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Github user JoshRosen commented on the pull request:
https://github.com/apache/spark/pull/2259#issuecomment-55510191
This looks good to me; merging it into master now. I wonder if we'll see a
net reduction in Jenkins flakiness due to using significantly fewer ephemeral
ports in
Github user asfgit closed the pull request at:
https://github.com/apache/spark/pull/2259
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Github user nchammas commented on the pull request:
https://github.com/apache/spark/pull/2259#issuecomment-55510267
Yeah, the bad diffs are especially weird. `class Dummy`? Really?
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Github user davies commented on the pull request:
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Jenkins, retest this please.
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Github user davies commented on the pull request:
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@JoshRosen The problem that will cause hanging has been fixed.
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Jenkins, retest this please.
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Github user JoshRosen commented on the pull request:
https://github.com/apache/spark/pull/2259#issuecomment-55068149
Hmm, I wonder why we're seeing these timeouts. It looks like both tests
failed in `recommendation.py`, so it might be worth running those tests locally
to see whether
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2259#issuecomment-55068303
yeah, I will investigate it locally.
On Tue, Sep 9, 2014 at 8:53 PM, Josh Rosen notificati...@github.com wrote:
Hmm, I wonder why we're seeing these
Github user JoshRosen commented on the pull request:
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Jenkins, retest this please.
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Github user JoshRosen commented on a diff in the pull request:
https://github.com/apache/spark/pull/2259#discussion_r17268480
--- Diff:
core/src/main/scala/org/apache/spark/api/python/PythonWorkerFactory.scala ---
@@ -199,9 +207,47 @@ private[spark] class
Github user JoshRosen commented on a diff in the pull request:
https://github.com/apache/spark/pull/2259#discussion_r17268576
--- Diff:
core/src/main/scala/org/apache/spark/api/python/PythonWorkerFactory.scala ---
@@ -199,9 +207,47 @@ private[spark] class
Github user JoshRosen commented on the pull request:
https://github.com/apache/spark/pull/2259#issuecomment-54890949
One general issue, not specifically related to this patch but still worth
fixing, is thread-safety for the collections in PythonWorkerFactory. It looks
like there's
Github user JoshRosen commented on a diff in the pull request:
https://github.com/apache/spark/pull/2259#discussion_r17269479
--- Diff: python/pyspark/worker.py ---
@@ -69,8 +69,12 @@ def main(infile, outfile):
ser = CompressedSerializer(pickleSer)
for _
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Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2259#discussion_r17271207
--- Diff: python/pyspark/worker.py ---
@@ -69,8 +69,12 @@ def main(infile, outfile):
ser = CompressedSerializer(pickleSer)
for _ in
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Jenkins, retest this please.
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Github user mateiz commented on the pull request:
https://github.com/apache/spark/pull/2259#issuecomment-54767509
You guys should time out the worker after some time period to avoid it
always consuming resources. If we have that, I think it should be on by default
-- in general it's
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2259#issuecomment-54775047
@mateiz It will time out the worker after 1 minute. It will reuse worker by
default, can be disabled by 'spark.python.worker.reuse = false', then it will
shut down the
Github user davies commented on the pull request:
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Jenkins, test this please.
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Jenkins, retest this please.
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Github user JoshRosen commented on the pull request:
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Jenkins, retest this please.
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Github user JoshRosen commented on the pull request:
https://github.com/apache/spark/pull/2259#issuecomment-54731896
Do you think worker re-use should be enabled by default?
The only problem that I anticipate is for applications that share a single
SparkContext with both
Github user JoshRosen commented on the pull request:
https://github.com/apache/spark/pull/2259#issuecomment-54731921
It would be interesting to measure the end-to-end performance impact for
more realistic jobs, especially ones that make use of large numbers of tasks
and large
Github user davies commented on the pull request:
https://github.com/apache/spark/pull/2259#issuecomment-54733273
It's already enabled by default. I had added benchmark result in the
description.
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Jenkins, retest this please.
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Jenkins, retest this please.
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GitHub user davies opened a pull request:
https://github.com/apache/spark/pull/2259
[SPARK-3030] [PySpark] Reuse Python worker
Reuse Python worker to avoid the overhead of fork() Python process for each
tasks. It also tracks the broadcasts for each worker, avoid sending repeated
Github user JoshRosen commented on a diff in the pull request:
https://github.com/apache/spark/pull/2259#discussion_r17091100
--- Diff: python/run-tests ---
@@ -50,7 +50,7 @@ echo Running PySpark tests. Output is in
python/unit-tests.log.
# Try to test with Python 2.6,
Github user davies commented on a diff in the pull request:
https://github.com/apache/spark/pull/2259#discussion_r17091311
--- Diff: python/run-tests ---
@@ -50,7 +50,7 @@ echo Running PySpark tests. Output is in
python/unit-tests.log.
# Try to test with Python 2.6,
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