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Github user rdblue commented on the issue:
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Yeah, I added the `isinstance(f, DataType)` trick to my local tests. I'd
add it if it were up to me, but I'm fine requiring `returnType` to be a keyword
arg if you feel strongly about it.
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Github user asfgit closed the pull request at:
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Github user davies commented on the issue:
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Merging this into master, thanks!
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Github user nchammas commented on the issue:
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> Does a build of Spark + Hadoop 2.7 right now have no ability at all to
read from S3 out of the box, or just not full / ideal support?
No ability at all, as far as I can tell. People
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Github user zero323 commented on the issue:
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@rdblue Good question. I vaguely remember I had some motivation to avoid
this but now I cannot recall why. In general I really liked the initial
approach because it allowed us to write:
Github user gatorsmile commented on a diff in the pull request:
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--- Diff:
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@@ -62,15 +62,17 @@ private[hive] class
Github user gatorsmile commented on a diff in the pull request:
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Github user ajbozarth commented on the issue:
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I checked this out and tested it and it runs well, code LGTM as well, but I
agree that the unrelated changes should be removed.
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Github user yhuai commented on the issue:
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Cool I am merging this to master.
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--- Diff:
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@@ -0,0 +1,141 @@
+/*
+ * Licensed to the Apache Software
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--- Diff: R/pkg/R/mllib_clustering.R ---
@@ -38,6 +45,146 @@ setClass("KMeansModel", representation(jobj = "jobj"))
#' @note LDAModel since 2.1.0
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LGTM pending Jenkins.
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My main concern of this pr is that if people will think it is recommended
to add new batches to force those rules running in a certain ordering. For
these resolution rules, we can also use conditions
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GitHub user yhuai opened a pull request:
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[SPARK-19295] [SQL] IsolatedClientLoader's downloadVersion should log the
location of downloaded metastore client jars
## What changes were proposed in this pull request?
This will help the
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Github user squito commented on the issue:
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ah, sorry I didn't notice that before my comment. well looks good now,
I'll merge once tests pass.
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Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/16645#discussion_r96941832
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
---
@@ -106,6 +106,13 @@ class Analyzer(
*/
Github user paragpc commented on the issue:
https://github.com/apache/spark/pull/16473
Thanks @squito. Actually I have resolved the merge conflicts and started a
new test build about half an hour ago. Currently, I don't see any merge
conflicts.
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--- Diff:
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---
@@ -43,11 +45,24 @@ private[v1] class
Github user rdblue commented on the issue:
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@zero323, I think that the decorator and existing UDF factory method should
be the same, but that we can't break existing code. Can you explain why this
necessarily breaks code that relies on
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Github user squito commented on the issue:
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thanks @paragpc . lgtm, but now there are merge conflicts. Can you merge
with the latest master? You might need to regenerate those test expectation
files.
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Github user Krimit commented on the issue:
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@srowen @jkbradley updated with comments. I used the spark version to sniff
the version as suggested by @jkbradley, although I'm happy to continue the
conversation about the best way to handle
Github user jkbradley commented on the issue:
https://github.com/apache/spark/pull/14547
I'd recommend overriding setImpurity in the relevant concrete classes. In
those, you can add warnings in the Scala doc and also add logWarning messages
about deprecation. That's almost as good
Github user jkbradley commented on the issue:
https://github.com/apache/spark/pull/15730
The API looks good to me. I have not reviewed the internals carefully.
One comment: Let's add a check to verify that numMidDimSplits is > 0.
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Github user saj1th commented on the issue:
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Facing huge performance issues with range joins. Hoping to see this
implemented
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Github user sureshthalamati commented on the issue:
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@gatorsmile Verified on the master , problem still exist. Resolved the
conflicts, when u get a chance can you please review.
Error stack without the fix
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Github user actuaryzhang commented on the issue:
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Could anybody help me understand what's causing this test to fail? I see
several other ML PR failing as well, with the same error message like below:
> Error instrumenting
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Github user squito commented on the issue:
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thanks for the feedback @mridulm , all good points. I pushed an update to
address some of the points, also have some follow up discussion
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--- Diff:
mllib/src/main/scala/org/apache/spark/ml/r/GaussianMixtureWrapper.scala ---
@@ -91,7 +92,10 @@ private[r] object GaussianMixtureWrapper
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--- Diff: core/src/main/scala/org/apache/spark/executor/Executor.scala ---
@@ -405,6 +415,13 @@ private[spark] class Executor(
Github user squito commented on a diff in the pull request:
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--- Diff: core/src/main/scala/org/apache/spark/executor/Executor.scala ---
@@ -405,6 +415,13 @@ private[spark] class Executor(
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--- Diff:
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@@ -91,7 +92,10 @@ private[r] object GaussianMixtureWrapper
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--- Diff:
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@@ -45,6 +45,12 @@ private[spark] class FetchFailedException(
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Jenkins, test this please
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import
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Can one of the admins verify this patch?
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GitHub user bdrillard opened a pull request:
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[SPARK-18016][SQL][CATALYST] Code Generation: Constant Pool Limit
[class_splitting] increasing stack size for Catalyst tests
## What changes were proposed in this pull request?
Github user squito commented on the issue:
https://github.com/apache/spark/pull/15505
This might be a really dumb question, but please humor me -- can you
explain to me the threads involved, both before and after this change? I must
be missing something, because it seems to me it
Github user cloud-fan commented on the issue:
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retest this please
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https://github.com/apache/spark/pull/15505#discussion_r96889501
--- Diff:
core/src/main/scala/org/apache/spark/scheduler/cluster/CoarseGrainedSchedulerBackend.scala
---
@@ -602,6 +619,20 @@ class
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/16647
**[Test build #71666 has
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Github user cloud-fan commented on the issue:
https://github.com/apache/spark/pull/16647
cc @yhuai @gatorsmile @ericl
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