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.das1565@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 <mike@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.
>>
>
>
|