Could you try to turn on the external shuffle service?
spark.shuffle.service.enable= true
On 21.2.2015. 17:50, Corey Nolet wrote:
I'm experiencing the same issue. Upon closer inspection I'm noticing
that executors are being lost as well. Thing is, I can't figure out
how they are dying. I'm using MEMORY_AND_DISK_SER and i've got over
1.3TB of memory allocated for the application. I was thinking perhaps
it was possible that a single executor was getting a single or a
couple large partitions but shouldn't the disk persistence kick in at
that point?
On Sat, Feb 21, 2015 at 11:20 AM, Anders Arpteg <arp...@spotify.com
<mailto:arp...@spotify.com>> wrote:
For large jobs, the following error message is shown that seems to
indicate that shuffle files for some reason are missing. It's a
rather large job with many partitions. If the data size is
reduced, the problem disappears. I'm running a build from Spark
master post 1.2 (build at 2015-01-16) and running on Yarn 2.2. Any
idea of how to resolve this problem?
User class threw exception: Job aborted due to stage failure: Task
450 in stage 450.1 failed 4 times, most recent failure: Lost task
450.3 in stage 450.1 (TID 167370,
lon4-hadoopslave-b77.lon4.spotify.net
<http://lon4-hadoopslave-b77.lon4.spotify.net>):
java.io.FileNotFoundException:
/disk/hd06/yarn/local/usercache/arpteg/appcache/application_1424333823218_21217/spark-local-20150221154811-998c/03/rdd_675_450
(No such file or directory)
at java.io.FileOutputStream.open(Native Method)
at java.io.FileOutputStream.(FileOutputStream.java:221)
at java.io.FileOutputStream.(FileOutputStream.java:171)
at org.apache.spark.storage.DiskStore.putIterator(DiskStore.scala:76)
at
org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:786)
at
org.apache.spark.storage.BlockManager.putIterator(BlockManager.scala:637)
at
org.apache.spark.CacheManager.putInBlockManager(CacheManager.scala:149)
at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:74)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:264)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:231)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:68)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:64)
at
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:192)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
TIA,
Anders
