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Ping @ueshin, do you think of the current state of the PR?
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--- Diff: python/pyspark/sql/tests.py ---
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bool_f(col('bool')))
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@liyinan926 -- not yet, will be running them shortly.
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Thank you for review and commit @vanzin !
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@foxish have you run the integration tests against this on both minikube
and GKE?
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> I suggest running more tests(real workloads)
I've tested all of these PRs attached to SPARK-18085 with lots of real and
synthetic app logs.
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Github user bowei commented on the issue:
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Confirmed -- the FQDN is not going to work on clusters that have a custom
cluster suffix.
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cc/ @zihongz @bowei from K8s networking - can you guys confirm that using
`..svc` is strictly better than using the FQDN which
made an assumption of the dns zone (cluster.local)?
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ok SGTM
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[SPARK-22992][K8S] Remove assumption of the DNS domain
## What changes were proposed in this pull request?
Remove the use of FQDN to access the driver because it assumes that it's
set up in
Github user CodingCat commented on the issue:
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I see, I didn't recognize that the same registry is used to for source as
well.
in this case, even we have some way to eliminate MetricsRegistry from the
API signature, haven't we still i
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retest this please
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Can one of the admins verify this patch?
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thanks, merging to master/2.3!
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@gatorsmile I think now it is ready for review, thanks.
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Github user srowen commented on the issue:
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@wangyum any comments on the follow-up here? if you've observed it gets the
desired behavior, that's pretty convincing. At least we should treat both
timeouts consistently.
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Github user HyukjinKwon commented on the issue:
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To be honest, just to share what have been on my mind on this so far, I
have been trying to think if it's worth vs the amount of changes, in
particular, we now happen to have some divergence, `m
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Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/20186
good catch! LGTM
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Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/20186
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GitHub user gengliangwang opened a pull request:
https://github.com/apache/spark/pull/20186
[SPARK-22990][Core] Fix method isFairScheduler in JobsTab and StagesTab
## What changes were proposed in this pull request?
In current implementation, the function `isFairScheduler` i
Github user mgaido91 commented on the issue:
https://github.com/apache/spark/pull/19492
any more comments on this @viirya @HyukjinKwon?
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Github user mgaido91 commented on a diff in the pull request:
https://github.com/apache/spark/pull/20023#discussion_r160147366
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/types/DecimalType.scala ---
@@ -117,6 +117,7 @@ object DecimalType extends AbstractDataType {
Github user henrify commented on the issue:
https://github.com/apache/spark/pull/19943
@dongjoon-hyun It is possible that the "multiple byte arrays" case happens
only in write side when consumer code explicitly does it, and it is fine to use
the single byte array and putArray() in rea
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/19993
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Github user mgaido91 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19993#discussion_r160143590
--- Diff: mllib/src/main/scala/org/apache/spark/ml/param/params.scala ---
@@ -249,6 +250,27 @@ object ParamValidators {
def arrayLengthGt[T](lowerBou
Github user gaborgsomogyi commented on a diff in the pull request:
https://github.com/apache/spark/pull/20019#discussion_r160143221
--- Diff:
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/parser/ExpressionParserSuite.scala
---
@@ -263,21 +263,60 @@ class ExpressionPars
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/13599
(re) cc @Stibbons for reviewing. I think you are another right one to
review this given https://github.com/apache/spark/pull/14180. Let's start to
incrementally improve this feature unless you a
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/13599
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Github user zjffdu commented on the issue:
https://github.com/apache/spark/pull/13599
@holdenk @ueshin @HyukjinKwon Thanks for review the long pending PR. Will
refine the PR soon.
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