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GitHub user wangyum opened a pull request:
https://github.com/apache/spark/pull/18833
[SPARK-21625][SQL] sqrt(negative number) should be null.
## What changes were proposed in this pull request?
This PR makes `sqrt(negative number)` to null, same as Hive and MySQL.
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Github user gatorsmile commented on the issue:
https://github.com/apache/spark/pull/18808
I hit the same issue! Thanks for fixing it!
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GitHub user mpjlu opened a pull request:
https://github.com/apache/spark/pull/18832
[SPARK-21623][ML]fix RF doc
## What changes were proposed in this pull request?
comments of parentStats in RF are wrong.
parentStats is not only used for the first iteration, it is used
Github user SparkQA commented on the issue:
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Github user srowen commented on the issue:
https://github.com/apache/spark/pull/18811
Ah, I'm sorry I misled you a bit here @zuotingbing . Yes you found another
unused variable, but, it's in code that is copied directly from Hive. I think
we should leave HiveSessionImplwithUGI
Github user srowen commented on the issue:
https://github.com/apache/spark/pull/18815
This won't necessarily be available to people viewing the UI? it could be
an HDFS location
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Github user yaooqinn commented on a diff in the pull request:
https://github.com/apache/spark/pull/18668#discussion_r131074348
--- Diff: docs/configuration.md ---
@@ -2335,5 +2335,59 @@ The location of these configuration files varies
across Hadoop versions, but
a common
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Github user srowen commented on the issue:
https://github.com/apache/spark/pull/18749
Yes, this isn't RTC. It isn't even RTC with 1-vote consensus, because you
rightly say that you could merge with no other votes if it were obviously not
required. But whatever. We can pick the
Github user rxin commented on the issue:
https://github.com/apache/spark/pull/18749
@HyukjinKwon you weren't a committer before :)
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Github user rxin commented on the issue:
https://github.com/apache/spark/pull/18749
@srowen search for "RTC vs CTR (was: Concerning Sentry...)"
From Todd Lipcon:
```
I don't have incubator stats... nor do I have a good way to measure "most
active" or "most
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/18749
(BTW, just for clarification, I think anyone can use that approve feature.
I did it before - `https://github.com/apache/spark/pull/17734`)
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Github user srowen commented on the issue:
https://github.com/apache/spark/pull/18749
RTC means a vote happens for each change:
https://www.apache.org/foundation/glossary.html#ReviewThenCommit
That's not what we do. What debate are you referring to?
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Github user rxin commented on the issue:
https://github.com/apache/spark/pull/18749
Actually Sean I disagree. Spark has always been review then commit from the
days before it entered ASF. In a huge debate last year within the ASF on RTC vs
CTR, Spark was cited as a prominent example.
Github user yaooqinn commented on a diff in the pull request:
https://github.com/apache/spark/pull/18668#discussion_r131068575
--- Diff: docs/configuration.md ---
@@ -2335,5 +2335,59 @@ The location of these configuration files varies
across Hadoop versions, but
a common
Github user yaooqinn commented on a diff in the pull request:
https://github.com/apache/spark/pull/18668#discussion_r131068501
--- Diff: docs/configuration.md ---
@@ -2335,5 +2335,59 @@ The location of these configuration files varies
across Hadoop versions, but
a common
Github user srowen commented on the issue:
https://github.com/apache/spark/pull/18749
Formally, our model is "Commit Then Review". No approval or vote is
required for any change, but changes can be retroactively vetoed.
https://www.apache.org/foundation/glossary.html#CommitThenReview
Github user HyukjinKwon commented on the issue:
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I see. Thanks for the details and explanation.
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Github user rxin commented on the issue:
https://github.com/apache/spark/pull/18749
Ah OK. That's what we are discussing here. In the past it has always been
an explicit "LGTM". That was defined before github had even the approval
feature. Now most committers are actually not ASF
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Github user dilipbiswal commented on the issue:
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retest this please
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Github user HyukjinKwon commented on the issue:
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I was wondering if other methods such as SGTM or a Github approval aa an
approval for a patch are not allowed by rule. I usually say based on
documentation or references to other guys and I
Github user rxin commented on the issue:
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Still looking into it, but the failure is related to reuse exchange and
caching.
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Github user rxin commented on the issue:
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What's your point? You should be able to merge PR without anybody reviewing?
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Github user HyukjinKwon commented on the issue:
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I understood Spark have used LGTM as convention and it is a good way to
show an approval as a sign-off but I meant, is "LGTM", not any other methods,
required before merging it?
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GitHub user actuaryzhang opened a pull request:
https://github.com/apache/spark/pull/18831
[SPARK-21622][ML][SparkR] Support offset in SparkR GLM
## What changes were proposed in this pull request?
Support offset in SparkR GLM #16699
You can merge this pull request into a Git
Github user rxin commented on the issue:
https://github.com/apache/spark/pull/18749
Yes.
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Github user yanboliang commented on the issue:
https://github.com/apache/spark/pull/18538
ok to test
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Github user jerryshao commented on the issue:
https://github.com/apache/spark/pull/18830
Nice catch, looks good to me.
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Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/18749
Hm, do you mean this line?
> Reviewers can indicate that a change looks suitable for merging with a
comment such as: âI think this patch looks goodâ. Spark uses the LGTM
convention
Github user viirya commented on the issue:
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@gatorsmile
scala> df.groupBy(lit(2)).agg(col("a")).queryExecution.logical
res6: org.apache.spark.sql.catalyst.plans.logical.LogicalPlan =
'Aggregate [2], [2 AS 2#51,
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Github user viirya commented on the issue:
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When using Dataset groupBy API, if you use int literals as grouping
expressions, do we filter this case out for substituting `UnresolvedOrdinals`?
Seems there is no related logic to prevent it.
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Github user gatorsmile commented on the issue:
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Our Dataset APIs support `conf.groupByOrdinal`? If so, this might surprise
me. `conf.groupByOrdinal` was introduced for SQL APIs only.
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Github user rxin commented on the issue:
https://github.com/apache/spark/pull/18749
It is documented: http://spark.apache.org/contributing.html
It's been the convention forever and it's also good to use one way rather
than multiple, so I'd prefer us just using that ... until
Github user gatorsmile commented on the issue:
https://github.com/apache/spark/pull/18668
@vanzin @zhzhan @tejasapatil Could you also help review the documentation
and the fix? Thanks!
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Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/18809
Thank you @felixcheung and @actuaryzhang.
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Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/18668#discussion_r131060237
--- Diff: docs/configuration.md ---
@@ -2335,5 +2335,59 @@ The location of these configuration files varies
across Hadoop versions, but
a common
Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/18668#discussion_r131059952
--- Diff: docs/configuration.md ---
@@ -2335,5 +2335,59 @@ The location of these configuration files varies
across Hadoop versions, but
a common
Github user actuaryzhang commented on the issue:
https://github.com/apache/spark/pull/18809
LGTM
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Github user jerryshao commented on a diff in the pull request:
https://github.com/apache/spark/pull/18628#discussion_r131059886
--- Diff:
sql/hive-thriftserver/src/main/scala/org/apache/spark/sql/hive/thriftserver/SparkSQLCLIService.scala
---
@@ -57,6 +59,19 @@ private[hive]
Github user ConeyLiu commented on the issue:
https://github.com/apache/spark/pull/18830
@cloud-fan @vanzin Would you mind take a lookï¼ Thanks a lot.
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Github user ConeyLiu commented on the issue:
https://github.com/apache/spark/pull/18830
You can see here
[L208](https://github.com/apache/spark/blob/master/core/src/main/scala/org/apache/spark/storage/DiskBlockObjectWriter.scala#L208),
when we called 'revertPartialWritesAndClose',
Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/18668#discussion_r131059673
--- Diff: docs/configuration.md ---
@@ -2335,5 +2335,59 @@ The location of these configuration files varies
across Hadoop versions, but
a common
Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/18824#discussion_r131059637
--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/client/HiveClientImpl.scala
---
@@ -413,7 +414,10 @@ private[hive] class HiveClientImpl(
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/18749
I think we should rather make https://spark-prs.appspot.com recognising the
github approval as well .. I considered github approval as an approval for this
patch.
BTW, for now, is it
Github user AmplabJenkins commented on the issue:
https://github.com/apache/spark/pull/18830
Can one of the admins verify this patch?
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Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/18668#discussion_r131059429
--- Diff: docs/configuration.md ---
@@ -2335,5 +2335,59 @@ The location of these configuration files varies
across Hadoop versions, but
a common
GitHub user ConeyLiu opened a pull request:
https://github.com/apache/spark/pull/18830
[SPARK-21621][Core] Reset numRecordsWritten after
DiskBlockObjectWriter.commitAndGet called
## What changes were proposed in this pull request?
We should reset numRecordsWritten to zero
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Github user wangyum commented on the issue:
https://github.com/apache/spark/pull/18413
@HyukjinKwon Could you help review this?
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