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https://issues.apache.org/jira/browse/BEAM-11881?focusedWorklogId=567000&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-567000
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ASF GitHub Bot logged work on BEAM-11881:
-----------------------------------------

                Author: ASF GitHub Bot
            Created on: 16/Mar/21 14:13
            Start Date: 16/Mar/21 14:13
    Worklog Time Spent: 10m 
      Work Description: TheNeuralBit commented on pull request #14135:
URL: https://github.com/apache/beam/pull/14135#issuecomment-800291507


   The force push I did was my attempt to clean up commits - squashing together 
fixups. The remaining commits are largely independent portions of the refactor, 
along with some small commits fixing bugs that the refactor exposed, and some 
bulk renames.


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Issue Time Tracking
-------------------

    Worklog Id:     (was: 567000)
    Time Spent: 6h 40m  (was: 6.5h)

> DataFrame subpartitioning order is incorrect
> --------------------------------------------
>
>                 Key: BEAM-11881
>                 URL: https://issues.apache.org/jira/browse/BEAM-11881
>             Project: Beam
>          Issue Type: Bug
>          Components: sdk-py-core
>            Reporter: Brian Hulette
>            Assignee: Brian Hulette
>            Priority: P2
>              Labels: dataframe-api
>             Fix For: 2.30.0
>
>          Time Spent: 6h 40m
>  Remaining Estimate: 0h
>
> Currently we've defined
> Nothing() < Index([i]) < Index([i,j]) < .. < Index() < Singleton()
> s.t. Singleton is a subpartitoning of Index, is a subpartitioning of 
> Index([i,j]), but this is incorrect. The order should be 
> Singleton() < Index([i]) < Index([i,j]) < .. < Index() < Nothing()
> s.t. every other partitioning is a subpartitioning of Singleton. This is 
> logical, since Singleton will collect the largest amount of data on a single 
> node, partitioning by a single index will be alittle more distributed, and 
> partitioning by the full Index() will be the most distribtued.



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