Github user Ishiihara commented on the pull request:
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@marmbrus All test failures have the same pattern
select * from a right outer join b on condition1 join c on condition2
With the extra join oper
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Jenkins, retest this please.
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LGTM
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Github user saucam commented on the pull request:
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Hi @mateiz , thanks for the suggestions, just a few points
1. Need to know which strategy to be kept as default (currently we use a
different one than the default one
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GitHub user harishreedharan opened a pull request:
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[SPARK-4122][STREAMING] Add a library that can write data back to Kafka ...
...from Spark Streaming.
This adds a library that can writes dstreams to Kafka. An implicit also has
been
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@@ -128,7 +128,7 @@ private[spark] class ShuffleMapTask(
}
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}
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--- Diff: core/src/main/scala/org/apache/spark/ui/exec/ThreadDumpPage.scala
---
@@ -0,0 +1,71 @@
+/*
+ * Licensed to the Apache Software Foundation
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Github user JoshRosen commented on the pull request:
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I've rewritten this patch so that thread dumps are triggered on-demand
using a new driver -> executor RPC channel. There are a few hacks involved in
setting this up, m
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GitHub user liancheng opened a pull request:
https://github.com/apache/spark/pull/2993
[Build] Uploads HiveCompatibilitySuite logs
In addition to unit-tests.log files, also upload failure output files
generated by `HiveCompatibilitySuite` to Jenkins master. These files can be
very
Github user shivaram commented on the pull request:
https://github.com/apache/spark/pull/2907#issuecomment-60877866
Yes - treeAggregate is very useful -- In fact I was going to suggest moving
it to the core RDD API. Any reasons to not do that ?
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Github user anantasty commented on the pull request:
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@marmbrus just did that. Thanks for that.
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Github user tdas commented on the pull request:
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I mentioned this in the earlier in the original thread. This is a tradeoff
between generality and type checking. I want the code in
ReceiverSupervisorImpl, and ReceivedBlock
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[SPARK-4129][MLlib] Performance tuning in MultivariateOnlineSummarizer
In MultivariateOnlineSummarizer, breeze's activeIterator is used to loop
through the nonZero elements in the vector. However, ac
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Github user javadba commented on the pull request:
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RE: use case. We are considering to use the treeAggregate function within
the implementation of SpectralClustering. In addition it was noted that the
EigenvalueDecompos
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Github user davies commented on the pull request:
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thanks, update the link
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Github user jerryshao commented on the pull request:
https://github.com/apache/spark/pull/2991#issuecomment-60875453
Hi @tdas , would you mind taking a look at this? Thanks a lot.
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GitHub user jerryshao opened a pull request:
https://github.com/apache/spark/pull/2991
[SPARK-4062][Streaming]Add ReliableKafkaReceiver in Spark Streaming Kafka
connector
Add ReliableKafkaReceiver in Kafka connector to prevent data loss if WAL in
Spark Streaming is enabled. Details
Github user aarondav commented on the pull request:
https://github.com/apache/spark/pull/2753#issuecomment-60875179
That is a pass with netty turned on. Now I am turning it off for
preparation to merge.
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Github user nchammas commented on the pull request:
https://github.com/apache/spark/pull/2988#issuecomment-60874638
Phantom new classes _again_? :angry: I'll look into this tomorrow. Thought
it was a resolved issue...
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Github user mengxr commented on the pull request:
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The failed test from streaming is a known flaky test. @tdas
I've merged this one into master (because it will speed up Jenkins builds).
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Github user asfgit closed the pull request at:
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Github user mengxr commented on the pull request:
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Had an offline discussion with @freeman-lab . We decided to introduce the
concept of `timeUnit` to describe decay. A `timeUnit` (like a second) could be
either a `batch` o
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Github user liancheng commented on the pull request:
https://github.com/apache/spark/pull/2685#issuecomment-60872647
@scwf How about Spark dev related environment variable settings on your
host? I unset `SPARK_PREPEND_CLASSES` and set `SPARK_TESTING` to 1 before
running `core/test` (w
Github user liancheng commented on the pull request:
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Local testing each test suite individually doesn't fail, guess another case
related to test suite execution order.
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Github user aarondav commented on the pull request:
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LGTM. This patch decreases build time by roughly 10 minutes. Good job!
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GitHub user mengxr opened a pull request:
https://github.com/apache/spark/pull/2990
[FIX] disable benchmark code
I forgot to disable the benchmark code in #2937, which increased the
Jenkins build time by couple minutes.
@aarondav
You can merge this pull request into a Git
Github user AmplabJenkins commented on the pull request:
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Can one of the admins verify this patch?
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Github user andrewor14 commented on the pull request:
https://github.com/apache/spark/pull/2840#issuecomment-60870350
I believe `missing` can't be negative, because that would imply
`maxExecutors < numPendingAllocate + numExecutorsRunning`. We only decrease
`maxExecutors` from kill ex
GitHub user KaiXinXiaoLei opened a pull request:
https://github.com/apache/spark/pull/2989
delete jetty 6.1.26 form spark package
In spark code, jetty version is 8.1.14.v20131031 (see ./pom.xml). But when
building, the jetty-6.1.26 and jetty-util-6.1.26 is packaged in
spark-assembl
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https://github.com/apache/spark/pull/2840#discussion_r19519070
--- Diff:
core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedClusterMessage.scala
---
@@ -66,7 +66,16 @@ private[spark] object CoarseGrai
Github user scwf commented on the pull request:
https://github.com/apache/spark/pull/2685#issuecomment-60869228
@liancheng, master branch passed in your local machine?
i tested with
```
sbt/sbt -Phive,hadoop-2.3 assembly
sbt/sbt -Phive,hadoop-2.3 core/test
```
a
Github user pwendell commented on the pull request:
https://github.com/apache/spark/pull/2940#issuecomment-60869205
The way this now we have to do runtime type checking in a bunch of
places... I think it could be avoided with a fairly simple change.
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Github user pwendell commented on the pull request:
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I took another pass - the main thing blocking this for me is cleaning up
the type signature to not have `Option[Any]`. I made a proposal earlier and I
stick by that one.
Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/2868#discussion_r19518754
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/tree/impl/NodeIdCache.scala ---
@@ -0,0 +1,189 @@
+/*
+ * Licensed to the Apache Software Foundat
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--- Diff:
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@@ -0,0 +1,189 @@
+/*
+ * Licensed to the Apache Software Foundat
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--- Diff:
streaming/src/main/scala/org/apache/spark/streaming/receiver/ReceivedBlockHandler.scala
---
@@ -0,0 +1,144 @@
+package org.apache.spark.stream
Github user liancheng commented on the pull request:
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I'm looking into this.
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Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/2753#issuecomment-60868156
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Github user aarondav commented on the pull request:
https://github.com/apache/spark/pull/2753#issuecomment-60867974
Jenkins, retest this please.
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GitHub user nchammas opened a pull request:
https://github.com/apache/spark/pull/2988
[EC2] Don't change working dir on user
The issue was uncovered after [this
discussion](https://issues.apache.org/jira/browse/SPARK-3398?focusedCommentId=14187471&page=com.atlassian.jira.plugin.syst
Github user liyezhang556520 commented on the pull request:
https://github.com/apache/spark/pull/2956#issuecomment-60867864
RDD checkpoint should also support like this:
`rdd0 = sc.makeRDD(...)`
`rdd1 = rdd0.flatmap(...)`
`rdd1.collect()`
`rdd0.checkpoint()`
`rdd1.cou
Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/2753#issuecomment-60867860
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Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/2753#issuecomment-60867867
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Github user scwf commented on the pull request:
https://github.com/apache/spark/pull/2685#issuecomment-60867822
I tested the master branch locally, it also failed.
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Github user SparkQA commented on the pull request:
https://github.com/apache/spark/pull/2753#issuecomment-60867311
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Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/2987#issuecomment-60867101
Can one of the admins verify this patch?
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GitHub user ravipesala opened a pull request:
https://github.com/apache/spark/pull/2987
[SPARK-4120][SQL] Join of multiple tables with syntax like SELECT .. FROM
T1,T2,T3.. does not work in SparkSQL
Right now it works for only 2 tables like below query.
sql("SELECT * FROM record
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