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[GitHub] [spark] cloud-fan commented on a change in pull request #28683: [SPARK-31875][SQL] Provide a option to disable user supplied Hints

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[GitHub] [spark] LantaoJin commented on pull request #28947: [SPARK-32129][SQL] Support AQE skew join with Union

LantaoJin commented on pull request #28947: URL: https://github.com/apache/spark/pull/28947#issuecomment-654661775 > Can we make a general approach here? e.g. if we just optimize SMJ with both sides as shuffle stages, we can even optimize the first join of a 3-table join plan.

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[GitHub] [spark] moomindani commented on a change in pull request #28953: [SPARK-32013][SQL] Support query execution before/after reading/writing DataFrame over JDBC

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[GitHub] [spark] imback82 commented on pull request #23340: [SPARK-23431][CORE] Expose the new executor memory metrics at the stage level

imback82 commented on pull request #23340: URL: https://github.com/apache/spark/pull/23340#issuecomment-654654972 I created a PR here: #29020. I will also ask a reviewing committer to put @edwinalu as a co-author if that's the practice when a PR is "inherited". Thanks!

[GitHub] [spark] LantaoJin opened a new pull request #29021: [SPARK-32201][SQL] More general skew join pattern matching

LantaoJin opened a new pull request #29021: URL: https://github.com/apache/spark/pull/29021 ### What changes were proposed in this pull request? Current the AQE skew join handling logic is very specified. It can only handle the pattern like this: ``` SMJ Sort

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[GitHub] [spark] imback82 opened a new pull request #29020: [SPARK-23431][CORE] Expose stage level peak executor metrics via REST API

imback82 opened a new pull request #29020: URL: https://github.com/apache/spark/pull/29020 ### What changes were proposed in this pull request? Note that this PR is forked from #23340 originally written by @edwinalu. This PR proposes to expose the peak executor metrics

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