataFusion but is not extensible. For 
> example, it is not possible to provide a different MergeExec implementation 
> that would distribute queries to a cluster.
> A better design would be to move the logic into the query planner so that the 
> physical plan contains explicit steps such as:
>  
> {code:java}
> - HashAggregate // final aggregate
>   - MergeExec
>     - HashAggregate // aggregate per partition
>  {code}
> This would then make it easier to customize the plan in other projects, to 
> support distributed execution:
> {code:java}
>  - HashAggregate // final aggregate
>    - MergeExec
>       - DistributedExec
>          - HashAggregate // aggregate per partition{code}



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