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Please write a proper PR description.
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Since the failure in SparkR is not related to this PR, I will merge this.
Thanks! Merged to master.
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[SPARK-14228][CORE][YARN] Lost executor of RPC disassociated, and occurs
exception: Could not find CoarseGrainedScheduler or it has been stopped
## What changes were proposed in this pull req
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--- Diff: dev/sparktestsupport/modules.py ---
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sparkr = Module(
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-depende
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[SPARK-22756] [Build] [SparkR] Run SparkR tests if hive_thriftserver module
has code changes
## What changes were proposed in this pull request?
The recent PR change in hive_thriftserver cau
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Github user vanzin commented on the issue:
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The SparkR tests seem flaky all of a sudden; other PRs are also failing. So
I'm just going to ignore that failure.
Merging to master.
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The Arrow 0.8.0 release vote just started today. Assuming it passes, the
earliest you could see packages pushed to PyPI or conda-forge would be sometime
on Thursday evening or Friday.
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[SPARK-16060][SQL] Support Vectorized ORC Reader
## What changes were proposed in this pull request?
This PR adds a ORC columnar-batch reader to native `OrcFileFormat`.
## Ho
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Just FYI, the test failure is not related to this PR.
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Github user shaneknapp commented on the issue:
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yeah, i can do the upgrade next week. i'll be working remotely from the
east coast, but unavailable at all on monday due to travel.
On Mon, Dec 11, 2017 at 1:59 PM, Bryan Cutler
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@BryanCutler could you just pull my changes into this PR since we need to
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>Jenkins cannot support to install multiple versions of PyArrow?
@zsxwing that's right, we will have to coordinate to make sure the Jenkins
pyarrow is upgraded to version 0.8 as well. I
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>When I tried to run tests locally, I got OutOfMemoryException
@ueshin , you got that error because the latest Arrow has upgraded Netty to
4.1.17 but Spark has an older version on the cl
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Sorry, I need to revert the changes. It breaks CRAN.
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/cc @brkyvz @zsxwing
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I saw #18974 tried to upgrade Arrow but got closed due to some Jenkins
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@kiszk for instance it can remove one entry for every timestamp function
(to_timestamp or from_utc_timestamp). Of course #19811 is the most important
PR, because it solves the problem. But I think
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Github user gatorsmile commented on the issue:
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Github user asfgit closed the pull request at:
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Github user vanzin commented on a diff in the pull request:
https://github.com/apache/spark/pull/19942#discussion_r156177369
--- Diff:
core/src/main/scala/org/apache/spark/deploy/SparkSubmitArguments.scala ---
@@ -291,6 +291,18 @@ private[deploy] class SparkSubmitArguments(args:
S
Github user SparkQA commented on the issue:
https://github.com/apache/spark/pull/19717
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Github user srowen commented on the issue:
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Github user liyinan926 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19717#discussion_r156176319
--- Diff: docs/configuration.md ---
@@ -157,13 +157,33 @@ of the most common options to set are:
or in your default properties file.
Github user liyinan926 commented on a diff in the pull request:
https://github.com/apache/spark/pull/19717#discussion_r156176301
--- Diff: core/src/test/scala/org/apache/spark/util/UtilsSuite.scala ---
@@ -1146,6 +1146,27 @@ class UtilsSuite extends SparkFunSuite with
ResetSystemPr
Github user vanzin commented on a diff in the pull request:
https://github.com/apache/spark/pull/19717#discussion_r156172100
--- Diff: docs/configuration.md ---
@@ -157,13 +157,33 @@ of the most common options to set are:
or in your default properties file.
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