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From Chen Song <chen.song...@gmail.com>
Subject FetchFailedException during shuffle
Date Fri, 27 Mar 2015 01:45:17 GMT
Using spark 1.3.0 on cdh5.1.0, I was running a fetch failed exception.

I searched in this email list but not found anything like this reported.
What could be the reason for the error?

org.apache.spark.shuffle.FetchFailedException: [EMPTY_INPUT] Cannot
decompress empty stream
	at org.apache.spark.shuffle.hash.BlockStoreShuffleFetcher$.org$apache$spark$shuffle$hash$BlockStoreShuffleFetcher$$unpackBlock$1(BlockStoreShuffleFetcher.scala:67)
	at org.apache.spark.shuffle.hash.BlockStoreShuffleFetcher$$anonfun$3.apply(BlockStoreShuffleFetcher.scala:83)
	at org.apache.spark.shuffle.hash.BlockStoreShuffleFetcher$$anonfun$3.apply(BlockStoreShuffleFetcher.scala:83)
	at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
	at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:32)
	at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
	at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
	at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
	at org.apache.spark.util.collection.ExternalAppendOnlyMap.insertAll(ExternalAppendOnlyMap.scala:125)
	at org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$5.apply(CoGroupedRDD.scala:160)
	at org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$5.apply(CoGroupedRDD.scala:159)
	at scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:772)
	at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
	at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
	at scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:771)
	at org.apache.spark.rdd.CoGroupedRDD.compute(CoGroupedRDD.scala:159)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
	at org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$2.apply(CoGroupedRDD.scala:130)
	at org.apache.spark.rdd.CoGroupedRDD$$anonfun$compute$2.apply(CoGroupedRDD.scala:127)
	at scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:772)
	at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
	at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
	at scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:771)
	at org.apache.spark.rdd.CoGroupedRDD.compute(CoGroupedRDD.scala:127)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
	at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
	at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
	at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
	at org.apache.spark.scheduler.Task.run(Task.scala:64)
	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
	at java.lang.Thread.run(Thread.java:745)
Caused by: org.xerial.snappy.SnappyIOException: [EMPTY_INPUT] Cannot
decompress empty stream
	at org.xerial.snappy.SnappyInputStream.readHeader(SnappyInputStream.java:88)
	at org.xerial.snappy.SnappyInputStream.<init>(SnappyInputStream.java:58)
	at org.apache.spark.io.SnappyCompressionCodec.compressedInputStream(CompressionCodec.scala:160)
	at org.apache.spark.storage.BlockManager.wrapForCompression(BlockManager.scala:1165)
	at org.apache.spark.storage.ShuffleBlockFetcherIterator$$anonfun$4.apply(ShuffleBlockFetcherIterator.scala:301)
	at org.apache.spark.storage.ShuffleBlockFetcherIterator$$anonfun$4.apply(ShuffleBlockFetcherIterator.scala:300)
	at scala.util.Success$$anonfun$map$1.apply(Try.scala:206)
	at scala.util.Try$.apply(Try.scala:161)
	at scala.util.Success.map(Try.scala:206)
	at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:300)
	at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:53)
	... 60 more


----

Chen

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