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Posted to reviews@spark.apache.org by "itholic (via GitHub)" <gi...@apache.org> on 2023/05/22 11:16:14 UTC

[GitHub] [spark] itholic opened a new pull request, #41255: [SPARK-42996][CONNECT][PS][ML] Assign JIRA tickets for all failing tests.

itholic opened a new pull request, #41255:
URL: https://github.com/apache/spark/pull/41255

   ### What changes were proposed in this pull request?
   
   This PR proposes to add comments for all pandas-on-Spark with Spark Connect failing tests, with related JIRA tickets.
   
   
   ### Why are the changes needed?
   
   To assign appropriate tasks to efficiently fix the failing tests.
   
   
   ### Does this PR introduce _any_ user-facing change?
   
   No, it's dev-only.
   
   
   ### How was this patch tested?
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   The existing CI should pass
   


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[GitHub] [spark] zhengruifeng closed pull request #41255: [SPARK-42996][CONNECT][PS][ML] Create & assign proper JIRA tickets for all failing tests.

Posted by "zhengruifeng (via GitHub)" <gi...@apache.org>.
zhengruifeng closed pull request #41255: [SPARK-42996][CONNECT][PS][ML] Create & assign proper JIRA tickets for all failing tests.
URL: https://github.com/apache/spark/pull/41255


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[GitHub] [spark] zhengruifeng commented on pull request #41255: [SPARK-42996][CONNECT][PS][ML] Create & assign proper JIRA tickets for all failing tests.

Posted by "zhengruifeng (via GitHub)" <gi...@apache.org>.
zhengruifeng commented on PR #41255:
URL: https://github.com/apache/spark/pull/41255#issuecomment-1558322402

   merged to master


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[GitHub] [spark] itholic commented on pull request #41255: [SPARK-42996][CONNECT][PS][ML] Create & assign proper JIRA tickets for all failing tests.

Posted by "itholic (via GitHub)" <gi...@apache.org>.
itholic commented on PR #41255:
URL: https://github.com/apache/spark/pull/41255#issuecomment-1558217797

   cc @HyukjinKwon @zhengruifeng @ueshin @xinrong-meng 
   Could you please take a look at this when you have time? This is essentially a foundational task for achieving 100% test coverage of the pandas API on Spark, built on top of Spark Connect.


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