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--- Diff:
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@@ -930,10 +942,8 @@ class BinaryLogisticRegressionSummary
pr
Github user vanzin commented on the issue:
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Ping, I'll push this tomorrow unless someone complains.
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--- Diff:
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Github user nsyca commented on the issue:
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This problem can be viewed in SQL language like this:
```
val a = Seq((1),(2)).toDF("a").createOrReplaceTempView("A")
val b = Seq((2),(3)).toDF("a").createOrReplaceTempView("B")
sca
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Github user shivaram commented on the issue:
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This looks fine to me - @felixcheung feel free to merge this when you think
its good to go
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Github user markhamstra commented on the issue:
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There are multiple issues with this PR. Some are at a more stylistic
level, but some include deeper issues -- e.g. see SPARK-17064. Most
fundamentally, this PR is the wrong solution at least i
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See https://issues.apache.org/jira/browse/SPARK-17064
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Github user hvanhovell commented on the issue:
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@gatorsmile I am trying to understand you comment. Why shouldn't we use
`full outer` in combination with `using`? I am under the impression that using
is just a bit of syntactic sugar. For instan
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Github user JoshRosen commented on the issue:
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Jenkins, retest this please.
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LGTM, so I'll merge this to master. Thanks @davies!
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--- Diff: python/pyspark/rdd.py ---
@@ -188,6 +188,12 @@ def __init__(self, jrdd, ctx,
jrdd_deserializer=AutoBatchedSerializer(PickleSeri
self
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woot
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Github user gatorsmile commented on the issue:
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Based on my understanding, after this PR, we will respect the conf values
of `hive.exec.dynamic.partition`, `hive.exec.dynamic.partition.mode` and
`hive.exec.compress.output` that are specified i
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@srowen Mesos also supports node labels as well (which is how constraints
is implemented in Spark framework). However GPUs are implemented as a resource
(as we want to account for # of GPUs instead
Github user MLnick commented on a diff in the pull request:
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--- Diff: python/pyspark/rdd.py ---
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jrdd_deserializer=AutoBatchedSerializer(PickleSeri
self._i
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jrdd_deserializer=AutoBatchedSerializer(PickleSeri
self
Github user dongjoon-hyun commented on a diff in the pull request:
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@@ -1334,12 +1334,19 @@ object EliminateOuterJoin ex
Github user kiszk commented on the issue:
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@davies, thank you for your comment. I hope that you will have bandwidth
soon since Spark 2.0 was released.
[this PR](https://github.com/apache/spark/pull/13899/files) does the same
thing. In par
Github user hvanhovell commented on a diff in the pull request:
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@tedyu the scala code is shaping up nicely.
I do have a question regarding usage. How will this be used? The thing is
that the `monotonically_increasing_id` returns an id based on the num
Github user frreiss commented on a diff in the pull request:
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--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/text/TextSuite.scala
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@@ -39,6 +39,11 @@ class TextSuite extends QueryTest w
Github user vanzin commented on the issue:
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Given the overwhelming amount of feedback, merging to master.
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Github user sethah commented on a diff in the pull request:
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--- Diff:
mllib/src/main/scala/org/apache/spark/ml/classification/LogisticRegression.scala
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@@ -945,13 +955,139 @@ class BinaryLogisticRegressionSummary
Github user asfgit closed the pull request at:
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@@ -533,6 +533,12 @@ object SQLConf {
.timeConf(TimeUnit.MILLISE
Github user shivaram commented on the issue:
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Yeah LGTM. Merging this to master, branch-2.0 -- Thanks @junyangq
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Github user shivaram commented on the issue:
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I had one minor question about partitionBy -- otherwise change LGTM. Thanks
@felixcheung
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--- Diff: R/pkg/R/generics.R ---
@@ -152,9 +146,9 @@ setGeneric("getNumPartitions", function(x) {
standardGeneric("getNumPartitions")
# @export
se
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@@ -81,3 +91,12 @@ case class Monoton
Github user kiszk commented on the issue:
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Thank you for your comment. We are on the same page to address the problem.
In this case, you are right. This is because we finally would like to write
an primitive int array `mapelements_valu
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Github user davies commented on the issue:
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@kiszk I'm sorry that I do not have the bandwidth to review this,
https://github.com/apache/spark/pull/13899/files sounds like an easier approach
(have not looked into the details), how do you think
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--- Diff: R/pkg/R/generics.R ---
@@ -1279,6 +1279,11 @@ setGeneric("spark.naiveBayes", function(data,
formula, ...) { standardGeneric("s
#' @export
Github user yhuai commented on the issue:
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Sorry. What's the necessity to make this change?
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Github user skonto commented on the issue:
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@mgummelt pls review.
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--- Diff:
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@@ -25,55 +25,57 @@
import org.apache.spark.sql.
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Github user shivaram commented on the issue:
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Yep, this looks good @felixcheung -- Feel free to merge once you think its
good to go.
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GitHub user skonto opened a pull request:
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[SPARK-17062][MESOS] add conf option to mesos dispatcher
## What changes were proposed in this pull request?
Adds --conf option to set spark configuration properties in mesos
dispacther.
Pro
Github user shivaram commented on the issue:
https://github.com/apache/spark/pull/14639
@zjffdu Lets discuss why this was introduced more in the JIRA. Regd. the
code change, on my Mac `$HOME` is set without any custom changes on my side.
Any ideas when this will not be the case ?
-
Github user shivaram commented on the issue:
https://github.com/apache/spark/pull/14392
`spark.gaussianMixture` sounds good to me.
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Github user holdenk commented on the issue:
https://github.com/apache/spark/pull/14628
Awesome thanks for taking the time to do this. A few follow up questions:
1) So this is happening with the default tree depth (2) did you try it with
other depths?
2) Have you had a chance to
Github user shivaram commented on the issue:
https://github.com/apache/spark/pull/14641
Thanks @yanboliang - Do you know how the existing tests were passing ?
Should we add a new test case for this ?
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Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/14580
Test PASSed.
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Test PASSed.
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Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/14580
Merged build finished. Test PASSed.
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Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/14580
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Github user holdenk commented on the issue:
https://github.com/apache/spark/pull/14640
Thanks for making this issue and PR :) The first thing before people are
likely to have the bandwith to review this is we are switching all new ML
development to Spark ML from MLlib so it might be g
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/14624
@mvervuurt Could you please double check this one? I am pretty sure I
checked out this PR and then tested this correctly.
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Github user tedyu commented on the issue:
https://github.com/apache/spark/pull/14568
@rxin
Can you take a look at the python API one more time ?
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Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/12004
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Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/13758
The new `UnsafeArrayData` should be as fast as primitive array right? The
problem you pointed out is valid, but can we improve the encoder framework to
create unsafe array directly for primitive a
Github user steveloughran commented on the issue:
https://github.com/apache/spark/pull/14646
I'd be against making it default for a few reasons
1. You don't want to accidentally pick up some staging artifact or upstream
snapshot.
2. I don't know how SBT/Ivy handles remote
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