GitHub user mccheah opened a pull request:
https://github.com/apache/spark/pull/2608
[SPARK-1860] Worker better app cleanup
First contribution to the project, so apologize for any significant errors.
This PR addresses [SPARK-1860]. The application directories are now
GitHub user mccheah reopened a pull request:
https://github.com/apache/spark/pull/2608
[SPARK-1860] Worker better app cleanup
First contribution to the project, so apologize for any significant errors.
This PR addresses [SPARK-1860]. The application directories are now
Github user mccheah closed the pull request at:
https://github.com/apache/spark/pull/2608
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Github user mccheah closed the pull request at:
https://github.com/apache/spark/pull/2608
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GitHub user mccheah opened a pull request:
https://github.com/apache/spark/pull/2609
[SPARK-1860] More conservative app directory cleanup.
First contribution to the project, so apologize for any significant errors.
This PR addresses [SPARK-1860]. The application directories
Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/2609#discussion_r18316820
--- Diff: core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala
---
@@ -22,6 +22,7 @@ import java.text.SimpleDateFormat
import java.util.Date
Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/2609#discussion_r18365112
--- Diff: core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala
---
@@ -233,8 +244,15 @@ private[spark] class Worker(
} else
Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/2609#discussion_r18365510
--- Diff:
core/src/main/scala/org/apache/spark/deploy/worker/ExecutorRunner.scala ---
@@ -174,7 +168,7 @@ private[spark] class ExecutorRunner
Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/2609#discussion_r18407971
--- Diff: core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala
---
@@ -191,6 +194,8 @@ private[spark] class Worker(
changeMaster
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/2662#issuecomment-58056000
Sorry about that. I think Jenkins should be catching these kinds of build
failures though. Jenkins should attempt to build the project against multiple
versions
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/2662#issuecomment-58057718
Fair enough. The bottom line is that we could be more explicit about this.
Perhaps something in the documentation?
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GitHub user mccheah opened a pull request:
https://github.com/apache/spark/pull/2828
[SPARK-3736] Workers reconnect when disassociated from the master.
Before, if the master node is killed and restarted, the worker nodes
would not attempt to reconnect to the Master. Therefore
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/2828#issuecomment-59408043
One remark is that there are no automated tests in this commit for now.
I was unsuccessful in setting up TestKit to emulate a worker and master
sending messages
Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/2828#discussion_r18977288
--- Diff: core/src/main/scala/org/apache/spark/deploy/master/Master.scala
---
@@ -341,7 +341,11 @@ private[spark] class Master(
case Some
Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/2828#discussion_r18978981
--- Diff: core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala
---
@@ -362,9 +372,19 @@ private[spark] class Worker
Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/2828#discussion_r18986188
--- Diff: core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala
---
@@ -362,9 +372,19 @@ private[spark] class Worker
Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/2828#discussion_r18986702
--- Diff: core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala
---
@@ -362,9 +372,19 @@ private[spark] class Worker
Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/2828#discussion_r18986941
--- Diff: core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala
---
@@ -362,9 +372,19 @@ private[spark] class Worker
Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/2828#discussion_r18988742
--- Diff: core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala
---
@@ -362,9 +372,19 @@ private[spark] class Worker
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/2828#issuecomment-59803881
@JoshRosen agreed with @ash211, this is really good.
Are there any actual comments on the PR, or can it be merged? =)
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Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/2828#issuecomment-59824518
The PR doesn't seem to be related to the unit tests that failed. How shall
we tackle this issue?
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GitHub user mccheah opened a pull request:
https://github.com/apache/spark/pull/2984
Shading the Jetty dependency.
Jetty is a common dependency in projects. Spark is sensitive to the version
of Jetty that is used, but version conflicts should be avoided. Shading Jetty
in a similar
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/2984#issuecomment-60848427
Broken for now, investigating
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Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/2984#issuecomment-60849409
False alarm. This should be okay for review.
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Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/2984#issuecomment-60850543
@vanzin Is there a slated timeline for spark.files.userClassPathFirst to be
done?
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Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/2984#issuecomment-60859256
@JoshRosen any comments? I know you've participated in the dependency
discussion in the past.
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Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/2984#issuecomment-60968644
It's sounding like Spark's dependency tree is so large that we eventually
want a solution that prevents any collision at all whatsoever; a holistic
solution, if you
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/2984#issuecomment-61133142
Any update on this? @JoshRosen @pwendell
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Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/2984#issuecomment-61301013
Requesting an update?
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Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/2984#issuecomment-61339002
Except we also need this to get into 1.2. Can we get this bumped up to be
merged in for that release?
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Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/2984#issuecomment-61582083
Jenkins, test this please
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Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/3130#issuecomment-62029607
@ash211 please take a look at this as well. Going to test now.
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Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/3130#issuecomment-62057981
Working on it. Will let you know shortly.
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Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/3130#issuecomment-62070813
I'm pretty sure this doesn't work when Spark is built with maven. I'm going
to try with sbt, but this is what I've found so far.
I used make-distribution.sh
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/3130#issuecomment-62080459
This is not the way that we pull in the Spark dependency. We launch our
server as a standalone application, and specify that the spark core jar is a
library
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/3130#issuecomment-62195376
@pwendell I tried to run a mvn compile and it broke trying to compile
Spark-SQL. Can you verify you're getting the same behavior? I'm taking your
changes and playing
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/3130#issuecomment-62201800
I also built the project with sbt/sbt clean compile assembly, and when
starting the master, I got the following stack trace:
:43:14 ERROR ActorSystemImpl
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/3130#issuecomment-62210767
It passed mvn compile after clearing the caches once, but now it's failing
on make-distribution in packaging GraphX. Do I need to clear the local caches
before each
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/3130#issuecomment-62211101
Scratch that, it failed on streaming, not GraphX
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Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/3130#issuecomment-62608315
Any update on this?
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GitHub user mccheah opened a pull request:
https://github.com/apache/spark/pull/3275
[SPARK-4349] Checking if parallel collection partition is serializable
Before, the DAGScheduler would determine if a task is serializable by doing
a dry-run serialization of the first task
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/3275#issuecomment-63149863
Please consider the design issues that I think this bug uncovers before
providing comment on the PR.
From what I understand, the original design was to catch
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/2984#issuecomment-63396867
That is what this PR is trying to address, but it is superceded by another
PR now.
https://github.com/apache/spark/issues/3130
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Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/3275#issuecomment-64712768
Hi @pwendell or anyone, is there an update on this?
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Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/3130#issuecomment-65126080
Update on this?
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Github user mccheah closed the pull request at:
https://github.com/apache/spark/pull/3275
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Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/3275#issuecomment-65709183
We want a more generic fix than this. I'll push something new which will be
completely different, addressing the issue further down in the stack.
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Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/3130#issuecomment-65878359
Totally makes sense. I don't think I have enough context in the Spark world
as a whole to suggest a holistic build design, but I agree that this is where
the disconnect
GitHub user mccheah opened a pull request:
https://github.com/apache/spark/pull/3638
[SPARK-4737] Task set manager properly handles serialization errors
Dealing with [SPARK-4737], the handling of serialization errors should not
be the DAGScheduler's responsibility. The task set
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/3130#issuecomment-66189849
Wanted to follow up on this - the priority of getting this done was just
increased for us.
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Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/3638#issuecomment-66357595
Anyone have any comment on this?
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Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/3638#issuecomment-66366316
This is ready for further review.
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Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/3638#issuecomment-66823756
Hi, it would be appreciated if someone could give this patch some love.
Thanks!
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Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/3638#discussion_r21938291
--- Diff: core/src/test/scala/org/apache/spark/SharedSparkContext.scala ---
@@ -30,7 +30,7 @@ trait SharedSparkContext extends BeforeAndAfterAll {
self
Github user mccheah closed the pull request at:
https://github.com/apache/spark/pull/2984
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Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/4155#discussion_r23478673
--- Diff: core/src/main/scala/org/apache/spark/SparkHadoopWriter.scala ---
@@ -106,18 +107,25 @@ class SparkHadoopWriter(@transient jobConf: JobConf
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/4155#issuecomment-71253931
I'm also concerned about the performance ramifications of this. We need to
run performance benchmarks. However, the only critical path that is affected by
this are tasks
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/3656#issuecomment-71526176
Seeing some problems that this PR could address so reviving this thread.
@lawlerd the configurable count would help because if it is known that the
individual
Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/4155#discussion_r23560945
--- Diff:
core/src/main/scala/org/apache/spark/scheduler/OutputCommitCoordinator.scala ---
@@ -0,0 +1,252 @@
+/*
+ * Licensed to the Apache Software
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/4155#issuecomment-71530343
@vanzin that's pretty much what I went with. The actor will receive the
message and for commit permission requests they're farmed off to a thread pool.
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Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/4155#discussion_r23567732
--- Diff:
core/src/main/scala/org/apache/spark/scheduler/OutputCommitCoordinator.scala ---
@@ -0,0 +1,252 @@
+/*
+ * Licensed to the Apache Software
Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/4066#discussion_r24072691
--- Diff:
core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala ---
@@ -596,7 +597,9 @@ private[spark] class TaskSetManager
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/4106#issuecomment-72557914
@pwendell do we need this for Spark 1.3.0? Is the feature merge deadline
already past? I'm uncertain of what my bandwidth will be like but if it needs
to be sped up I
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/4106#issuecomment-72435710
Suggestions make sense. I'm currently on a business trip so it might be a
bit of time before I can get back to this.
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Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/4066#issuecomment-73025607
I think your latest comment is correct, @JoshRosen . We shouldn't hit an
infinite loop because the failing authorized committers will eventually cause
the task set
Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/4066#discussion_r23106734
--- Diff: core/src/main/scala/org/apache/spark/SparkHadoopWriter.scala ---
@@ -105,10 +107,20 @@ class SparkHadoopWriter(@transient jobConf: JobConf
Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/4066#discussion_r23108057
--- Diff: core/src/main/scala/org/apache/spark/SparkHadoopWriter.scala ---
@@ -105,10 +107,20 @@ class SparkHadoopWriter(@transient jobConf: JobConf
Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/4066#discussion_r23108302
--- Diff: core/src/main/scala/org/apache/spark/SparkHadoopWriter.scala ---
@@ -105,10 +107,20 @@ class SparkHadoopWriter(@transient jobConf: JobConf
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/3130#issuecomment-70321240
Looks like we're on the same page. However I believe this still raises the
question of how to best do the shading itself. It looks like the short-term
solution
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/4066#issuecomment-70710069
Instead of having every task require a call back to the driver or master,
can the master broadcast to the executor that a task is being speculated and
any executor
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/4066#issuecomment-70723749
Did you think of any corner cases that you might have missed? In terms of
correctness, this seems okay (although the Jenkins build indicates there are
some issues). Have
Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/4106#discussion_r23326963
--- Diff:
core/src/main/scala/org/apache/spark/deploy/StandaloneSparkHadoopUtil.scala ---
@@ -0,0 +1,76 @@
+/*
+ * Licensed to the Apache Software
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/4106#issuecomment-70891705
That¹s correct. Definitely a work-in-progress so if there¹s another
security
model you¹d recommend I¹m all ears!
-Matt Cheah
From: Tom Graves
Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/4106#discussion_r23317321
--- Diff:
core/src/main/scala/org/apache/spark/deploy/StandaloneSparkHadoopUtil.scala ---
@@ -0,0 +1,76 @@
+/*
+ * Licensed to the Apache Software
Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/4106#discussion_r23320905
--- Diff:
core/src/main/scala/org/apache/spark/deploy/StandaloneSparkHadoopUtil.scala ---
@@ -0,0 +1,76 @@
+/*
+ * Licensed to the Apache Software
Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/4066#discussion_r23270381
--- Diff: core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
---
@@ -113,7 +115,7 @@ class DAGScheduler(
private val failedEpoch = new
Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/4066#discussion_r23255988
--- Diff: core/src/main/scala/org/apache/spark/SparkHadoopWriter.scala ---
@@ -105,10 +107,24 @@ class SparkHadoopWriter(@transient jobConf: JobConf
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/4066#issuecomment-70959680
The linked pull request takes your ideas, makes them compatible with
master, and adds unit tests. Feel free to take a look.
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GitHub user mccheah opened a pull request:
https://github.com/apache/spark/pull/4155
[SPARK-4879] Use the Spark driver to authorize Hadoop commits.
This is a version of https://github.com/apache/spark/pull/4066/ which is up
to date with master and has unit tests
GitHub user mccheah opened a pull request:
https://github.com/apache/spark/pull/4106
[SPARK-5158] [core] [security] Spark standalone mode can authenticate
against a Kerberos-secured Hadoop cluster
Previously, Kerberos secured Hadoop clusters could only be accessed by
Spark running
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/4106#issuecomment-70553364
Suggestions to unit test are welcome. This should not be merged until it is
unit-tested.
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Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/4106#issuecomment-70553855
One other caveat I forgot to mention, and the commit message should be
updated and this reflected in the docs: User proxying needs to be enabled.
Basically, the user
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/4155#issuecomment-71116954
Looks like the tests timed out. This change is probably a large performance
bottleneck, as communication back to the driver on every commit task is
expensive
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/4155#issuecomment-71130249
Actually it just looks like one test is hanging, so likely something not
being shut down properly.
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Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/4066#discussion_r23265225
--- Diff: core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala
---
@@ -113,7 +115,7 @@ class DAGScheduler(
private val failedEpoch = new
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/4420#issuecomment-74827293
If every single object is large though, then in that case after we've
spilled the 32nd object, there would still be an OOM before we check for
spilling again, right? I
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/4420#issuecomment-74558171
@andrewor14 what do you think about the comments from @mingyukim ?
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Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/4634#issuecomment-74732535
There is a case where map-side-combine is actually not the right thing to
do in some of my workflows. map-side-combine makes sense if the overall amount
of data
GitHub user mccheah opened a pull request:
https://github.com/apache/spark/pull/4634
[SPARK-5843] Allowing map-side combine to be specified in Java.
Specifically, when calling JavaPairRDD.combineByKey(), there is a new
five-parameter method that exposes the map-side-combine
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/4634#issuecomment-74752839
We want to take advantage of the distributed reduce functionality of
combineByKey when computing the other aggregation metrics as well. Is this not
lost if we do a map
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/4634#issuecomment-74756966
You lose the parallelism that's inherent in computing the reduce as a
parallel operation, as opposed to computing it on a list in a single task.
For more context
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/4106#issuecomment-74762686
Able to come back to this now!
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Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/4634#issuecomment-74580824
groupBy and reduceByKey in the Scala API are actually just convenience
methods that call through to combineByKey with parameters that make sense.
Given that, perhaps
Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/4634#discussion_r24786524
--- Diff: core/src/test/java/org/apache/spark/JavaAPISuite.java ---
@@ -25,17 +25,17 @@
import java.util.concurrent.*;
import
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/4634#issuecomment-74579047
Can we also allow map-side-combine to be specified without specifying the
partitioner?
In general since Java doesn't offer the luxury of default-values
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/4420#issuecomment-75170336
Jenkins, test this please.
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Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/4106#discussion_r24860380
--- Diff: core/src/main/scala/org/apache/spark/rdd/HadoopRDD.scala ---
@@ -193,17 +193,21 @@ class HadoopRDD[K, V](
override def getPartitions: Array
Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/4155#discussion_r23581966
--- Diff: core/src/main/scala/org/apache/spark/SparkHadoopWriter.scala ---
@@ -106,18 +107,25 @@ class SparkHadoopWriter(@transient jobConf: JobConf
Github user mccheah commented on a diff in the pull request:
https://github.com/apache/spark/pull/4155#discussion_r23634059
--- Diff:
core/src/test/scala/org/apache/spark/scheduler/OutputCommitCoordinatorSuite.scala
---
@@ -0,0 +1,177 @@
+/*
+ * Licensed to the Apache
Github user mccheah commented on the pull request:
https://github.com/apache/spark/pull/4155#issuecomment-71743261
Jenkins, retest this please
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