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let's just say, happy to discuss :)
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Github user felixcheung commented on a diff in the pull request:
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--- Diff: R/pkg/inst/tests/testthat/test_streaming.R ---
@@ -61,6 +61,7 @@ test_that("read.stream, write.stream, awaitTermination,
stopQuery", {
GitHub user felixcheung opened a pull request:
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[SPARK-20192][SPARKR] SparkR migration guide to 2.2.0
## What changes were proposed in this pull request?
Updating R Programming Guide
## How was this patch tested?
Github user kevinyu98 commented on a diff in the pull request:
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--- Diff:
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@@ -24,13 +24,13 @@ import
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Thanks.
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cc @tdas @marmbrus
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LGTM. Minor comment
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Github user shivaram commented on a diff in the pull request:
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--- Diff: R/pkg/inst/tests/testthat/test_streaming.R ---
@@ -61,6 +61,7 @@ test_that("read.stream, write.stream, awaitTermination,
stopQuery", {
Github user zero323 commented on the issue:
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Don't take away my hope :)
i think that `grouping_bit`is OK. It is descriptive, doesn't introduce
generic `_col` and we can avoid masking. I'll resolve the conflicts and update
PR in a
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merged to master
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Github user felixcheung commented on the issue:
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I'm not sure there is one rule for this - we would need to look at it on a
case-by-case basis. Generally we should try to avoid conflict, because it is
inconvenient and breaks any existing code
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merged to master/2.2
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Github user 10110346 commented on the issue:
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@srowen, can you review it again?
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Github user viirya commented on a diff in the pull request:
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--- Diff: python/pyspark/sql/column.py ---
@@ -171,6 +171,58 @@ def __init__(self, jc):
__ge__ = _bin_op("geq")
__gt__ = _bin_op("gt")
Github user zero323 commented on a diff in the pull request:
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--- Diff: python/pyspark/sql/column.py ---
@@ -171,6 +171,58 @@ def __init__(self, jc):
__ge__ = _bin_op("geq")
__gt__ = _bin_op("gt")
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Github user zero323 commented on the issue:
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What I like about masking is that is relatively explicit:
> library(SparkR)
Attaching package: âSparkRâ
The following objects are masked from
Github user zero323 commented on the issue:
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> strange error with AppVeyor..
Indeed strange. `tempfile` conflict is not likely, is it?
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cc @cloud-fan
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--- Diff:
core/src/main/scala/org/apache/spark/deploy/rest/RestSubmissionServer.scala ---
@@ -214,15 +214,15 @@ private[rest] abstract class
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Github user felixcheung commented on the issue:
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strange error with AppVeyor..
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Github user felixcheung commented on the issue:
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yea, I agree it's not ideal and I'm not in favor of dispatch hacking either.
I think the latest you have is reasonable... but as you say, perhaps this
isn't worthwhile to iterate that
Github user viirya commented on a diff in the pull request:
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--- Diff:
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---
@@ -461,68 +461,267 @@ case class
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@@ -461,68 +461,267 @@ case class
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@@ -461,68 +461,267 @@ case class
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--- Diff:
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---
@@ -24,13 +24,13 @@ import
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--- Diff:
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@@ -1086,10 +1106,22 @@ class AstBuilder extends
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--- Diff:
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@@ -1086,10 +1106,22 @@ class AstBuilder extends
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Github user viirya commented on the issue:
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I guess you can directly ask the jenkins to retest like above too,
@kevinyu98.
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GitHub user felixcheung opened a pull request:
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[SPARK-20541][SPARKR][SS] support awaitTermination without timeout
## What changes were proposed in this pull request?
Add without param for timeout - will need this to submit a job
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--- Diff: python/pyspark/sql/column.py ---
@@ -171,6 +171,58 @@ def __init__(self, jc):
__ge__ = _bin_op("geq")
__gt__ = _bin_op("gt")
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retest this please
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[SPARK-20015][SPARKR][DOC][EXAMPLE] Document R Structured Streaming
(experimental) in R vignettes and R & SS programming guide, R example
## What changes were proposed in this pull request?
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@vanzin, can you take a look at this? It is a dynamic allocation bug.
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[SPARK-20540][CORE] Fix unstable executor requests.
There are two problems fixed in this commit. First, the
ExecutorAllocationManager sets a timeout to avoid requesting executors
too often.
Github user zero323 commented on the issue:
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To keep this option open
https://github.com/zero323/spark/commit/a67c77e7bdf40ea40807e9d984975c04738d327d
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@cloud-fan, I've removed the metrics work-around so this is ready to go.
I'm all for getting this in and fixing the broken query plans.
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Github user mridulm commented on the issue:
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@vanzin Since hadoop 1 is no longer maintained, I was referring to hadoop
security as yarn security - you are right, they are not the same : though in
what I described, replacing one with another,
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The failing test case is : build/sbt "test-only
org.apache.spark.deploy.master", I can run successful locally.
build/sbt "test-only org.apache.spark.deploy.master"
Total time: 16 s,
Github user zero323 commented on the issue:
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Thanks @felixcheung
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I thought about it before, but there are two or three problems:
- `base::grouping` has `...` signature so it is not possible without
changing behavior or adding nullary variant.
- It
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Github user felixcheung commented on the issue:
https://github.com/apache/spark/pull/17809
merged to master, thanks!
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Github user vanzin commented on the issue:
https://github.com/apache/spark/pull/17723
No YARN API is being exposed in core. There are hadoop security APIs being
exposed in the current patch (`Credentials`). It's different.
Michael's patch is not exposing YARN's way of using
Github user felixcheung commented on the issue:
https://github.com/apache/spark/pull/17807
I understanding what you are saying and for frequent R users this might not
really be a big issue, so far we are taking the view of avoiding masking any
inconvenience, if we if at all could.
Github user kiszk commented on the issue:
https://github.com/apache/spark/pull/17087
ping @marmbrus
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