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[GitHub] [spark] dongjoon-hyun closed pull request #28997: [SPARK-32172][CORE]Use createDirectory instead of mkdir

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[GitHub] [spark] warrenzhu25 commented on a change in pull request #28972: [SPARK-30794][CORE] Stage Level scheduling: Add ability to set off heap memory

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[GitHub] [spark] tgravescs commented on pull request #28412: [SPARK-31608][CORE][WEBUI] Add a new type of KVStore to make loading UI faster

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tgravescs commented on pull request #28412: URL: https://github.com/apache/spark/pull/28412#issuecomment-654344387 thanks for getting the numbers. yeah in general I agree, I would rather overestimate the memory usage as GC and OOM are bad. in practice if people find it using way less memor

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igreenfield commented on pull request #28629: URL: https://github.com/apache/spark/pull/28629#issuecomment-654356898 @cloud-fan, looking at the code I thought to add the properties in `DAGScheduler` line: 1216-1219 ```scala // Use the scheduling pool, job group, desc

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[GitHub] [spark] cloud-fan commented on pull request #28629: [SPARK-31769][CORE] Add MDC support for driver threads

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cloud-fan commented on pull request #28629: URL: https://github.com/apache/spark/pull/28629#issuecomment-654361051 can you add a new commit? It's easier to review on github This is an automated message from the Apache Git Ser

[GitHub] [spark] cloud-fan commented on a change in pull request #28979: [SPARK-32154][SQL] Use ExpressionEncoder for the return type of ScalaUDF to convert to catalyst type

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cloud-fan commented on a change in pull request #28979: URL: https://github.com/apache/spark/pull/28979#discussion_r450365549 ## File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/encoders/ExpressionEncoder.scala ## @@ -285,7 +285,7 @@ case class ExpressionEn

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cloud-fan commented on a change in pull request #28979: URL: https://github.com/apache/spark/pull/28979#discussion_r450366063 ## File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/ScalaUDF.scala ## @@ -62,7 +65,7 @@ case class ScalaUDF( * Nil(

[GitHub] [spark] huaxingao commented on pull request #28960: [SPARK-32140][ML][PySpark] Add training summary to FMClassificationModel

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huaxingao commented on pull request #28960: URL: https://github.com/apache/spark/pull/28960#issuecomment-654362232 This is a python 2 failure only, python 3 is OK. I think I can simply change test data to get around this, but I found one more problem that I didn't have time to fix yet.

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[GitHub] [spark] Sudhar287 commented on a change in pull request #29008: [SPARK-31579][SQL] replaced floorDiv to Div

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[GitHub] [spark] dongjoon-hyun commented on pull request #29006: [SPARK-32058][BUILD][SQL][test-hive1.2][test-hadoop2.7][FOLLOWUP] Set hadoop 2.7.4 for hive 1.2 profile

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dongjoon-hyun commented on pull request #29006: URL: https://github.com/apache/spark/pull/29006#issuecomment-654366581 BTW, @yaooqinn . Please use a new JIRA ID because `banning a dependency` is orthogonal to SPARK-32058. Th

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[GitHub] [spark] huaxingao commented on pull request #28990: [SPARK-32164][ML] GeneralizedLinearRegressionSummary optimization

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huaxingao commented on pull request #28990: URL: https://github.com/apache/spark/pull/28990#issuecomment-654367357 I will merge this PR :) I had problem with my jira account earlier and I think it's OK now. I will use this PR to test if everything works OK for me. I will leave this

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[GitHub] [spark] rdblue commented on pull request #28993: [SPARK-32168][SQL] Fix hidden partitioning correctness bug in SQL overwrite

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rdblue commented on pull request #28993: URL: https://github.com/apache/spark/pull/28993#issuecomment-654381321 The tests were failing because `InMemoryTable` was ignoring hidden partitions when building partition keys. I implemented the rest of the transforms needed for the tests to fix i

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rdblue edited a comment on pull request #28993: URL: https://github.com/apache/spark/pull/28993#issuecomment-654381321 The tests were failing because `InMemoryTable` was ignoring hidden partitions when building partition keys. I implemented the rest of the transforms needed for the tests t

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