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[GitHub] [spark] ivoson commented on a change in pull request #32557: [SPARK-35411][SQL] Add essential information while serializing TreeNode to json

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ivoson commented on a change in pull request #32557: URL: https://github.com/apache/spark/pull/32557#discussion_r634256260 ## File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/trees/TreeNode.scala ## @@ -997,9 +997,11 @@ abstract class TreeNode[BaseType <:

[GitHub] [spark] itholic commented on a change in pull request #32161: [SPARK-35025][SQL][PYTHON][DOCS] Move Parquet data source options from Python and Scala into a single page.

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itholic commented on a change in pull request #32161: URL: https://github.com/apache/spark/pull/32161#discussion_r634248907 ## File path: python/pyspark/sql/readwriter.py ## @@ -1259,12 +1218,15 @@ def parquet(self, path, mode=None, partitionBy=None, compression=None):

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[GitHub] [spark] maropu commented on pull request #32536: [SPARK-35398][SQL] Simplify the way to get classes from ClassBodyEvaluator in `CodeGenerator.updateAndGetCompilationStats` method

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maropu commented on pull request #32536: URL: https://github.com/apache/spark/pull/32536#issuecomment-843035882 Ah, okay. Thank you for the investigation. If so, I think we don't need to add tests. Instead of it, could you update the PR description to describe how you checked if the stats

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[GitHub] [spark] lipzhu commented on pull request #32572: [SPARK-35305][BUILD] Upgrade Zookeeper to 3.7.0

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lipzhu commented on pull request #32572: URL: https://github.com/apache/spark/pull/32572#issuecomment-843021436 Yes, you are right, the list CVE were resolved by `netty-all 4.1.63.Final`. For zookeeper, version 3.6.3 https://zookeeper.apache.org/doc/r3.6.3/releasenotes.html includes

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[GitHub] [spark] cloud-fan commented on pull request #32542: [SPARK-35403][SQL] Migrate ALTER TABLE commands that alter columns to use UnresolvedTable to resolve the identifier

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cloud-fan commented on pull request #32542: URL: https://github.com/apache/spark/pull/32542#issuecomment-843013396 I think there are 2 options we can pick: 1. Have a single `AlterTable` logical plan, which has 2 members: `table: LogicalPlan` and `changes: Seq[TableChange]`. We also have

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[GitHub] [spark] bozhang2820 commented on pull request #32434: [SPARK-35312][SS] Introduce new Option in Kafka source to specify minimum number of records to read per trigger

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bozhang2820 commented on pull request #32434: URL: https://github.com/apache/spark/pull/32434#issuecomment-843006824 I think it would be nice if we can extend ReadLimit for this, as that would be the centralized interface to control data consumption from different sources. For

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HyukjinKwon commented on a change in pull request #32161: URL: https://github.com/apache/spark/pull/32161#discussion_r634199138 ## File path: python/pyspark/sql/readwriter.py ## @@ -1259,12 +1218,15 @@ def parquet(self, path, mode=None, partitionBy=None, compression=None):

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[GitHub] [spark] LuciferYang edited a comment on pull request #32536: [SPARK-35398][SQL] Simplify the way to get classes from ClassBodyEvaluator in `CodeGenerator.updateAndGetCompilationStats` method

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LuciferYang edited a comment on pull request #32536: URL: https://github.com/apache/spark/pull/32536#issuecomment-842979946 @maropu for the above problem, can we add a case similar to the following to compare the result of `reflection api and using ClassBodyEvaluator.getBytecodes api`

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