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viirya commented on pull request #31451: URL: https://github.com/apache/spark/pull/31451#issuecomment-810844094 > @viirya how about the history server? I'm a bit worried about the event log with v2 metrics. Oh, there is a problem on ser/de `aggregateMethod`... -- This is an automa

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cloud-fan commented on pull request #31451: URL: https://github.com/apache/spark/pull/31451#issuecomment-810849844 @viirya I think this is hard to fix. The history server is a different JVM and may not have the data source implementation classes loaded, we can't run the aggregate code in t

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[GitHub] [spark] cloud-fan commented on a change in pull request #31451: [SPARK-34338][SQL] Report metrics from Datasource v2 scan

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[GitHub] [spark] srowen closed pull request #32008: [SPARK-34911][SQL] Fix code not close issue in monitoring.md

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cloud-fan commented on pull request #30144: URL: https://github.com/apache/spark/pull/30144#issuecomment-810864610 Can we enrich the PR description a bit more? Now we support `group by a, cube(b, c)`, but what's its semantic? Does it have a equivalent representation using `GROUPING SETS`?

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cloud-fan commented on pull request #30144: URL: https://github.com/apache/spark/pull/30144#issuecomment-810866475 Please update the SQL doc accordingly as well. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL

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[GitHub] [spark] xuanyuanking commented on pull request #31944: [SPARK-34854][SQL][SS] Expose source metrics via progress report and add Kafka use-case to report delay.

xuanyuanking commented on pull request #31944: URL: https://github.com/apache/spark/pull/31944#issuecomment-810876034 ``` They want to dynamically adjust the size of the cluster based on how far they're falling behind the latest. With this PR, they can be exposed to this metrics through

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sadhen commented on pull request #31735: URL: https://github.com/apache/spark/pull/31735#issuecomment-810886187 > @HyukjinKwon: > Furthermore, we will probably have to do it for toPandas and createDataFrame with Arrow optimization on. It should be best to think about these cases as well

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sadhen edited a comment on pull request #31735: URL: https://github.com/apache/spark/pull/31735#issuecomment-810886187 > @HyukjinKwon: > Furthermore, we will probably have to do it for toPandas and createDataFrame with Arrow optimization on. It should be best to think about these cases

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[GitHub] [spark] AngersZhuuuu commented on a change in pull request #30144: [SPARK-33229][SQL] Support GROUP BY use Separate columns and CUBE/ROLLUP

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[GitHub] [spark] ulysses-you opened a new pull request #32012: [SPARK-34919][SQL] Change partitioning to SinglePartition if partition number is 1

ulysses-you opened a new pull request #32012: URL: https://github.com/apache/spark/pull/32012 ### What changes were proposed in this pull request? Change partitioning to `SinglePartition`. ### Why are the changes needed? For node `Repartition` and `RepartitionByE

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[GitHub] [spark] gaborgsomogyi commented on a change in pull request #32009: [SPARK-34914][CORE] Local scheduler backend support update token

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[GitHub] [spark] wangyum opened a new pull request #32013: [WIP][SPARK-34920][SQL] Add SQLSTATE and ERRORCODE to SQL exception

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