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Github user BryanCutler commented on a diff in the pull request:
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Github user felixcheung commented on the issue:
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Cool!
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LGTM. Thanks! Merging to master and 2.2.
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Github user tgravescs commented on the issue:
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Yeah if we are releasing and they reacquiring right away over and over
again that would be bad, but I don't know when we would do that so more details
would be great if possible.
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Github user vanzin commented on the issue:
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@bOOm-X
I pushed some code to my repo:
https://github.com/vanzin/spark/tree/SPARK-18838
Which is an attempt to do things the way I've been trying to explain. It
tries to keep
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+/*
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Github user gatorsmile commented on the issue:
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Looks pretty good! Will do the final pass after addressing the above
comments.
Thanks for your work!
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--- Diff: python/pyspark/sql/functions.py ---
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@since(1.3)
-def udf(f=None,
Github user gatorsmile commented on a diff in the pull request:
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Github user vanzin commented on the issue:
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I was told that the preemption issue was fixed in YARN (that's YARN-6210);
so I don't think there's a need for this code currently (just use a fixed YARN
if you want reliable preemption).
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Github user tgravescs commented on the issue:
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It might help if you can give an exact scenario where you see the issue and
perhaps configs if those matter. meaning do you have like some set of minimum
containers, a small idle timeout, etc..
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Github user vanzin commented on the issue:
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LGTM pending tests.
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Github user tgravescs commented on the issue:
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Unfortunately that isn't clear to me as to the cause or what the issue is
with the yarn side.
I'm not sure what he means by "AM is releasing and then acquiring the
reservations again and
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Github user jiangxb1987 commented on the issue:
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It would be great to test the perf on executors with various
corsPerExecutor settings to ensure we don't bring in regressions by the code
change.
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Github user Tagar commented on the issue:
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@tgravescs, here's quote from Wilfred Spiegelenburg - hope it answers both
of your questions.
> The behaviour I discussed earlier around the Spark AM reservations is not
optimal. It turns
Github user tgravescs commented on the issue:
https://github.com/apache/spark/pull/19046
@Tagar can you be more specific about the problems you are seeing? how
does this affect preemption? Why don't you see the same issues on
MapReduce/Tez?
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Github user gatorsmile commented on the issue:
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After more discussion with others, this behavior change really bothers us.
Both changes do not sound good to us. Where is the requirement from?
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Github user holdenk commented on the issue:
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Gentle ping (going through old PySpark PRs) :)
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Github user holdenk commented on the issue:
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Sorry for the delay. Lets get Jenkins to retest this and make sure
everything is ok but it looks like a good change :)
LGTM pending jenkins/merge issues (if they show up during jenkins).
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Github user holdenk commented on a diff in the pull request:
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--- Diff: python/pyspark/ml/tests.py ---
@@ -319,6 +320,20 @@ def test_hasparam(self):
testParams = TestParams()
Github user holdenk commented on the issue:
https://github.com/apache/spark/pull/18826
On the Python side using __repr__ looks reasonable (although I would like
to see a doctest for this). But we really should get @jkbradley or maybe
@dbtsai to take a look on the ML side.
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Github user holdenk commented on the issue:
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Sorry for the slow reply, I left a note with how to get at the tuples
contents (the _call_java is behaving weirdly I'm not sure why its shoving the
tuple into a string).
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@@ -274,6 +274,29 @@ class Word2VecModel private[ml] (
Github user vanzin commented on the issue:
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I'm in general not a fan of adding more and more config options; the end
result is that most people won't enable it until they run into problems, and to
me that's too late.
I'm still
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Github user kevinyu98 commented on a diff in the pull request:
https://github.com/apache/spark/pull/12646#discussion_r137366326
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringExpressions.scala
---
@@ -503,69 +504,319 @@ case class
Github user kevinyu98 commented on a diff in the pull request:
https://github.com/apache/spark/pull/12646#discussion_r137366302
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringExpressions.scala
---
@@ -503,69 +504,319 @@ case class
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Github user Tagar commented on the issue:
https://github.com/apache/spark/pull/19046
> This could just be an adhoc queue but the spark users would lose out to
tez/mapreduce users. I'm pretty positive this will hurt spark users on some of
our cluster so would want performance numbers
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/19136
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