Github user yhuai commented on the issue:
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Cool. Thanks! I may have time today or tomorrow. I will try to take a look
at it during the weekend.
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--- Diff:
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@@ -200,22 +200,17 @@ abstract class
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Github user asfgit closed the pull request at:
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Github user liancheng commented on the issue:
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Nit: All occurrences of `_global_temp` in the PR description should be
replaced to `global_temp`.
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Github user sethah commented on the issue:
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Right now, if a multinomial family is used in LOR, it silently ignores
`threshold` regardless. I don't really like that behavior, but perhaps we can
focus on it in (and add some tests) in
Github user sethah commented on a diff in the pull request:
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Github user liancheng commented on the issue:
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LGTM. Merging to master.
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Github user yhuai commented on the issue:
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Can you try `CREATE TABLE tmp_default(id INT) as select ` and see if
the table will be converted to parquet format?
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Github user cloud-fan commented on the issue:
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I'll update this PR after the global temp view
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Can one of the admins verify this patch?
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GitHub user yucai opened a pull request:
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[SPARK-17635][SQL] Remove hardcode "agg_plan" in HashAggregateExec
## What changes were proposed in this pull request?
"agg_plan" are hardcoded in HashAggregateExec, which have potential
Github user yanboliang commented on the issue:
https://github.com/apache/spark/pull/15113
Further more, ```weightCol=None``` in the Python API doc may be confused
for users, I think we can add some annotations to clarify the meanings. Thanks.
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@BryanCutler Thanks for working on this. I'm a bit worried that if users
set ```weightCol = None``` for Python means he would like to set ```weightCol =
null``` for Scala.
The common
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Github user andrewor14 commented on the issue:
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Got it. I think back then when I wrote that comment we still haven't
supported cluster mode with python yet. It's just a little confusing if we're
reading that comment in isolation.
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Github user yanboliang commented on the issue:
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@WeichenXu123 We should also expose ```coefficientMatrix``` and
```interceptVector``` for ```LogisticRegressionModel```. Meanwhile, update the
Python docs for supporting multinomial logistic
Github user asfgit closed the pull request at:
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Github user yanboliang commented on the issue:
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LGTM, merged into master. Thanks!
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Github user HyukjinKwon commented on the issue:
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@davies Do you mind if I ask to confirm this? This would at least close a
open JIRA. If you decide this comment is verbose and unneeded, I am happy to
close this.
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Github user HyukjinKwon commented on the issue:
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This PR removes duplicated logics which I guess is not a safe-guard because
they are inconsistent. I would appreciate if you both @rxin and @liancheng take
a look please.
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Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/14399
Hi @liancheng , I'd appreciate if you could take a look please.
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Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/14172
Gentle ping @yhuai and @liancheng
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Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/14035
Thank you!!
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Github user yanboliang commented on the issue:
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Sorry for late response. I like this change and will have a look soon.
Thanks.
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Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/15049
Hi @davies What you do think about this? I can add some more benchmarks if
you think I need more.
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Github user srowen commented on the issue:
https://github.com/apache/spark/pull/14467
That LGTM. I'll leave it open a bit for any more comments.
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Github user srowen commented on the issue:
https://github.com/apache/spark/pull/12601
OK, this isn't really my area. It looks reasonable to me. @gatorsmile ?
I think https://github.com/apache/spark/pull/12601#issuecomment-246165894
was suggesting that some short notes should be
Github user skonto commented on a diff in the pull request:
https://github.com/apache/spark/pull/14650#discussion_r80014437
--- Diff: core/src/main/scala/org/apache/spark/util/Utils.scala ---
@@ -1962,6 +1962,20 @@ private[spark] object Utils extends Logging {
path
Github user HyukjinKwon commented on the issue:
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Hi @mengxr, @yanboliang and @jkbradley, if these changes are so big, I can
just leave `testImplicits` and let others fix them later without sweeping.
Could you please take a look?
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Github user srowen commented on the issue:
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Yes that's better IMHO. It makes this more consistent. Word2Vec was the
only case that looked for an exact match on nullability when it was expecting
nullable input (i.e. pointlessly disallowed
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Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/15198
Thanks, I just updated them.
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Github user srowen commented on the issue:
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Agree, and I would add: 9440 15023 14643 14827
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--- Diff: core/src/main/scala/org/apache/spark/util/Utils.scala ---
@@ -1962,6 +1962,20 @@ private[spark] object Utils extends Logging {
path
Github user HyukjinKwon commented on the issue:
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I don't mind closing this if they are so few. cc @srowen
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Github user HyukjinKwon commented on the issue:
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I might have to propose this later after queuing up those more; however, it
seems some PRs against a branch to a branch such as 15118, 15184 and 15183 are
triggering AppVeyor tests, leaving a
GitHub user HyukjinKwon opened a pull request:
https://github.com/apache/spark/pull/15198
[BUILD] Closes some stale PRs
## What changes were proposed in this pull request?
This PR proposes to close some stale PRs and ones suggested to be closed by
committer(s)
Github user skonto commented on a diff in the pull request:
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--- Diff:
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@@ -73,37 +94,55 @@ private[mesos] class
Github user skonto commented on a diff in the pull request:
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--- Diff:
core/src/main/scala/org/apache/spark/util/SparkConfigParseUtils.scala ---
@@ -0,0 +1,48 @@
+/*
+ * Licensed to the Apache Software
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Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/14963
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Github user zhangxinyu1 commented on the issue:
https://github.com/apache/spark/pull/15197
@marmbrus
I propose this feature mainly because we require output streaming query
results via http api. One of use cases is real-time alarm. It's essential to
send alarm messages in real
Github user vruusmann commented on the issue:
https://github.com/apache/spark/pull/3062
@manugarri You can export fitted pipeline models to PMML using the
[JPMML-SparkML-Package](https://github.com/jpmml/jpmml-sparkml-package) Apache
Spark Package. There's a worked-out PySpark
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/15197
Can one of the admins verify this patch?
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