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test passed, merged to master/2.3.
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--- Diff:
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@@ -34,17 +34,25 @@ private[spark] class
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LGTM
I'm going to merge this with master and branch-2.3, backporting as a
fairly important bug fix
Thanks @MrBago !
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Thanks! I'll do.
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cc @zsxwing
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Updated!
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as a follow-up, we should do the same thing for struct and map type too.
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thanks, merging to master/2.3!
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retest this please
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sorry this is a little late, but lgtm too. agree with the points above
about leaving the old name deprecated and moving to the new name
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change is fine, but from discussion on the jira I'm unclear if this is
really worth it -- gain seems pretty small after the other fix in 2.3.
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Github user HyukjinKwon commented on the issue:
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Wait .. Isn't this because we failed to call `toInternal` by the return
type? Please give me few days .. will double check tonight.
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@steveloughran can you bring this up on dev@? we should move this
discussion off of this PR.
(sorry haven't had a chance to look yet, but I appreciate you doing this)
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--- Diff: python/pyspark/sql/udf.py ---
@@ -26,6 +26,28 @@
def _wrap_function(sc, func, returnType):
+def coerce_to_str(v):
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Github user icexelloss commented on the issue:
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I think Scalar and Group map UDF expect pandas Series of datetime64[ns]
(native pandas timestamp type) instead of a pandas Series of datetime.date and
datetime.datetime object. I don't think
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retest this please
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LGTM, merging to master/2.3!
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+/*
+ * Licensed to the
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retest this please
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LGTM, cc @ueshin @icexelloss does this behavior consistent with pandas UDF?
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GitHub user rednaxelafx opened a pull request:
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[SPARK-22966][PySpark] Spark SQL should handle Python UDFs that return a
datetime.date or datetime.datetime
## What changes were proposed in this pull request?
Perform appropriate
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Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/20161
Merged build finished. Test PASSed.
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