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Posted to reviews@spark.apache.org by "zhengruifeng (via GitHub)" <gi...@apache.org> on 2025/12/30 01:48:04 UTC
[PR] [SPARK-54869][PYTHON][TESTS] Apply the standard import of pyarrow compute in `test_arrow_udf_scalar` [spark]
zhengruifeng opened a new pull request, #53640:
URL: https://github.com/apache/spark/pull/53640
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### What changes were proposed in this pull request?
Apply the standard import of pyarrow compute in `test_arrow_udf_scalar`
```
import pyarrow.compute as pc
```
### Why are the changes needed?
There seems to be a bug in cloudpickle when dealing with nested lambdas + submodules like `pa.compute`
see https://github.com/apache/spark/pull/53607, it fixed a failure in Python-Only MacOS26.
This PR applies such change in more tests.
### Does this PR introduce _any_ user-facing change?
no, test-only
### How was this patch tested?
ci
### Was this patch authored or co-authored using generative AI tooling?
no
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Re: [PR] [SPARK-54869][PYTHON][TESTS] Apply the standard import of pyarrow compute in `test_arrow_udf_scalar` [spark]
Posted by "zhengruifeng (via GitHub)" <gi...@apache.org>.
zhengruifeng commented on PR #53640:
URL: https://github.com/apache/spark/pull/53640#issuecomment-3698162498
> Is this something that users can run into? Seems like as long as we have a lambda function that uses `pa.compute` inside we will have issues on MacOS?
@gaogaotiantian I think so, if users use `pa.compute.xxx` with lambdas like the tests in https://github.com/apache/spark/pull/53607/changes, they might occasionally hit this issue.
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Re: [PR] [SPARK-54869][PYTHON][TESTS] Apply the standard import of pyarrow compute in `test_arrow_udf_scalar` [spark]
Posted by "zhengruifeng (via GitHub)" <gi...@apache.org>.
zhengruifeng commented on PR #53640:
URL: https://github.com/apache/spark/pull/53640#issuecomment-3698305345
merged to master
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Re: [PR] [SPARK-54869][PYTHON][TESTS] Apply the standard import of pyarrow compute in `test_arrow_udf_scalar` [spark]
Posted by "zhengruifeng (via GitHub)" <gi...@apache.org>.
zhengruifeng closed pull request #53640: [SPARK-54869][PYTHON][TESTS] Apply the standard import of pyarrow compute in `test_arrow_udf_scalar`
URL: https://github.com/apache/spark/pull/53640
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Re: [PR] [SPARK-54869][PYTHON][TESTS] Apply the standard import of pyarrow compute in `test_arrow_udf_scalar` [spark]
Posted by "gaogaotiantian (via GitHub)" <gi...@apache.org>.
gaogaotiantian commented on PR #53640:
URL: https://github.com/apache/spark/pull/53640#issuecomment-3698426832
> they might occasionally hit this issue.
Shouldn't this be reliably reproducible if it's caused by cloudpickle?
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Re: [PR] [SPARK-54869][PYTHON][TESTS] Apply the standard import of pyarrow compute in `test_arrow_udf_scalar` [spark]
Posted by "zhengruifeng (via GitHub)" <gi...@apache.org>.
zhengruifeng commented on PR #53640:
URL: https://github.com/apache/spark/pull/53640#issuecomment-3698608977
> > they might occasionally hit this issue.
>
> Shouldn't this be reliably reproducible if it's caused by cloudpickle?
I don't have a local reproduer now, it should be reliably on edge combination of testing env and commit.
E.g. it was reliably reproducible in https://github.com/apache/spark/actions/runs/20495264978/job/58904792835 (it only failed in Github action, I cannot reproduce the failure in my local macos at that time), but the test had been fine before this failure (see https://github.com/apache/spark/actions/workflows/build_python_3.11_macos26.yml)
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Re: [PR] [SPARK-54869][PYTHON][TESTS] Apply the standard import of pyarrow compute in `test_arrow_udf_scalar` [spark]
Posted by "gaogaotiantian (via GitHub)" <gi...@apache.org>.
gaogaotiantian commented on PR #53640:
URL: https://github.com/apache/spark/pull/53640#issuecomment-3700759465
Hmm okay. If we can reproduce this locally that would be nice. But for now just let it be.
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Re: [PR] [SPARK-54869][PYTHON][TESTS] Apply the standard import of pyarrow compute in `test_arrow_udf_scalar` [spark]
Posted by "gaogaotiantian (via GitHub)" <gi...@apache.org>.
gaogaotiantian commented on PR #53640:
URL: https://github.com/apache/spark/pull/53640#issuecomment-3698149139
Is this something that users can run into? Seems like as long as we have a lambda function that uses `pa.compute` inside we will have issues on MacOS?
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