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Posted to issues@spark.apache.org by "Sean Owen (JIRA)" <ji...@apache.org> on 2016/07/13 17:43:20 UTC
[jira] [Resolved] (SPARK-16513) Spark executor deadlocks itself in
memory management
[ https://issues.apache.org/jira/browse/SPARK-16513?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Sean Owen resolved SPARK-16513.
-------------------------------
Resolution: Duplicate
I am pretty sure it's a duplicate of https://issues.apache.org/jira/browse/SPARK-13566 then, fixed in 1.6.2
> Spark executor deadlocks itself in memory management
> ----------------------------------------------------
>
> Key: SPARK-16513
> URL: https://issues.apache.org/jira/browse/SPARK-16513
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 1.6.1
> Reporter: Steven Lowenthal
> Attachments: driver.stack.txt, hung.executor.stack.txt, screenshot-1.png, sparklog
>
>
> I have a spark streaming application which uses stateful RDDs (2 to be exact), but a given job only uses one. The last part of the executor stderr log is enclosed. There is no output in stdout. There are 3 concurrent Spark tasks on the executor deadlocked as follows:
> org.apache.spark.storage.BlockManager.dropFromMemory(BlockManager.scala:1029)
> org.apache.spark.storage.BlockManager.dropFromMemory(BlockManager.scala:1009)
> org.apache.spark.storage.MemoryStore$$anonfun$evictBlocksToFreeSpace$2.apply(MemoryStore.scala:460)
> org.apache.spark.storage.MemoryStore$$anonfun$evictBlocksToFreeSpace$2.apply(MemoryStore.scala:449)
> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
> org.apache.spark.storage.MemoryStore.evictBlocksToFreeSpace(MemoryStore.scala:449)
> org.apache.spark.memory.StorageMemoryPool.acquireMemory(StorageMemoryPool.scala:89)
> org.apache.spark.memory.StorageMemoryPool.acquireMemory(StorageMemoryPool.scala:69)
> org.apache.spark.memory.UnifiedMemoryManager.acquireStorageMemory(UnifiedMemoryManager.scala:155)
> org.apache.spark.memory.UnifiedMemoryManager.acquireUnrollMemory(UnifiedMemoryManager.scala:162)
> org.apache.spark.storage.MemoryStore.reserveUnrollMemoryForThisTask(MemoryStore.scala:493)
> org.apache.spark.storage.MemoryStore.unrollSafely(MemoryStore.scala:291)
> org.apache.spark.CacheManager.putInBlockManager(CacheManager.scala:171)
> org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:78)
> org.apache.spark.rdd.RDD.iterator(RDD.scala:268)
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
> org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
> org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
> org.apache.spark.scheduler.Task.run(Task.scala:89)
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> java.lang.Thread.run(Thread.java:745)
> org.apache.spark.storage.MemoryStore.tryToPut(MemoryStore.scala:379)
> org.apache.spark.storage.MemoryStore.tryToPut(MemoryStore.scala:346)
> org.apache.spark.storage.MemoryStore.putArray(MemoryStore.scala:133)
> org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:800)
> org.apache.spark.storage.BlockManager.putArray(BlockManager.scala:676)
> org.apache.spark.CacheManager.putInBlockManager(CacheManager.scala:175)
> org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:78)
> org.apache.spark.rdd.RDD.iterator(RDD.scala:268)
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
> org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
> org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
> org.apache.spark.scheduler.Task.run(Task.scala:89)
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> java.lang.Thread.run(Thread.java:745)
> org.apache.spark.memory.MemoryManager.releaseExecutionMemory(MemoryManager.scala:120)
> org.apache.spark.memory.TaskMemoryManager.releaseExecutionMemory(TaskMemoryManager.java:201)
> org.apache.spark.util.collection.Spillable$class.releaseMemory(Spillable.scala:111)
> org.apache.spark.util.collection.ExternalSorter.releaseMemory(ExternalSorter.scala:89)
> org.apache.spark.util.collection.ExternalSorter.stop(ExternalSorter.scala:694)
> org.apache.spark.shuffle.sort.SortShuffleWriter.stop(SortShuffleWriter.scala:95)
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:74)
> org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
> org.apache.spark.scheduler.Task.run(Task.scala:89)
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> java.lang.Thread.run(Thread.java:745)
> This is the log file exerpt:
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