Github user kevinyu98 commented on a diff in the pull request:
https://github.com/apache/spark/pull/12646#discussion_r114703725
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/stringExpressions.scala
---
@@ -461,68 +462,270 @@ case class
Github user QQshu1 commented on the issue:
https://github.com/apache/spark/pull/16561
hi , I have a question, why we should Eliminate View in the first of the
optimizer.?
thank you.@jiangxb1987
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Github user zero323 commented on a diff in the pull request:
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--- Diff: R/pkg/R/DataFrame.R ---
@@ -3715,3 +3715,34 @@ setMethod("rollup",
sgd <- callJMethod(x@sdf, "rollup", jcol)
Github user ueshin commented on a diff in the pull request:
https://github.com/apache/spark/pull/17678#discussion_r114700907
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/ObjectAggregationIterator.scala
---
@@ -83,6 +85,7 @@ class
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GitHub user wangyum opened a pull request:
https://github.com/apache/spark/pull/17856
[SPARK-19660][SQL] Replace the deprecated property name fs.default.name to
fs.defaultFS that newly introduced
## What changes were proposed in this pull request?
Replace the deprecated
Github user felixcheung commented on the issue:
https://github.com/apache/spark/pull/17825
you know - it would definitely be a better experience for the R user, so we
should try that - it might break with the generic in `stats::alias` though
and speaking of, we should
Github user felixcheung commented on the issue:
https://github.com/apache/spark/pull/17817
merged to master/2.2
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Github user lins05 commented on the issue:
https://github.com/apache/spark/pull/17750
IMO we should not enable checkpointing in fine-grained mode. Because with
checkpointing enabled, mesos agents would persist all status updates to disk
which means great I/O cost because fine-grained
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Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/17855
cc @srowen, could you take a look please?
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GitHub user HyukjinKwon opened a pull request:
https://github.com/apache/spark/pull/17855
[INFRA] Close stale PRs
## What changes were proposed in this pull request?
This PR proposes to close a stale PR, several PRs suggested to be closed by
a committer and obviously
Github user asfgit closed the pull request at:
https://github.com/apache/spark/pull/17817
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Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/9
Do you guys mind if I propose to close this PR?
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GitHub user mariahualiu opened a pull request:
https://github.com/apache/spark/pull/17854
[SPARK-20564][Deploy] Reduce massive executor failures when executor count
is large (>2000)
## What changes were proposed in this pull request?
In applications that use over 2000
Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/17851#discussion_r114698221
--- Diff: R/pkg/R/DataFrame.R ---
@@ -3715,3 +3715,34 @@ setMethod("rollup",
sgd <- callJMethod(x@sdf, "rollup", jcol)
Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/17851#discussion_r114698264
--- Diff: R/pkg/R/DataFrame.R ---
@@ -3715,3 +3715,34 @@ setMethod("rollup",
sgd <- callJMethod(x@sdf, "rollup", jcol)
Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/17851#discussion_r114698385
--- Diff: R/pkg/R/DataFrame.R ---
@@ -3715,3 +3715,34 @@ setMethod("rollup",
sgd <- callJMethod(x@sdf, "rollup", jcol)
Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/17851#discussion_r114698072
--- Diff: R/pkg/R/DataFrame.R ---
@@ -3715,3 +3715,34 @@ setMethod("rollup",
sgd <- callJMethod(x@sdf, "rollup", jcol)
Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/17851#discussion_r114698515
--- Diff: R/pkg/inst/tests/testthat/test_sparkSQL.R ---
@@ -2147,6 +2147,18 @@ test_that("join(), crossJoin() and merge() on a
DataFrame", {
Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/17851#discussion_r114698548
--- Diff: R/pkg/R/generics.R ---
@@ -572,6 +572,10 @@ setGeneric("first", function(x, ...) {
standardGeneric("first") })
#' @export
Github user felixcheung commented on a diff in the pull request:
https://github.com/apache/spark/pull/17851#discussion_r114698295
--- Diff: R/pkg/R/DataFrame.R ---
@@ -3715,3 +3715,34 @@ setMethod("rollup",
sgd <- callJMethod(x@sdf, "rollup", jcol)
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/17853
@crjk21 it looks mistakenly open. Could you close this please?
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GitHub user crjk21 opened a pull request:
https://github.com/apache/spark/pull/17853
Branch 2.2
## What changes were proposed in this pull request?
(Please fill in changes proposed in this fix)
## How was this patch tested?
(Please explain how this patch
Github user holdenk commented on the issue:
https://github.com/apache/spark/pull/17831
Thanks for making this PR with the details @gatorsmile it appears to be
orthogonal to this change. Historically we've treated Python API parity fixes
as closer to bug fixes rather than new features
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Github user jinxing64 commented on a diff in the pull request:
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--- Diff:
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@@ -100,7 +114,14 @@ public void
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Github user asfgit closed the pull request at:
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Github user rxin commented on the issue:
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Merging in master/2.2.
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Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/17831
cc @viirya too who I believe is appropriate to review this.
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Github user guoxiaolongzte commented on the issue:
https://github.com/apache/spark/pull/17841
Where is the risk? High concurrency? Transaction processing? This is where
I am puzzled.
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Github user vanzin commented on the issue:
https://github.com/apache/spark/pull/17723
To ask a more direct question:
The only public interface being added in this change is
`ServiceCredentialProvider`. It's an interface that service-specific libraries
(e.g. a Solr connector,
Github user HyukjinKwon commented on the issue:
https://github.com/apache/spark/pull/17831
It sounds orthogonal to me as well. LGTM.
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Github user jerryshao commented on the issue:
https://github.com/apache/spark/pull/17841
I think @srowen already clarified it very clearly, you can use it at your
own risk, but to make it public and add to the doc should be well considered.
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Github user zero323 commented on a diff in the pull request:
https://github.com/apache/spark/pull/17825#discussion_r114687096
--- Diff: R/pkg/R/DataFrame.R ---
@@ -3715,3 +3715,25 @@ setMethod("rollup",
sgd <- callJMethod(x@sdf, "rollup", jcol)
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Github user guoxiaolongzte commented on the issue:
https://github.com/apache/spark/pull/17841
@jerryshao
I said that the use of the scene is real, do you agree?
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Github user zero323 commented on the issue:
https://github.com/apache/spark/pull/17825
I wonder if it would make more sense to make `alias` generic for both
`object` and `data`:
signature(object = "SparkDataFrame", data = "character")
and skip the type checks.
GitHub user jyu00 opened a pull request:
https://github.com/apache/spark/pull/17852
[SPARK-20546][Deploy] spark-class gets syntax error in posix mode
## What changes were proposed in this pull request?
Updated spark-class to turn off posix mode so the process substitution
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Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/17847#discussion_r114683203
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSource.scala
---
@@ -523,7 +530,8 @@ object DataSource {
Github user zero323 commented on the issue:
https://github.com/apache/spark/pull/17831
I think there is no conflict between #17848 and this. As of 2.2 we no
longer return `UserDefinedFunction` from `udf` (and we never documented
`UserDefinedFunctions`) so changes will have to be
Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/17847#discussion_r114683317
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/DataSource.scala
---
@@ -483,35 +483,42 @@ case class DataSource(
Github user mgummelt commented on the issue:
https://github.com/apache/spark/pull/17723
> a) we have explicitly based our support on it
What does this mean?
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Github user rdblue commented on the issue:
https://github.com/apache/spark/pull/17540
I'm not an expert on the metrics path, but I think we should be able to
join up the actual physical plans well enough to display everything. I doubt it
will be a long-term regression, but I don't
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Github user vanzin commented on the issue:
https://github.com/apache/spark/pull/17723
> This was my point - we should not introduce system specific api's into
spark core infrastructure api's/spi's
Sorry, I still have no idea what your point is. How do you suggest we
support
Github user zsxwing commented on the issue:
https://github.com/apache/spark/pull/17540
I was not saying there is no way to fix metrics. Just asking your thoughts.
If we don't have a concrete plan, it might be a long-term regression if just
merging this PR.
I just want to
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Github user mridulm commented on the issue:
https://github.com/apache/spark/pull/17723
@vanzip wrote:
> So, this is purely about handling Hadoop authentication for Hadoop
services.
This was my point - we should not introduce system specific api's into
spark core
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GitHub user zero323 opened a pull request:
https://github.com/apache/spark/pull/17851
[SPARK-20585][SPARKR] R generic hint support
## What changes were proposed in this pull request?
Adds support for generic hints on `SparkDataFrame`
## How was this patch tested?
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Github user rdblue commented on the issue:
https://github.com/apache/spark/pull/17540
@zsxwing, you don't think there's a way to fix metrics? I don't know
exactly how to fix the UI to show two plans worth of metrics, but it seems like
it can be done. What about also updating
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Github user zero323 commented on the issue:
https://github.com/apache/spark/pull/17848
Disabling optimizations aside, to what extent can we actually support
nondeterministic functions? Right now a common user mistake is to run RNG
inside an UDF. `nonDeterministic`could suggest it is
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Github user zsxwing commented on the issue:
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> @zsxwing, I don't know. Sounds like we should fix the underlying problem
that there are 2 physical plans.
SQL metrics won't work without fixing it. IMO, that's more serious than the
Github user rdblue commented on the issue:
https://github.com/apache/spark/pull/17540
@zsxwing, I don't know. Sounds like we should fix the underlying problem
that there are 2 physical plans.
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Github user HyukjinKwon commented on the issue:
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Yea, thanks for chiming in. It helped me a lot to understand the context.
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Github user zsxwing commented on the issue:
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> That requires breaking the command into two phases, one to get a
SparkPlan and one to run it.
Yeah, but how to show metrics you get from a plan on another plan's DAG
considering these
Github user zero323 commented on the issue:
https://github.com/apache/spark/pull/17831
Thanks @gatorsmile
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Github user rdblue commented on the issue:
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@zsxwing, there should be a fix for the metrics without waiting for all of
the bad plans to be fixed (which is to basically eliminate the use of
`ExecutedCommandExec`).
The metrics are
Github user lw-lin commented on the issue:
https://github.com/apache/spark/pull/17346
thank you @zsxwing
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Github user zsxwing commented on the issue:
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@rdblue I just tested this PR and found that I could not see any SQL
metrics on Web UI. This is pretty important for many users to analyze their
queries.
What's your plan to fix it? As far
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Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/17834
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Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/17100
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Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/17850
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https://github.com/apache/spark/pull/17850
Merged build finished. Test FAILed.
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