Github user hvanhovell closed the pull request at:
https://github.com/apache/spark/pull/8298
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Github user hvanhovell commented on the pull request:
https://github.com/apache/spark/pull/8298#issuecomment-134620114
@adrian-wang the improvement is absolutely tiny, about 2-3% if you do a lot
of ```min```'s of ```max```'es.
This PR was a response to misdiagnosed performance
Github user adrian-wang commented on the pull request:
https://github.com/apache/spark/pull/8298#issuecomment-134054452
I doubt that whether your decision tree is better. But GreaterThan/LessThan
should be a little better than Least/Greatest, I think.
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Github user adrian-wang commented on a diff in the pull request:
https://github.com/apache/spark/pull/8298#discussion_r37721828
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/functions.scala
---
@@ -236,15 +234,13 @@ case class Min(child:
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Github user yhuai commented on the pull request:
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ok to test
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Can one of the admins verify this patch?
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GitHub user hvanhovell opened a pull request:
https://github.com/apache/spark/pull/8298
[SPARK-10100] [SQL] Perfomance improvements to new MIN/MAX aggregate
functions.
The new MIN/MAX suffer from a performance regression. This PR aims to fix
this by simplifying the evaluation of th
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