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--- Diff:
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retest this please
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Github user rxin commented on the issue:
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@xuanyuanking can you separate the prs to rename read side metric and the
write side change?
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In short, we need to run the tests on the three patterns below, right?
- wholeStage=true, factoryMode=CODEGEN_ONLY (default behaviour in Spark)
- wholeStage=false, factoryMode=CODEGEN_ONLY
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Github user HeartSaVioR commented on the issue:
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@gaborgsomogyi
That's really huge... Could you share how you tested? Like which FS
(local/HDFS/S3/etc), directory structure, count of files... That would help me
understanding the impact
Github user viirya commented on the issue:
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> Compared to the error values from the test failures above, they match up
until the 10th batch but then these continue until the 16th where it has a
timeout
I suspect that might because as
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retest this please
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Github user kevinyu98 commented on the issue:
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Retest please, I didn't change Pyspark code, and tested
`--modules=pyspark-sql` in local machine, it is fine. Thanks
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Thanks guys .. I will try to take a look for it as well (although it's
going to take relatively a long while). Let me get this in for now anyway.
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I agree with @BryanCutler's analysis and it looks a bit weird at few things
about this test. I also think it is fine to increase the timeout for now.
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True, the test is not that long under light resources. Locally, I saw a
couple seconds difference with the changes I mentioned. The weird thing is the
unmodified test completes after the 11th
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If a test passes without/with this changes, it wouldn't verify the
regression.
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Thanks for a close look, @BryanCutler. I just increased the timeout because
I was just trying to keep the test as is and fix it. The actual test doesn't
look taking so much time but it looks it
Github user dima-asana commented on the issue:
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> @dima-asana can you rebase, and add a simple test case or else find one
that does demonstrate the behavior here?
done, sorry for the delay
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Please use the PR title and summary to describe the solution, not the
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ok to test
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I think I've made my case for this patch as best I can. It does not appear
this PR has unanimous support, but I continue to believe we should merge it to
master. So where do we take it from here?
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@BryanCutler Thank you very much for your review! I will submit changes
soon.
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Hi @dbtsai @HyukjinKwon @gatorsmile @viirya. Can we merge this to master?
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Done, thanks @dongjoon-hyun
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Rather than controlling the queue sizes it would be better to limit the max
epoch backlog and fail the query once that threshold is reached. There already
seems to be patch that attempted to
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@dongjoon-hyun Thank you very much for your review. I will make the changes
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https://github.com/apache/spark/pull/23072#discussion_r239250335
--- Diff: R/pkg/R/mllib_clustering.R ---
@@ -610,3 +616,58 @@ setMethod("write.ml", signature(object = "LDAModel",
path = "character"),
Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/21465#discussion_r239245388
--- Diff: python/pyspark/ml/regression.py ---
@@ -705,12 +710,59 @@ def getNumTrees(self):
return self.getOrDefault(self.numTrees)
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