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Good point, done, I can get profiling the below code then? Builds fine and
no scalastyle problems
```
def getComparator[K](keyComparator: Option[Comparator[K]]):
Comparator[(Int, K)
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GitHub user wangyum opened a pull request:
https://github.com/apache/spark/pull/16079
[SPARK-18645][Deploy] Fix spark-daemon.sh arguments error lead to throws
Unrecognized option
## What changes were proposed in this pull request?
spark-daemon.sh will lost single quotes aro
Github user a-roberts commented on the issue:
https://github.com/apache/spark/pull/15713
In response to @rxin's question, for HiBench CompactBuffers are **used only
on PageRank** (none of the other 11) and these buffers mainly have between 3
and 40 elements, no more than 60, never wit
Github user srowen commented on the issue:
https://github.com/apache/spark/pull/15736
Looks right except you just want to write
```
if (...) {
...
} else {
new Comparator...
}
```
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Github user a-roberts commented on the issue:
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@srowen how about this for profiling?
```
private[spark] object WritablePartitionedPairCollection {
/**
* Takes an optional parameter (keyComparator), use if provided
Github user MLnick commented on the issue:
https://github.com/apache/spark/pull/16037
What worries me more actually is that the initial vector when sent in the
closure should be compressed. So why is this issue occurring? Is it a problem
with serialization / compression? OR even after
Github user MLnick commented on the issue:
https://github.com/apache/spark/pull/16037
Right ok. So I think the approach of making the zero vector sparse then
calling `toDense` in `seqOp` as @srowen suggested makes most sense.
Currently the gradient vector *must* be dense in ML
Github user MLnick commented on the issue:
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@AnthonyTruchet I think in this case it was just confusing to have many PRs
opened against the issue. One option is to either adjust the existing PR with
changes (so that only one PR is open).
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retest this please
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Github user AnthonyTruchet closed the pull request at:
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Github user AnthonyTruchet commented on the issue:
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In order to reduce the mess around multiple PRs I'll close this one and
rebase the change in #16037 as you requested.
What is the right way,convenient for you, to share a proposal wit
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Github user srowen commented on the issue:
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This should be the main PR @MLnick
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Github user srowen commented on the issue:
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Regarding plugin updates: I wouldn't mind updating the Maven plugins too
while you're at it. `mvn versions:display-plugin-updates` will show you all the
candidates. Some changes we can't or won't tak
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This is all a bit confusing - can we highlight which PR is actually to be
reviewed?
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Merged to master/2.1
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Github user ueshin commented on a diff in the pull request:
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--- Diff:
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---
@@ -590,7 +591,11 @@ object ScalaReflection extends ScalaReflec
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Github user AnthonyTruchet commented on the issue:
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Agreed this is too ML specific to be deserve a fix in core.
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Github user AnthonyTruchet commented on the issue:
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It is necessary to address it in L-BFGS at least. We propose a solution in
core which can be legitimately rejected as not relevant for core. And two
solutions in MLlib, one provide for a reus
Github user asfgit closed the pull request at:
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Github user MLnick commented on the issue:
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Sorry for delay - this LGTM. Given it's been around for a while and given
RC2 is likely to be cut, I've gone ahead and merged to master / branch-2.1.
Thanks!
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Github user ueshin commented on a diff in the pull request:
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Github user lshmouse commented on the issue:
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@lianhuiwang
Just a feedback. With this patch, creating a MACRO throws the following
exception.
Any suggestion? I am trying to debug it.
```
16/11/30 16:59:18 INFO execut
Github user srowen commented on the issue:
https://github.com/apache/spark/pull/16037
Following https://github.com/apache/spark/pull/16038 I suggest this proceed
by making the zero value a sparse vector, and then making it dense in the seqOp
immediately.
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Github user srowen commented on the issue:
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As in https://github.com/apache/spark/pull/16078 I do not think we should
merge a change like this. Let's fix the problem directly in
https://github.com/apache/spark/pull/16037
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Github user srowen commented on the issue:
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This is getting a bit out of hand, with 6 pull requests now. To be clear, I
do not think we should merge this change. It's not necessary to address the
problem.
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Github user AmplabJenkins commented on the issue:
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Can one of the admins verify this patch?
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Github user vijoshi commented on the issue:
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@tgravescs would like to have this in 2.0 along with the other improvement
that got accepted for backport (spark-18010). so would you consider allowing
this into 2.0 as well?
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Github user AnthonyTruchet commented on the issue:
https://github.com/apache/spark/pull/16038
@mridulm we don't know how to monitor the size of the serialize task. Sure
it would not 10MB due to all those zeros. But we nonetheless measure a
significant increase in performance and (more
Github user cloud-fan commented on a diff in the pull request:
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Github user viirya commented on a diff in the pull request:
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GitHub user AnthonyTruchet opened a pull request:
https://github.com/apache/spark/pull/16078
[SPARK-18471][MLLIB] Fix huge vectors of zero send in closure in L-BFGS
## What changes were proposed in this pull request?
Introduced util TreeAggregatorWithZeroGenerator and used i
Github user uncleGen commented on the issue:
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Is there any update? @JoshRosen
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val counter
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val counter
Github user liancheng commented on the issue:
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Good to merge pending Jenkins. Thanks!
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Github user kapilsingh5050 commented on a diff in the pull request:
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Github user uncleGen commented on the issue:
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@rxin OK, I will backport it to branch-2.0
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retest this please
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retest this please
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retest this please.
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