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retest this please
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--- Diff:
network/common/src/main/java/org/apache/spark/network/client/StreamInterceptor.java
---
@@ -0,0 +1,76 @@
+/*
+ * Licensed to the Apache Sof
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--- Diff:
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ch
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SharedSQLC
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LGTM
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/cc @andrewor14 @tdas
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@andrewor14 I just opened #9428 to take over #7021 and fix potential issues
in the previous PR.
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Pr7021
Took over #7021 and fixed the following potential issues in the previous PR:
1. Make sure checkpointing all data even if the Iterator is not drained.
2. Make sure checkpointing al
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Github user calvinjia commented on the pull request:
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@pwendell @yhuai
Thanks for the pointers and reviewing this PR.
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Github user Lewuathe commented on the pull request:
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@shivaram Sure. I'll submit.
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Github user pwendell commented on the pull request:
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Got it- thanks I can merge it then.
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Github user JoshRosen commented on the pull request:
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Ping @slachiewicz, do you mind either addressing Sean's comments or closing
this PR?
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--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/unresolved.scala
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@@ -166,26 +166,63 @@ abstract class Star extends LeafExpres
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--- Diff: core/src/main/scala/org/apache/spark/deploy/SparkSubmit.scala ---
@@ -520,6 +520,8 @@ object SparkSubmit {
}
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Github user jegonzal commented on the pull request:
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This is actually a pretty serious error since it could lead to mass being
accumulated on unreachable sub-graphs. The performance implications of the
above branch shoul
Github user JoshRosen closed the pull request at:
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@yhuai I think it's pretty low-risk. I'm going to close this PR and will
continue work over at #9427, which is opened against branch-1.5.
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[SPARK-11293] Fix shuffle memory leaks in Spillable collections and
UnsafeShuffleWriter (branch-1.5)
This patch fixes multiple memory leaks in `Spillable` collections, as well
as a leak in `Unsaf
Github user dwmclary commented on the pull request:
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Yes, I agree, it shouldn't add overhead.
Sent from my iPhone
> On Nov 2, 2015, at 4:35 PM, DB Tsai wrote:
>
> I think the branching should be
Github user chenghao-intel commented on the pull request:
https://github.com/apache/spark/pull/9419#issuecomment-153207195
@gatorsmile thanks for working on this fixing, can you also add the unit
test?
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@pwendell
We changed the default hadoop version from 2.2. MIMA was pulling in
`hadoop2.2` jars into the `lib_managed` directory when it built `oldDeps`. In
`spark
Github user vectorijk commented on the pull request:
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Thanks @mengxr @dbtsai !
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--- Diff: mllib/src/main/scala/org/apache/spark/ml/r/SparkRWrappers.scala
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@@ -51,13 +51,22 @@ private[r] object SparkRWrappers {
pipeline.fit(d
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Ok, thanks for explanation.
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Github user dbtsai commented on the pull request:
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I think the branching should be fine since it's just initialization.
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Hey @calvinjia seems okay to merge since this is just triggering other
failures. Can you explain more though how this works around the mima issue -
the patch seems the
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`unhandledFilter` will not see filters using partitioning columns.
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Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/9302#discussion_r43703873
--- Diff: mllib/src/main/scala/org/apache/spark/ml/feature/RFormula.scala
---
@@ -200,6 +200,13 @@ class RFormulaModel private[feature](
dataset.sch
GitHub user dbtsai opened a pull request:
https://github.com/apache/spark/pull/9426
[MINOR][ML] removed the old `getModelWeights` function
Removed the old `getModelWeights` function which was private and renamed
into `getModelCoefficients`
You can merge this pull request into a Git
Github user vanzin commented on the pull request:
https://github.com/apache/spark/pull/9425#issuecomment-153203185
The failure should not be related to the version of hadoop, so testing with
2.x should be fine.
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Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/9425#issuecomment-153202972
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Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/9425#issuecomment-153202952
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Github user chenghao-intel commented on the pull request:
https://github.com/apache/spark/pull/9399#issuecomment-153202825
Ok, actually I was planning to optimize the expression with partition key,
which will introduce the `ConstantFolding`, as the partition key will be a
constant val
Github user yhuai commented on the pull request:
https://github.com/apache/spark/pull/9425#issuecomment-153202719
Thanks for the PR! btw, if you want jenkins to test hadoop1, you can add
`[test-hadoop1.0]` to the title.
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Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/9422#issuecomment-153202611
**[Test build #44854 has
started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/44854/consoleFull)**
for PR 9422 at commit
[`5c0da8e`](https://gith
Github user yhuai commented on the pull request:
https://github.com/apache/spark/pull/9260#issuecomment-153202532
Is it risky? Looks not?
If it is safe patch, wow about we add the check in `Task.scala` first to
make sure that 1.5 does throw the exception? Then, we add the fix
Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/9404#issuecomment-153202279
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Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/9404#issuecomment-153202255
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