Does it work as expected with smaller batch or smaller load? Could it be that 
it's accumulating too many events over 3 minutes?

You could also try increasing the parallelism via repartition to ensure smaller 
tasks that can safely fit in working memory.

Sent from my iPhone

> On 28 Oct 2015, at 17:45, Afshartous, Nick <nafshart...@turbine.com> wrote:
> 
> 
> Hi, we are load testing our Spark 1.3 streaming (reading from Kafka)  job and 
> seeing a problem.  This is running in AWS/Yarn and the streaming batch 
> interval is set to 3 minutes and this is a ten node cluster.
> 
> Testing at 30,000 events per second we are seeing the streaming job get stuck 
> (stack trace below) for over an hour.
> 
> Thanks on any insights or suggestions.
> --
>      Nick
> 
> org.apache.spark.streaming.api.java.AbstractJavaDStreamLike.mapPartitionsToPair(JavaDStreamLike.scala:43)
> com.wb.analytics.spark.services.streaming.drivers.StreamingKafkaConsumerDriver.runStream(StreamingKafkaConsumerDriver.java:125)
> com.wb.analytics.spark.services.streaming.drivers.StreamingKafkaConsumerDriver.main(StreamingKafkaConsumerDriver.java:71)
> sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> java.lang.reflect.Method.invoke(Method.java:606)
> org.apache.spark.deploy.yarn.ApplicationMaster$$anon$2.run(ApplicationMaster.scala:480)
> 
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