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https://issues.apache.org/jira/browse/SPARK-1712?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Matei Zaharia updated SPARK-1712:
---------------------------------
Priority: Major (was: Blocker)
> ParallelCollectionRDD operations hanging forever without any error messages
> ----------------------------------------------------------------------------
>
> Key: SPARK-1712
> URL: https://issues.apache.org/jira/browse/SPARK-1712
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 0.9.0
> Environment: Linux Ubuntu 14.04, a single spark node; standalone mode.
> Reporter: Piotr Kołaczkowski
> Assignee: Guoqiang Li
> Attachments: executor.jstack.txt, master.jstack.txt, repl.jstack.txt,
> spark-hang.png, worker.jstack.txt
>
>
> conf/spark-defaults.conf
> {code}
> spark.akka.frameSize 5
> spark.default.parallelism 1
> {code}
> {noformat}
> scala> val collection = (1 to 1000000).map(i => ("foo" + i, i)).toVector
> collection: Vector[(String, Int)] = Vector((foo1,1), (foo2,2), (foo3,3),
> (foo4,4), (foo5,5), (foo6,6), (foo7,7), (foo8,8), (foo9,9), (foo10,10),
> (foo11,11), (foo12,12), (foo13,13), (foo14,14), (foo15,15), (foo16,16),
> (foo17,17), (foo18,18), (foo19,19), (foo20,20), (foo21,21), (foo22,22),
> (foo23,23), (foo24,24), (foo25,25), (foo26,26), (foo27,27), (foo28,28),
> (foo29,29), (foo30,30), (foo31,31), (foo32,32), (foo33,33), (foo34,34),
> (foo35,35), (foo36,36), (foo37,37), (foo38,38), (foo39,39), (foo40,40),
> (foo41,41), (foo42,42), (foo43,43), (foo44,44), (foo45,45), (foo46,46),
> (foo47,47), (foo48,48), (foo49,49), (foo50,50), (foo51,51), (foo52,52),
> (foo53,53), (foo54,54), (foo55,55), (foo56,56), (foo57,57), (foo58,58),
> (foo59,59), (foo60,60), (foo61,61), (foo62,62), (foo63,63), (foo64,64),
> (foo...
> scala> val rdd = sc.parallelize(collection)
> rdd: org.apache.spark.rdd.RDD[(String, Int)] = ParallelCollectionRDD[0] at
> parallelize at <console>:24
> scala> rdd.first
> res4: (String, Int) = (foo1,1)
> scala> rdd.map(_._2).sum
> // nothing happens
> {noformat}
> CPU and I/O idle.
> Memory usage reported by JVM, after manually triggered GC:
> repl: 216 MB / 2 GB
> executor: 67 MB / 2 GB
> worker: 6 MB / 128 MB
> master: 6 MB / 128 MB
> No errors found in worker's stderr/stdout.
> It works fine with 700,000 elements and then it takes about 1 second to
> process the request and calculate the sum. With 700,000 items the spark
> executor memory doesn't even exceed 300 MB out of 2GB available. It fails
> with 800,000 items.
> Multiple parralelized collections of size 700,000 items at the same time in
> the same session work fine.
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