Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/14431
@gatorsmile, I'm able to access `groupingExprs` from `SQLUtils.scala`
through `val groupingExprs: Seq[Expression],` however it seems to be
challenging to access the name of the column from pure
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/14431
Alright, give me couple days to address to those cases.
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Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/14431
I think 'prepend' sounds better. What do you think ?
Yes, the `key` in `function(key, x) { x }` can be useful for some use cases
but I also think that the user could easily prepend
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/14431
I think @falaki's approach is good, only I find the key which is passed as
an argument together with x as an input of function is a little superfluous.
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Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/14431
Thank you, @gatorsmile! I'll give a try.
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Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/14431
@falaki, I'd be fine with a separate `gapplyWithKeys()` method too.
@shivaram, @felixcheung what do you think ? Should we add a new
`gapplyWithKeys()` method ?
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Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/14431#discussion_r124327866
--- Diff: R/pkg/R/DataFrame.R ---
@@ -1465,10 +1464,10 @@ setMethod("dapplyCollect",
#'
#' Result
#' -
-#' Model
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/14431
yes, but we only need read access.
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Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/14742
yes, we can close this, but it would be great if you could help us a way to
access the grouping columns from SparkR in #14431
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Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/14742
Hi @gatorsmile, #14431 depends on this. Is there a way I can access the
grouping columns from `RelationalGroupedDataset` ?
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Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/14431
Hi everyone, yes it depends on #14742 . I've been asked to close #14742.
For this PR I need to access the grouping columns. If you think that there
is an alternative way of accessing
Github user NarineK closed the pull request at:
https://github.com/apache/spark/pull/10162
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Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/10162
@HyukjinKwon do you mean closing or fixing the PR ? As I understand from
@gatorsmile he wants to close it
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Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/10162
I'd propose to have:
1. One input argument: suffixes[left, right] (if you want we can have 2
similar to pandas).
2. Default values for suffixes (I think defaults are more convenient
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/10162
In pandas it has 2 arguments:
lsuffix='', rsuffix='', respectively for left and right sides. And it
appends the suffixes to all column names regardless if they are in join
condition
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/10162
Thank you for following up on this, @marmbrus !
I looked into two places: R and Pandas DataFrames.
In R it seems that they give new names to columns(columns which aren't in
merge/join
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/10162
I am trying different ways to solve the problem without renaming the
columns and it seems that a better place to change the column names would be
here:
https://github.com/apache/spark/blob/master
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/10162
I see, I can go over the pull request this weekend. Thanks for the feedback.
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Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/10162
I'd be happy to update to the latest master if we want to review this now.
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Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/14742
@liancheng, @rxin, Do you think adding `columns` to
`RelationalGroupedDataset` is reasonable or should we find a workaround on R
side ?
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Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/14431
Made a pull request for grouping columns: #14742
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Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/14742
cc: @shivaram, @liancheng
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GitHub user NarineK opened a pull request:
https://github.com/apache/spark/pull/14742
[SPARK-17177][SQL] Make grouping columns accessible from
`RelationalGroupedDataset`
## What changes were proposed in this pull request?
Currently, once we create `RelationalGroupedDataset
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/14384#discussion_r74551161
--- Diff: R/pkg/inst/tests/testthat/test_mllib.R ---
@@ -454,4 +454,61 @@ test_that("spark.survreg", {
}
})
+test_that(
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/14431
yes, @shivaram , that will be one way to do.
Basically, adding a new public function to `RelationalGroupedDataset` which
will return the column names.
If it is fine from SQL perspective
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/14431
My point is the following: Let's say we have the following:
`var relationalGroupedDataset = df.groupBy("col1", "col2");`
Now, having `relationalGroupedDataset` how can I f
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/14431
Thanks, @shivaram! Yes, we have a handle to RelationalGroupedDataset, but I
couldn't access column fields of RelationalGroupedDataset's instance. Is there
a way to access the columns
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/14384#discussion_r73999377
--- Diff: R/pkg/R/mllib.R ---
@@ -632,3 +642,147 @@ setMethod("predict", signature(object =
"AFTSurvivalRegressionModel"),
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/14384#discussion_r73999041
--- Diff: R/pkg/R/mllib.R ---
@@ -632,3 +642,147 @@ setMethod("predict", signature(object =
"AFTSurvivalRegressionModel"),
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/14384#discussion_r73998522
--- Diff: R/pkg/R/mllib.R ---
@@ -632,3 +642,147 @@ setMethod("predict", signature(object =
"AFTSurvivalRegressionModel"),
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/14431
It seems that, currently, in SparkR the `GroupedData` which represents
scala's GroupedData object doesn't have any information about the grouping
keys. `RelationalGroupedDataset` has a private
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/14431
cool! Let me give a try that option.
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Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/14431
That's a good point, @shivaram `worker.R` is the component which has the
keys and appends it to the output.
I don't see any elegant way of doing it in `worker.R` yet.
However, I
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/14431#discussion_r72916339
--- Diff: docs/sparkr.md ---
@@ -429,19 +431,19 @@ result <- gapplyCollect(
df,
"waiting",
function(key, x) {
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/14431#discussion_r72916310
--- Diff: docs/sparkr.md ---
@@ -398,23 +398,25 @@ and Spark.
{% highlight r %}
# Determine six waiting times with the largest eruption time
GitHub user NarineK opened a pull request:
https://github.com/apache/spark/pull/14431
[SPARK-16258][SparkR][WIP] Gapply add key attach option
## What changes were proposed in this pull request?
The following pull request addresses the new feature request described in
SPARK
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/12836
@shivaram, @sun-rui , I was wondering if someone created a jira for the
issue described here:
https://github.com/apache/spark/pull/12836#issuecomment-225403054
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Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/14090
Thanks, I've generated the docs with your suggested way @shivaram, but I'm
not sure if I see the same thing as you.
I still see some '{% highlight r %}' and some formatting issues in general.
I
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/14090
Thanks @shivaram, @felixcheung for the comments. I'll address those today.
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Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/14090#discussion_r70923645
--- Diff: docs/sparkr.md ---
@@ -316,6 +314,139 @@ head(ldf, 3)
{% endhighlight %}
+ Run a given function on a large dataset
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/14090#discussion_r70921996
--- Diff: docs/sparkr.md ---
@@ -316,6 +314,139 @@ head(ldf, 3)
{% endhighlight %}
+ Run a given function on a large dataset
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/14090#discussion_r70920518
--- Diff: docs/sparkr.md ---
@@ -316,6 +314,139 @@ head(ldf, 3)
{% endhighlight %}
+ Run a given function on a large dataset
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/14090#discussion_r70920244
--- Diff: docs/sparkr.md ---
@@ -316,6 +314,139 @@ head(ldf, 3)
{% endhighlight %}
+ Run a given function on a large dataset
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/14090
Added data type description
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Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/14090#discussion_r70202736
--- Diff: docs/sparkr.md ---
@@ -306,6 +306,64 @@ head(ldf, 3)
{% endhighlight %}
+ Run a given function on a large dataset grouping
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/14090#discussion_r70202321
--- Diff: docs/sparkr.md ---
@@ -306,6 +306,64 @@ head(ldf, 3)
{% endhighlight %}
+ Run a given function on a large dataset grouping
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/14090#discussion_r70198331
--- Diff: docs/sparkr.md ---
@@ -306,6 +306,64 @@ head(ldf, 3)
{% endhighlight %}
+ Run a given function on a large dataset grouping
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/14090#discussion_r70194370
--- Diff: docs/sparkr.md ---
@@ -306,6 +306,64 @@ head(ldf, 3)
{% endhighlight %}
+ Run a given function on a large dataset grouping
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/14090#discussion_r70168781
--- Diff: docs/sparkr.md ---
@@ -306,6 +306,64 @@ head(ldf, 3)
{% endhighlight %}
+ Run a given function on a large dataset grouping
GitHub user NarineK opened a pull request:
https://github.com/apache/spark/pull/14090
[SPARK-16112][SparkR] Programming guide for gapply/gapplyCollect
## What changes were proposed in this pull request?
Updates programming guide for spark.gapply/spark.gapplyCollect
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/13760
Do you have any questions on this @shivaram , @sun-rui ?
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Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/13760
@felixcheung , I've addressed the comments or put a comment for the
non-addressed ones.
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Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/13760#discussion_r68571809
--- Diff: R/pkg/R/DataFrame.R ---
@@ -1370,14 +1370,22 @@ setMethod("dapplyCollect",
#' columns with data types integer and string and the
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/13760#discussion_r68571761
--- Diff: R/pkg/R/group.R ---
@@ -198,62 +198,61 @@ createMethods()
#'
#' Applies a R function to each group in the input GroupedData
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/13760#discussion_r68571781
--- Diff: R/pkg/R/DataFrame.R ---
@@ -1419,6 +1427,80 @@ setMethod("gapply",
gapply(grouped, fu
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/13760#discussion_r68565249
--- Diff: R/pkg/R/group.R ---
@@ -198,62 +198,61 @@ createMethods()
#'
#' Applies a R function to each group in the input GroupedData
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/13760#discussion_r68563365
--- Diff: R/pkg/R/group.R ---
@@ -198,62 +198,61 @@ createMethods()
#'
#' Applies a R function to each group in the input GroupedData
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/13760#discussion_r68542491
--- Diff: R/pkg/R/DataFrame.R ---
@@ -1370,14 +1370,22 @@ setMethod("dapplyCollect",
#' columns with data types integer and string and the
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/13760#discussion_r68298040
--- Diff: R/pkg/R/group.R ---
@@ -243,17 +236,73 @@ setMethod("gapply",
signature(x = "GroupedData"),
func
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/13760#discussion_r68291007
--- Diff: R/pkg/R/group.R ---
@@ -199,17 +199,10 @@ createMethods()
#' Applies a R function to each group in the input GroupedData
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/13760#discussion_r68227494
--- Diff: R/pkg/R/group.R ---
@@ -199,17 +199,10 @@ createMethods()
#' Applies a R function to each group in the input GroupedData
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/13760#discussion_r68116142
--- Diff: R/pkg/R/group.R ---
@@ -199,17 +199,10 @@ createMethods()
#' Applies a R function to each group in the input GroupedData
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/13760#discussion_r68114211
--- Diff: R/pkg/R/group.R ---
@@ -242,18 +235,73 @@ createMethods()
setMethod("gapply",
signature(x = &q
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/13660#discussion_r67944525
--- Diff: docs/sparkr.md ---
@@ -262,6 +262,83 @@ head(df)
{% endhighlight %}
+### Applying User-defined Function
+In SparkR, we
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/13760#discussion_r67936513
--- Diff: R/pkg/R/DataFrame.R ---
@@ -1347,6 +1347,65 @@ setMethod("gapply",
gapply(grouped, fu
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/13790
@shivaram , I've noticed that I didn't associate the pull request with the
jira. I've just did it.
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Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/13790
cc: @sun-rui, @shivaram @felixcheung
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GitHub user NarineK opened a pull request:
https://github.com/apache/spark/pull/13790
remove duplicated docs in dapply
## What changes were proposed in this pull request?
Removed unnecessary duplicated documentation in dapply and dapplyCollect.
In this pull request I
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/13660
Hi @vectorijk , @felixcheung ,
As I was looking at the documentation generated in R I've noticed that
there is some duplicated information. I'm not sure if this is the right place
to ask about
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/12836
Thanks for the quick response. I'll create one.
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Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/12836
@vectorijk, should I do the pull request for the same jira -
https://issues.apache.org/jira/browse/SPARK-15672, or should I create a new
jira for the programming guide?
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GitHub user NarineK opened a pull request:
https://github.com/apache/spark/pull/13760
[SPARK-16012][SparkR] GapplyCollect - applies a R function to each group
similar to gapply and collects the result back to R data.frame
## What changes were proposed in this pull request
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/12836
Hi @vectorijk,
Thanks for asking, i think in a separate PR. Do you think including in
#13660 would be better ?
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Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/12836#discussion_r67265581
--- Diff: R/pkg/R/DataFrame.R ---
@@ -1266,6 +1266,83 @@ setMethod("dapplyCollect",
ldf
})
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/12836
Thanks, @shivaram and @sun-rui. Yes, I can work on programming guide for
gapply.
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Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/12836#discussion_r67264756
--- Diff: R/pkg/R/DataFrame.R ---
@@ -1266,6 +1266,83 @@ setMethod("dapplyCollect",
ldf
})
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/12836#discussion_r67264555
--- Diff: R/pkg/R/DataFrame.R ---
@@ -1266,6 +1266,83 @@ setMethod("dapplyCollect",
ldf
})
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/12836#discussion_r67197168
--- Diff: R/pkg/inst/worker/worker.R ---
@@ -79,75 +127,72 @@ if (numBroadcastVars > 0) {
# Timing broadcast
broadcastElap <- elaps
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/12836
Addressed your comments @sun-rui, please let me know if you have any
comments.
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Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/12836#discussion_r66745283
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/objects.scala ---
@@ -325,6 +330,71 @@ case class MapGroupsExec
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/12836#discussion_r66732763
--- Diff: R/pkg/R/group.R ---
@@ -142,3 +142,58 @@ createMethods <- function() {
}
createMethods()
+
+#' gap
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/12836#discussion_r66717543
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/RelationalGroupedDataset.scala ---
@@ -381,6 +385,50 @@ class RelationalGroupedDataset protected[sql
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/12836
Thanks @liancheng and @rxin !
With respect to your point, @rxin - "private[sql] signature in public
APIs ."
dapply added that signature to `Dataset.scala `and g
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/12836#discussion_r66712035
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/RelationalGroupedDataset.scala ---
@@ -381,6 +385,50 @@ class RelationalGroupedDataset protected[sql
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/13610
Thanks! Changed the title!
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Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/13610
@sun-rui , @liancheng, @shivaram
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GitHub user NarineK opened a pull request:
https://github.com/apache/spark/pull/13610
overwritting stringArgs in MapPartitionsInR
## What changes were proposed in this pull request?
As discussed in https://github.com/apache/spark/pull/12836
we need to override
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/12836#discussion_r66672823
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/object.scala
---
@@ -286,6 +290,9 @@ case class FlatMapGroupsInR
Github user NarineK commented on a diff in the pull request:
https://github.com/apache/spark/pull/12836#discussion_r66670797
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/object.scala
---
@@ -286,6 +290,9 @@ case class FlatMapGroupsInR
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/12836
Hi @sun-rui, hi @shivaram,
I've overwritten the stringArgs - I've pushed my changes in the following
branch. I haven't created a jira yet.
https://github.com/apache/spark/commit
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/12836
Sure, let me try to override stringArgs and give it a try.
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Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/12836
Thank you for the quick responses @sun-rui and @shivaram .
Here is how the `dataframe.queyExection.toString` printout starts with:
== Parsed Logical Plan
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/12836
Do you know what exactly caused this ?
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Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/12836
Hi @shivaram , hi @sun-rui ,
Surprisingly the `dataframe.queyExection.toString` both for dapply and
gapply is prepended by a huge array, which I'm not able to understand. It seems
that recent
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/12836
I can print-out the query plan on scala side and see what does it look like
for that example.
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Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/12836
not sure why it fails. It fails for my new test case on iris dataset. The
resulting dataframe has 35x2 dimensions.
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Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/12836
Locally, run-tests.sh run successfully, but it fails on jenkins ...
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Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/12836
@shivaram, I didn't change the code, but merged with master, because prior
to this the build was failing because some pyspark tests didn't pass.
After my today's merge, when I run gapply
Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/12836
Merged build finished. Test FAILed.
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Github user NarineK commented on the issue:
https://github.com/apache/spark/pull/12836
Test FAILed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/59998/
Test FAILed
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