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Github user vanzin commented on the issue:
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> that won't work in the PySpark shell either though, even if you restart
the SparkContext
That's a separate issue which should also be fixed (stopping a python
SparkContext does not stop
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Github user BryanCutler commented on the issue:
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Hmmm, that won't work in the PySpark shell either though, even if you
restart the SparkContext. If that's what you want though, @zjffdu 's PR
addresses that.
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Github user zsxwing commented on the issue:
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LGTM. Merging to master! Thanks!
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Github user zhaoyunjiong closed the pull request at:
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@jerryshao, In the original patch I made a mistake, it should return
_recoveryPath in the last instead of return null. After that fix, I don't think
it will introduce a situation where
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Github user vanzin commented on the issue:
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@BryanCutler sorry, this is not what I meant. Guess I was confused about
your comment on the bug.
See my original code on the bug:
```
>>> from pyspark import SparkContext
Github user BryanCutler commented on the issue:
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@vanzin and @zjffdu , this is my take on a simplified solution that will
allow configuring the JVM from the command line. You still won't be able to
use these confs in the shell when creating
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Can one of the admins verify this patch?
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[SPARK-17321][YARN] YARN shuffle service should use good disk from
yarn.nodemanager.local-dirs
## What changes were proposed in this pull request?
Use good disk from
GitHub user BryanCutler opened a pull request:
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[SPARK-17387][PYSPARK] Allow passing of args to gateway to configure JVM
## What changes were proposed in this pull request?
When not using spark-submit, user configuration for the JVM is
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Merging to master. Thanks!
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--- Diff: python/pyspark/java_gateway.py ---
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Github user keypointt commented on the issue:
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how about adding type check? `expect_equal(typeof(summary$weights), "list")`
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Github user felixcheung commented on the issue:
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since the format of the output is changing it would be great to check more
than just the length in test
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Github user keypointt commented on the issue:
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There is already a test `expect_equal(length(summary$weights), 64)`
https://github.com/apache/spark/blob/master/R/pkg/inst/tests/testthat/test_mllib.R#L371
is it enough or we should
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Github user holdenk commented on the issue:
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ping @dbtsai if you have some cycles :)
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Back from vacation if anyone has review bandwidth would be really cool to
try and get this in :)
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Github user holdenk commented on the issue:
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Ping @yanboliang & @davies for thoughts
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GitHub user neggert opened a pull request:
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[SPARK-17455][MLlib] Improve PAVA implementation in IsotonicRegression
## What changes were proposed in this pull request?
New implementation of the Pool Adjacent Violators Algorithm
Github user holdenk commented on the issue:
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Back from vacation if anyone has review bandwidth I'd love to get this
cleanup in :)
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Github user holdenk commented on the issue:
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Would it make sense to replace some of the hacks with this util at the same
time?
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retest this please
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Github user holdenk commented on the issue:
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@zsxwing I'm not sure I understand - the current API allows users to
specify the class name and uses reflection to create it - this allows users to
specify a specific instance of the class but the
Github user zsxwing commented on the issue:
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In general, we don't want to use any source or sink classes to an API of
DataStreamWriter because they are not as stable as DataStreamWriter. This is
similar to DataFrameWriter.
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Github user felixcheung commented on a diff in the pull request:
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--- Diff: R/pkg/R/mllib.R ---
@@ -732,7 +733,6 @@ setMethod("summary", signature(object =
"MultilayerPerceptronClassificationModel
Github user felixcheung commented on the issue:
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cool thanks, just one comment
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Github user dbtsai commented on a diff in the pull request:
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--- Diff:
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@@ -50,6 +50,8 @@ private[classification] trait
Github user zsxwing commented on a diff in the pull request:
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--- Diff: core/src/main/scala/org/apache/spark/storage/BlockManager.scala
---
@@ -199,6 +199,9 @@ private[spark] class BlockManager(
Github user zsxwing commented on a diff in the pull request:
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--- Diff:
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---
@@ -148,12 +149,32 @@ private[spark] class
Github user dhruve commented on a diff in the pull request:
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--- Diff:
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@@ -392,10 +397,36 @@ private[spark] class ExecutorAllocationManager(
Github user dbtsai commented on the issue:
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@sethah For sparse MLOR problems with L1, the models will be sparse in row.
As a result, in the sparse, we need to store the models in CSR format, and CSR
models can be used for model prediction
Github user dbtsai commented on the issue:
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Some minor issues, and LGTM. Thanks.
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Github user ooq commented on the issue:
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LGTM. This is good. Thanks.
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Github user dbtsai commented on a diff in the pull request:
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--- Diff: graphx/src/main/scala/org/apache/spark/graphx/lib/PageRank.scala
---
@@ -163,6 +166,85 @@ object PageRank extends Logging {
}
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https://github.com/apache/spark/pull/15017
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Github user jkbradley commented on the issue:
https://github.com/apache/spark/pull/15017
CC: @yanboliang @MLnick Does one of you have time to review this? It
should be very quick. Thanks!
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GitHub user jkbradley opened a pull request:
https://github.com/apache/spark/pull/15017
[SPARK-17456][CORE] Utility for parsing Spark versions
## What changes were proposed in this pull request?
This patch adds methods for extracting major and minor versions as Int
types
Github user JoshRosen commented on the issue:
https://github.com/apache/spark/pull/15016
LGTM pending tests. I think this is definitely the right fix.
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Github user dbtsai commented on a diff in the pull request:
https://github.com/apache/spark/pull/14998#discussion_r78090050
--- Diff: graphx/src/main/scala/org/apache/spark/graphx/lib/PageRank.scala
---
@@ -163,6 +166,85 @@ object PageRank extends Logging {
}
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