Github user srowen commented on the pull request:
https://github.com/apache/spark/pull/1025#issuecomment-46402006
@dorx you said above you are trying to use the RNG from Jet? why, if
Commons math3 is usable now? I prefer the latter FWIW. I probably misunderstand
your comment.
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Github user pwendell commented on a diff in the pull request:
https://github.com/apache/spark/pull/813#discussion_r13901535
--- Diff: python/pyspark/join.py ---
@@ -79,15 +79,15 @@ def dispatch(seq):
return _do_python_join(rdd, other, numPartitions, dispatch)
Github user mateiz commented on the pull request:
https://github.com/apache/spark/pull/813#issuecomment-46401560
Hey @douglaz, thanks for updating this. One thing missing here is tests in
each of the languages -- please add them so that this code will be tested later.
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Github user WangTaoTheTonic commented on the pull request:
https://github.com/apache/spark/pull/1106#issuecomment-46401368
Another situation is that the works lists changes frequently, which will
make drivers relaunching a lot.
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--- Diff: python/pyspark/join.py ---
@@ -79,15 +79,15 @@ def dispatch(seq):
return _do_python_join(rdd, other, numPartitions, dispatch)
Github user pwendell commented on a diff in the pull request:
https://github.com/apache/spark/pull/813#discussion_r13901329
--- Diff: python/pyspark/rdd.py ---
@@ -1324,11 +1324,11 @@ def mapValues(self, f):
return self.map(map_values_fn, preservesPartitioning=True)
Github user pwendell commented on a diff in the pull request:
https://github.com/apache/spark/pull/813#discussion_r13901312
--- Diff: python/pyspark/join.py ---
@@ -79,15 +79,15 @@ def dispatch(seq):
return _do_python_join(rdd, other, numPartitions, dispatch)
Github user AmplabJenkins commented on the pull request:
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Github user pwendell commented on the pull request:
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Jenkins, test this please.
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Github user harishreedharan commented on a diff in the pull request:
https://github.com/apache/spark/pull/807#discussion_r13900807
--- Diff:
external/flume-sink/src/main/scala/org/apache/spark/flume/sink/SparkSink.scala
---
@@ -0,0 +1,432 @@
+/*
+ * Licensed to the Apache
Github user rezazadeh commented on a diff in the pull request:
https://github.com/apache/spark/pull/964#discussion_r13900614
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala
---
@@ -220,16 +247,43 @@ class RowMatrix(
}
/*
Github user rxin commented on the pull request:
https://github.com/apache/spark/pull/1109#issuecomment-46399205
Yup looks like a racing condition (in a good way). Thanks a lot for
catching this!
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Github user gregakespret commented on the pull request:
https://github.com/apache/spark/pull/1109#issuecomment-46399053
@rxin Sure, PR closed. At the time I created this PR, the other one wasn't
yet merged in I suppose.
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Github user gregakespret closed the pull request at:
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Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/964#issuecomment-46398850
Btw, we shouldn't use default parameters in method definition. It is
convenient in Scala but it is not Java friendly. Also, this is hard for us to
maintain binary compatibi
Github user harishreedharan commented on the pull request:
https://github.com/apache/spark/pull/807#issuecomment-46398801
@tdas Use the following configuration file to start flume:
agent.sources = seqGenSrc
agent.channels = memoryChannel
agent.sinks = spark
# F
Github user rxin commented on the pull request:
https://github.com/apache/spark/pull/1109#issuecomment-46398768
@gregakespret since this has been fixed already in master, do you mind
closing this pr?
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Github user mengxr commented on a diff in the pull request:
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--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/linalg/EigenValueDecomposition.scala
---
@@ -0,0 +1,155 @@
+/*
+ * Licensed to the Apache Softwar
Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/964#issuecomment-46398707
@vrilleup Thanks for updating the PR! I made a comment on the explicit type
checks. I'm a little confused about the new API. If `isDenseSVD` is true, `tol`
doesn't mean any
Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/964#discussion_r1396
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala
---
@@ -201,6 +202,31 @@ class RowMatrix(
}
/**
Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/964#discussion_r13899798
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/linalg/EigenValueDecomposition.scala
---
@@ -0,0 +1,155 @@
+/*
+ * Licensed to the Apache Softwar
Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/964#discussion_r13899792
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/linalg/EigenValueDecomposition.scala
---
@@ -0,0 +1,155 @@
+/*
+ * Licensed to the Apache Softwar
Github user mengxr commented on a diff in the pull request:
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--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/linalg/EigenValueDecomposition.scala
---
@@ -0,0 +1,155 @@
+/*
+ * Licensed to the Apache Softwar
Github user mengxr commented on a diff in the pull request:
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--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/linalg/EigenValueDecomposition.scala
---
@@ -0,0 +1,155 @@
+/*
+ * Licensed to the Apache Softwar
Github user ash211 commented on the pull request:
https://github.com/apache/spark/pull/369#issuecomment-46396473
Took a look through and didn't see any issues with the merge. Thanks to
everyone who helped me get this in!
On Tue, Jun 17, 2014 at 2:48 PM, Reynold Xin
Github user asfgit closed the pull request at:
https://github.com/apache/spark/pull/961
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Github user dbtsai commented on the pull request:
https://github.com/apache/spark/pull/1104#issuecomment-46393840
I think it's legacy reason to have two different way to access the API. As
far as I know, @mengxr is working on consolidating the interface. He probably
can talk about mor
Github user BaiGang commented on the pull request:
https://github.com/apache/spark/pull/1104#issuecomment-46393686
@dbtsai Thanks for looking into this PR. I've updated the code, removing
the unnecessary type specifications for the vars in class LBFGS.
Also I have a question.
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Github user pwendell commented on the pull request:
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Jenkins, retest this please. Okay I think we can merge this purely on the
grounds of more defensive coding (it avoids a potential `null` value).
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Github user CodingCat commented on the pull request:
https://github.com/apache/spark/pull/1106#issuecomment-46391510
yes, potentially...
and considering the long-term running of the cluster, eventually, the load
is well balanced with the current strategy.i.e. this commit o
Github user tmalaska commented on the pull request:
https://github.com/apache/spark/pull/#issuecomment-46391465
Never mind. I had to close the pull request. I thought about it. The
ccAccumulator is not accessible from the vprog which was my goal. I'm going to
have to use a broadca
Github user tmalaska closed the pull request at:
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Github user dbtsai commented on a diff in the pull request:
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--- Diff:
mllib/src/test/scala/org/apache/spark/mllib/optimization/LBFGSSuite.scala ---
@@ -195,4 +195,39 @@ class LBFGSSuite extends FunSuite with
LocalSpark
Github user tmalaska commented on the pull request:
https://github.com/apache/spark/pull/#issuecomment-46391395
Wait, this isn't going to get me what I want, because I can't read the
ssAccumulator in the vprog. I think I will have to change to a boardcast. I
will
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Can one of the admins verify this patch?
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GitHub user tmalaska opened a pull request:
https://github.com/apache/spark/pull/
Spark-2173 : Add Master Computer and SuperStep ...
Add Master Computer and SuperStep Accumulator to Pregel GraphX
Implemention
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Github user dbtsai commented on a diff in the pull request:
https://github.com/apache/spark/pull/1104#discussion_r13897737
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/optimization/LBFGS.scala ---
@@ -38,10 +38,10 @@ import org.apache.spark.mllib.linalg.{Vectors, Vector}
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Github user WangTaoTheTonic commented on the pull request:
https://github.com/apache/spark/pull/1106#issuecomment-46390574
You mean the increased shuffles may lead to a bad performance?
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Github user dorx commented on the pull request:
https://github.com/apache/spark/pull/1025#issuecomment-46389694
@falaki @mengxr Barring the API related issues, everything else should be
in the "final" state. commons-math3 added as a Spark dependency (okay'ed by
Matei). mvn clean insta
Github user markhamstra commented on the pull request:
https://github.com/apache/spark/pull/999#issuecomment-46389597
Is that the basic strategy we are going to use with AlphaComponents --
merging new APIs at both the minor and maintenance levels? I don't know that I
have any objecti
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Github user asfgit closed the pull request at:
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Github user vrilleup commented on the pull request:
https://github.com/apache/spark/pull/964#issuecomment-46389121
I add a flag for choosing dense/sparse svd, and set n = 100 as threshold
for default behavior. User can make a choice by the specific application.
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Github user rxin commented on the pull request:
https://github.com/apache/spark/pull/999#issuecomment-46389105
Thanks. I'm merging this in master & branch-1.0.
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Github user vrilleup commented on a diff in the pull request:
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--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/linalg/EigenValueDecomposition.scala
---
@@ -0,0 +1,150 @@
+/*
+ * Licensed to the Apache Softw
Github user vrilleup commented on a diff in the pull request:
https://github.com/apache/spark/pull/964#discussion_r13896269
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala
---
@@ -201,6 +202,31 @@ class RowMatrix(
}
/**
Github user vrilleup commented on a diff in the pull request:
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--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala
---
@@ -201,6 +202,31 @@ class RowMatrix(
}
/**
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--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/linalg/EigenValueDecomposition.scala
---
@@ -0,0 +1,150 @@
+/*
+ * Licensed to the Apache Softw
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--- Diff:
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---
@@ -0,0 +1,150 @@
+/*
+ * Licensed to the Apache Softw
Github user vrilleup commented on a diff in the pull request:
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--- Diff:
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---
@@ -201,6 +202,31 @@ class RowMatrix(
}
/**
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--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala
---
@@ -201,6 +202,31 @@ class RowMatrix(
}
/**
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--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/linalg/EigenValueDecomposition.scala
---
@@ -0,0 +1,150 @@
+/*
+ * Licensed to the Apache Softw
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--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/linalg/EigenValueDecomposition.scala
---
@@ -0,0 +1,150 @@
+/*
+ * Licensed to the Apache Softw
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--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/linalg/EigenValueDecomposition.scala
---
@@ -0,0 +1,150 @@
+/*
+ * Licensed to the Apache Softw
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--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/linalg/EigenValueDecomposition.scala
---
@@ -0,0 +1,150 @@
+/*
+ * Licensed to the Apache Softw
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--- Diff:
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---
@@ -0,0 +1,150 @@
+/*
+ * Licensed to the Apache Softw
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--- Diff:
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---
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+/*
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---
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+/*
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Github user douglaz commented on the pull request:
https://github.com/apache/spark/pull/813#issuecomment-46386598
@pwendell, merged with latest master.
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Github user li-zhihui commented on a diff in the pull request:
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---
@@ -225,6 +232,17 @@ class CoarseGrainedSchedulerBa
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Github user pwendell commented on the pull request:
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This was already fixed earlier today so it's probably hitting a merge
conflict.
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Github user pwendell commented on the pull request:
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https://github.com/apache/spark/commit/b2ebf429e24566c29850c570f8d76943151ad78c
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Github user adrian-wang commented on a diff in the pull request:
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@@ -225,6 +232,17 @@ class CoarseGrainedScheduler
Github user colorant commented on the pull request:
https://github.com/apache/spark/pull/1103#issuecomment-46383834
@andrewor14 e.g. you clean old rdd base on timestamp etc. I know this could
be rare, but not entirely wrong. And, if something is really go wrong, I tend
to think the ex
Github user rxin commented on the pull request:
https://github.com/apache/spark/pull/1109#issuecomment-46383668
Actually the merge script failed for this pull request. @pwendell any idea?
```
> ./merge_spark_pr.py
Which pull request would you like to merge? (e.g. 34): 1109
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Github user rxin commented on the pull request:
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Thanks. Merging this in master & branch-1.0.
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Github user andrewor14 commented on the pull request:
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Jenkins, test this please
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Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/1025#issuecomment-46381897
All automated tests passed.
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Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/1025#issuecomment-46381896
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Github user mengxr closed the pull request at:
https://github.com/apache/spark/pull/506
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Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/506#issuecomment-46380865
Thanks all for reviewing this PR! I found the butterfly pattern introduces
complex dependency that slows down the computation. In my tests, a good
approach for Spark is tre
Github user rxin commented on the pull request:
https://github.com/apache/spark/pull/999#issuecomment-46380653
This looks to me overall. Only few nitpicks.
I think we should merge it after you addressed the couple comments I had.
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Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/1110#issuecomment-46380509
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Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/999#discussion_r13893273
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala
---
@@ -0,0 +1,399 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) u
Github user AmplabJenkins commented on the pull request:
https://github.com/apache/spark/pull/1110#issuecomment-46380502
Merged build triggered.
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Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/999#discussion_r13893257
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala
---
@@ -0,0 +1,399 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) u
GitHub user mengxr opened a pull request:
https://github.com/apache/spark/pull/1110
[WIP][SPARK-2174][MLLIB] treeReduce and treeAggregate
In `reduce` and `aggregate`, the driver node spends linear time on the
number of partitions. It becomes a bottleneck when there are many partitio
Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/999#discussion_r13893161
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/SchemaRDD.scala ---
@@ -342,13 +344,34 @@ class SchemaRDD(
def toJavaSchemaRDD: JavaSchemaRDD = new J
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