This is likely due to a bug in shuffle file consolidation (which you have enabled) which was hopefully fixed in 1.1 with this patch: https://github.com/apache/spark/commit/78f2af582286b81e6dc9fa9d455ed2b369d933bd
Until 1.0.3 or 1.1 are released, the simplest solution is to disable spark.shuffle.consolidateFiles. (You could also try backporting the fixes yourself if you really need consolidated files.) On Wed, Aug 20, 2014 at 9:28 AM, Silvio Fiorito < silvio.fior...@granturing.com> wrote: > This is a long running Spark Streaming job running in YARN, Spark v1.0.2 > on CDH5. The jobs will run for about 34-37 hours then die due to this > FileNotFoundException. There’s very little CPU or RAM usage, I’m running 2 > x cores, 2 x executors, 4g memory, YARN cluster mode. > > > Here’s the stack trace that I pulled from the History server: > > Job aborted due to stage failure: Task 34331.0:1 failed 4 times, most > recent failure: Exception failure in TID 902905 on host host05: > java.io.FileNotFoundException: > /data02/yarn/nm/usercache/sfiorito/appcache/application_1402494159106_0524/spark-local-20140818181035-079a/29/merged_shuffle_9809_1_0 > (No such file or directory) java.io.RandomAccessFile.open(Native Method) > java.io.RandomAccessFile.<init>(RandomAccessFile.java:241) > org.apache.spark.storage.DiskStore.getBytes(DiskStore.scala:98) > org.apache.spark.storage.DiskStore.getValues(DiskStore.scala:124) > org.apache.spark.storage.BlockManager.getLocalFromDisk(BlockManager.scala:332) > org.apache.spark.storage.BlockFetcherIterator$BasicBlockFetcherIterator$$anonfun$getLocalBlocks$1.apply(BlockFetcherIterator.scala:204) > org.apache.spark.storage.BlockFetcherIterator$BasicBlockFetcherIterator$$anonfun$getLocalBlocks$1.apply(BlockFetcherIterator.scala:203) > scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) > scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47) > org.apache.spark.storage.BlockFetcherIterator$BasicBlockFetcherIterator.getLocalBlocks(BlockFetcherIterator.scala:203) > org.apache.spark.storage.BlockFetcherIterator$BasicBlockFetcherIterator.initialize(BlockFetcherIterator.scala:234) > org.apache.spark.storage.BlockManager.getMultiple(BlockManager.scala:537) > org.apache.spark.BlockStoreShuffleFetcher.fetch(BlockStoreShuffleFetcher.scala:76) > org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$2.apply(CoGroupedRDD.scala:133) > org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$2.apply(CoGroupedRDD.scala:123) > scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:772) > scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33) > scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108) > scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:771) > org.apache.spark.rdd.CoGroupedRDD.compute(CoGroupedRDD.scala:123) > org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) > org.apache.spark.rdd.RDD.iterator(RDD.scala:229) > org.apache.spark.rdd.MappedValuesRDD.compute(MappedValuesRDD.scala:31) > org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) > org.apache.spark.rdd.RDD.iterator(RDD.scala:229) > org.apache.spark.rdd.FlatMappedValuesRDD.compute(FlatMappedValuesRDD.scala:31) > org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) > org.apache.spark.rdd.RDD.iterator(RDD.scala:229) > org.apache.spark.rdd.MappedRDD.compute(MappedRDD.scala:31) > org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) > org.apache.spark.rdd.RDD.iterator(RDD.scala:229) > org.apache.spark.rdd.MappedRDD.compute(MappedRDD.scala:31) > org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) > org.apache.spark.rdd.RDD.iterator(RDD.scala:229) > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35) > org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) > org.apache.spark.rdd.RDD.iterator(RDD.scala:229) > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35) > org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262) > org.apache.spark.rdd.RDD.iterator(RDD.scala:229) > org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:111) > org.apache.spark.scheduler.Task.run(Task.scala:51) > org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:183) > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) > java.lang.Thread.run(Thread.java:744) Driver stacktrace: > >
