Spark Runner: Change to use partitioner in GroupNonMergingWindowsFunctions#groupByKeyInGlobalWindow

[twosom]

Please add a meaningful description for your change here

fixes #32608

This PR contains these changes

• change GroupNonMergingWindowsFunctions#groupByKeyInGlobalWindow to use partitioner
• add related test

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[twosom]

Run Java PreCommit

[twosom]

I think task fails is not related to this PR.

[twosom]

Run Java PreCommit

[twosom]

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[je-ik]

LGTM overall, just one question from higher-level perspective. Given that the only partitioner that is ever passed to this method is returned by

  private static @Nullable Partitioner getPartitioner(SparkTranslationContext context) {
    Long bundleSize =
        context.serializablePipelineOptions.get().as(SparkPipelineOptions.class).getBundleSize();
    return (bundleSize > 0)
        ? null
        : new HashPartitioner(context.getSparkContext().defaultParallelism());
  }

does this change have any practical impact? I would expect that the HashPartitioner with default parallelism is what would be used when the partitioner is unused, is this assumption wrong?

[je-ik]

I think we can remove these lines, the purpose of the file is to be just touched somehow for the tests to run. We might replace the old comment with a single one.

[twosom]

@je-ik
Thanks! I rollbacked trigger files!

[twosom]

LGTM overall, just one question from higher-level perspective. Given that the only partitioner that is ever passed to this method is returned by

  private static @Nullable Partitioner getPartitioner(SparkTranslationContext context) {
    Long bundleSize =
        context.serializablePipelineOptions.get().as(SparkPipelineOptions.class).getBundleSize();
    return (bundleSize > 0)
        ? null
        : new HashPartitioner(context.getSparkContext().defaultParallelism());
  }

does this change have any practical impact? I would expect that the HashPartitioner with default parallelism is what would be used when the partitioner is unused, is this assumption wrong?

Yes, as you mentioned, following the code ultimately leads to using the HashPartitioner.
However, I assumed that the partitioner would be passed as a parameter to the GroupNonMergingWindowsFunctions#groupByKeyInGlobalWindow method, so that it could be used if necessary.
While the current changes may not have a significant practical impact, this decision was made with future extensibility in mind, allowing the use of custom partitioners for specific Apache Beam PTransforms.
Of course, this may not be necessary in the end, but I wanted to leave room for this kind of flexibility.
Thank you.

[kennknowles]

Seems OK to me. I defer to Jan as well.

[je-ik]

Thanks @twosom!