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. >
