CheckpointRDD has different number of partitions than original RDD

[Paul Mogren]

Hello, Spark community!  My name is Paul. I am a Spark newbie, evaluating 
version 0.9.0 without any Hadoop at all, and need some help. I run into the 
following error with the StatefulNetworkWordCount example (and similarly in my 
prototype app, when I use the updateStateByKey operation).  I get this when 
running against my small cluster, but not (so far) against local[2].

61904 [spark-akka.actor.default-dispatcher-2] ERROR 
org.apache.spark.streaming.scheduler.JobScheduler - Error running job streaming 
job 1396905956000 ms.0
org.apache.spark.SparkException: Checkpoint RDD CheckpointRDD[310] at take at 
DStream.scala:586(0) has different number of partitions than original RDD 
MapPartitionsRDD[309] at mapPartitions at StateDStream.scala:66(2)
        at 
org.apache.spark.rdd.RDDCheckpointData.doCheckpoint(RDDCheckpointData.scala:99)
        at org.apache.spark.rdd.RDD.doCheckpoint(RDD.scala:989)
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:855)
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:870)
        at org.apache.spark.SparkContext.runJob(SparkContext.scala:884)
        at org.apache.spark.rdd.RDD.take(RDD.scala:844)
        at 
org.apache.spark.streaming.dstream.DStream$$anonfun$foreachFunc$2$1.apply(DStream.scala:586)
        at 
org.apache.spark.streaming.dstream.DStream$$anonfun$foreachFunc$2$1.apply(DStream.scala:585)
        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$JobHandler.run(JobScheduler.scala:155)
        at 
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
        at 
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
        at java.lang.Thread.run(Thread.java:744)


Please let me know what other information would be helpful; I didn't find any 
question submission guidelines.

Thanks,
Paul