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retest this please
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HyukjinKwon commented on pull request #28833:
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Thanks guys, sure. I will make a followup.
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retest this please
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HyukjinKwon edited a comment on pull request #28993:
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~~One question
https://github.com/apache/spark/pull/28993#discussion_r451234819. Otherwise, I
am okay considering that it's still under development.~~ I misread.
HyukjinKwon edited a comment on pull request #28993:
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~~One question
https://github.com/apache/spark/pull/28993#discussion_r451234819. Otherwise, I
am okay considering that it's still under development. ~~ I misread.
HyukjinKwon commented on a change in pull request #28993:
URL: https://github.com/apache/spark/pull/28993#discussion_r451292098
##
File path:
sql/catalyst/src/test/scala/org/apache/spark/sql/connector/InMemoryTable.scala
##
@@ -78,10 +92,44 @@ class InMemoryTable(
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dongjoon-hyun edited a comment on pull request #28833:
URL: https://github.com/apache/spark/pull/28833#issuecomment-655295006
Could you make a follow-up(full revert or partial revert) as what you
suggest, @HyukjinKwon ?
dongjoon-hyun commented on pull request #28833:
URL: https://github.com/apache/spark/pull/28833#issuecomment-655295006
Could you make a follow-up as what you suggest, @HyukjinKwon ?
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retest this please
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retest this please
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cloud-fan commented on pull request #28833:
URL: https://github.com/apache/spark/pull/28833#issuecomment-655292960
`NullType` is a stable public class, I don't think we can drop it.
The intention is to only allow parsing `NullType` for the type string of
legacy hive tables. But
dongjoon-hyun edited a comment on pull request #28833:
URL: https://github.com/apache/spark/pull/28833#issuecomment-655291242
First of all, it's not a good idea to add `NullType` into a new Spark
datatype officially. Not only the exposure causes more complexity, but also
what can we do in
dongjoon-hyun commented on pull request #28833:
URL: https://github.com/apache/spark/pull/28833#issuecomment-655291242
First of all, it's not a good idea to add `NullType` into a new Spark
datatype officially. If that is an official type, what can we do in Spark SQL
world
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sarutak commented on a change in pull request #28803:
URL: https://github.com/apache/spark/pull/28803#discussion_r451282622
##
File path: core/src/main/scala/org/apache/spark/ui/jobs/AllJobsPage.scala
##
@@ -184,20 +188,52 @@ private[ui] class AllJobsPage(parent: JobsTab,
gengliangwang commented on pull request #28803:
URL: https://github.com/apache/spark/pull/28803#issuecomment-655283658
@sarutak I am really sorry I missed your ping last week.
The perf problem is resolved in https://github.com/apache/spark/pull/28806.
If we want to avoid perf issue in
sarutak commented on a change in pull request #28803:
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File path: core/src/main/scala/org/apache/spark/ui/jobs/AllJobsPage.scala
##
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gengliangwang commented on a change in pull request #28803:
URL: https://github.com/apache/spark/pull/28803#discussion_r451280315
##
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##
@@ -184,20 +188,52 @@ private[ui] class AllJobsPage(parent:
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retest this please
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jenkins, retest this, please
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retest this please
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cloud-fan commented on pull request #28993:
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> python/pyspark/mllib/tests/test_streaming_algorithms.py", line 461, in
condition
>self.assertGreater(errors[1] - errors[-1], 2)
> AssertionError: 1.672640157855923
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##
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##
@@ -78,10 +92,44 @@ class InMemoryTable(
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HyukjinKwon edited a comment on pull request #28833:
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Re: https://github.com/apache/spark/pull/28833#discussion_r448165084
Sorry I read the comments just now. So the decision here is we allow to
parse `void` as
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