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Can one of the admins verify this patch?
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Thanks! Merged to master/2.3
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[SPARK-23261][PYSPARK][BACKPORT-2.3] Rename Pandas UDFs
This PR is to backport https://github.com/apache/spark/pull/20428 to Spark
2.3 without adding the changes regarding `GROUPED AGG PANDAS
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Yes. We need to avoid the performance regression since the last release
Spark 2.2
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I see. The baseline is 2.2, right?
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This is to revert back to the original behavior. Thus, we do not introduce
anything else compared with 2.2
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@gatorsmile .
In the original PR, https://github.com/apache/spark/pull/18810, there was a
microbenchmark.
Can we have the result on the same benchmark here, too?
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Thanks for submitting the PR https://github.com/apache/spark/pull/20433. It
sounds like there are still some test failure. Will review it after 2.3
release. Thanks!
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@maropu Yeah. As long as the queries are different, we should keep both
versions. This is to help the others understand we fully support TPC-DS queries
without the changes. Thanks!
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LGTM to adding the new package of partitioning/distribution.
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retest this please
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@rdblue The target is 2.3 release. Thanks for your time!
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Streaming part LGTM; I have no particular opinion or context on the
distribution stuff.
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cc @zsxwing @marmbrus too
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retest this please
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Will submit a new PR to 2.3
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Let me manually push it to 2.3. Thanks!
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Yes. We need to backport it to 2.3
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@cloud-fan, is the intent to get this into 2.3.0? If so, I'll make time to
review it today.
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@kiszk TPC-DS just shows the typical data analytics workloads. However,
Spark SQL is being used for ETL like workloads. The regression happened in a
complex pipeline of structured streaming
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Github user icexelloss commented on the issue:
https://github.com/apache/spark/pull/20295
Rebased
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