I think I know what is going on! This probably a race condition in the DAGScheduler. I have added a JIRA for this. The fix is not trivial though.
https://issues.apache.org/jira/browse/SPARK-2002 A "not-so-good" workaround for now would be not use coalesced RDD, which is avoids the race condition. TD On Tue, Jun 3, 2014 at 10:09 AM, Michael Chang <m...@tellapart.com> wrote: > I only had the warning level logs, unfortunately. There were no other > references of 32855 (except a repeated stack trace, I believe). I'm using > Spark 0.9.1 > > > On Mon, Jun 2, 2014 at 5:50 PM, Tathagata Das <tathagata.das1...@gmail.com > > wrote: > >> Do you have the info level logs of the application? Can you grep the >> value "32855" to find any references to it? Also what version of the >> Spark are you using (so that I can match the stack trace, does not seem to >> match with Spark 1.0)? >> >> TD >> >> >> On Mon, Jun 2, 2014 at 3:27 PM, Michael Chang <m...@tellapart.com> wrote: >> >>> Hi all, >>> >>> Seeing a random exception kill my spark streaming job. Here's a stack >>> trace: >>> >>> java.util.NoSuchElementException: key not found: 32855 >>> at scala.collection.MapLike$class.default(MapLike.scala:228) >>> at scala.collection.AbstractMap.default(Map.scala:58) >>> at scala.collection.mutable.HashMap.apply(HashMap.scala:64) >>> at >>> org.apache.spark.scheduler.DAGScheduler.getCacheLocs(DAGScheduler.scala:211) >>> at >>> org.apache.spark.scheduler.DAGScheduler.getPreferredLocs(DAGScheduler.scala:1072) >>> at >>> org.apache.spark.SparkContext.getPreferredLocs(SparkContext.scala:716) >>> at >>> org.apache.spark.rdd.PartitionCoalescer.currPrefLocs(CoalescedRDD.scala:172) >>> at >>> org.apache.spark.rdd.PartitionCoalescer$LocationIterator$$anonfun$4$$anonfun$apply$2.apply(CoalescedRDD.scala:189) >>> at >>> org.apache.spark.rdd.PartitionCoalescer$LocationIterator$$anonfun$4$$anonfun$apply$2.apply(CoalescedRDD.scala:188) >>> at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371) >>> at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:351) >>> at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:350) >>> at >>> org.apache.spark.rdd.PartitionCoalescer$LocationIterator.<init>(CoalescedRDD.scala:183) >>> at >>> org.apache.spark.rdd.PartitionCoalescer.setupGroups(CoalescedRDD.scala:234) >>> at >>> org.apache.spark.rdd.PartitionCoalescer.run(CoalescedRDD.scala:333) >>> at >>> org.apache.spark.rdd.CoalescedRDD.getPartitions(CoalescedRDD.scala:81) >>> at >>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:207) >>> at >>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:205) >>> at scala.Option.getOrElse(Option.scala:120) >>> at org.apache.spark.rdd.RDD.partitions(RDD.scala:205) >>> at >>> org.apache.spark.rdd.MappedRDD.getPartitions(MappedRDD.scala:28) >>> at >>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:207) >>> at >>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:205) >>> at scala.Option.getOrElse(Option.scala:120) >>> at org.apache.spark.rdd.RDD.partitions(RDD.scala:205) >>> at >>> org.apache.spark.rdd.MappedRDD.getPartitions(MappedRDD.scala:28) >>> at >>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:207) >>> at >>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:205) >>> at scala.Option.getOrElse(Option.scala:120) >>> at org.apache.spark.rdd.RDD.partitions(RDD.scala:205) >>> at >>> org.apache.spark.rdd.FlatMappedRDD.getPartitions(FlatMappedRDD.scala:30) >>> at >>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:207) >>> at >>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:205) >>> at scala.Option.getOrElse(Option.scala:120) >>> at org.apache.spark.rdd.RDD.partitions(RDD.scala:205) >>> at >>> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:31) >>> at >>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:207) >>> at >>> org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:205) >>> at scala.Option.getOrElse(Option.scala:120) >>> at org.apache.spark.rdd.RDD.partitions(RDD.scala:205) >>> at org.apache.spark.rdd.RDD.take(RDD.scala:830) >>> at >>> org.apache.spark.api.java.JavaRDDLike$class.take(JavaRDDLike.scala:337) >>> at org.apache.spark.api.java.JavaRDD.take(JavaRDD.scala:27) >>> at >>> com.tellapart.manifolds.spark.ManifoldsUtil$PersistToKafkaFunction.call(ManifoldsUtil.java:87) >>> at >>> com.tellapart.manifolds.spark.ManifoldsUtil$PersistToKafkaFunction.call(ManifoldsUtil.java:53) >>> at >>> org.apache.spark.streaming.api.java.JavaDStreamLike$$anonfun$foreachRDD$1.apply(JavaDStreamLike.scala:270) >>> at >>> org.apache.spark.streaming.api.java.JavaDStreamLike$$anonfun$foreachRDD$1.apply(JavaDStreamLike.scala:270) >>> at >>> org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1.apply(DStream.scala:520) >>> at >>> org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1.apply(DStream.scala:520) >>> at >>> org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply$mcV$sp(ForEachDStream.scala:41) >>> at >>> org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:40) >>> at >>> org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:40) >>> at scala.util.Try$.apply(Try.scala:161) >>> at org.apache.spark.streaming.scheduler.Job.run(Job.scala:32) >>> at >>> org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:155) >>> at >>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145) >>> at >>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615) >>> at java.lang.Thread.run(Thread.java:744) >>> >>> It doesn't seem to happen consistently, but I have no idea causes it. >>> Has anyone seen this before? The PersistToKafkaFunction here is just >>> trying to write the elements in a RDD to a Kafka topic. >>> >> >> >
