[SPARK-13398][STREAMING] Move away from thread pool task support to forkjoin #11423
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… that is the number of objects kept in memory.
…upport-java-forkjoin
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Test build #52165 has finished for PR 11423 at commit
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The HiveComptability test seems likely unrelated (happened in another unrelated PR at the same time). Will double check in the morning. |
| /** | ||
| * Extend ForkJoinWorkerThread so we can instantiate it. | ||
| */ | ||
| class SparkForkJoinWorkerThread(pool: ForkJoinPool) extends ForkJoinWorkerThread(pool) { |
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Comments are great of course -- javadoc won't do anything here. It could be a line comment.
I think you might be able to collapse most of this with anonymous classes:
val factory = new ForkJoinWorkerThreadFactory {
override def newThread(pool: ForkJoinPool) =
new ForkJoinWorkerThread(pool) {
setName(prefix + "-" + super.getName)
}
}
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Test build #52201 has finished for PR 11423 at commit
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Jenkins, retest this please |
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Test build #52239 has finished for PR 11423 at commit
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I'll just switch this to use the Scala one for now (this code path does the correct thing in 2.12 but in 2.11 using the Java pool also reports system parallelism). |
….11 necessary for correct concurrency report)
…upport-java-forkjoin
holdenk
changed the title
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Test build #52420 has finished for PR 11423 at commit
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LGTM |
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Merged to master |
roygao94
pushed a commit
to roygao94/spark
that referenced
this pull request
Mar 22, 2016
…orkjoin ## What changes were proposed in this pull request? Remove old deprecated ThreadPoolExecutor and replace with ExecutionContext using a ForkJoinPool. The downside of this is that scala's ForkJoinPool doesn't give us a way to specify the thread pool name (and is a wrapper of Java's in 2.12) except by providing a custom factory. Note that we can't use Java's ForkJoinPool directly in Scala 2.11 since it uses a ExecutionContext which reports system parallelism. One other implicit change that happens is the old ExecutionContext would have reported a different default parallelism since it used system parallelism rather than threadpool parallelism (this was likely not intended but also likely not a huge difference). The previous version of this PR attempted to use an execution context constructed on the ThreadPool (but not the deprecated ThreadPoolExecutor class) so as to keep the ability to have human readable named threads but this reported system parallelism. ## How was this patch tested? unit tests: streaming/testOnly org.apache.spark.streaming.util.* Author: Holden Karau <[email protected]> Closes apache#11423 from holdenk/SPARK-13398-move-away-from-ThreadPoolTaskSupport-java-forkjoin.
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What changes were proposed in this pull request?
Remove old deprecated ThreadPoolExecutor and replace with ExecutionContext using a ForkJoinPool. The downside of this is that scala's ForkJoinPool doesn't give us a way to specify the thread pool name (and is a wrapper of Java's in 2.12) except by providing a custom factory. Note that we can't use Java's ForkJoinPool directly in Scala 2.11 since it uses a ExecutionContext which reports system parallelism. One other implicit change that happens is the old ExecutionContext would have reported a different default parallelism since it used system parallelism rather than threadpool parallelism (this was likely not intended but also likely not a huge difference).
The previous version of this PR attempted to use an execution context constructed on the ThreadPool (but not the deprecated ThreadPoolExecutor class) so as to keep the ability to have human readable named threads but this reported system parallelism.
How was this patch tested?
unit tests: streaming/testOnly org.apache.spark.streaming.util.*