Under certain circumstances that I haven't yet been able to isolate, I get
the following error when doing a HQL query using HiveContext (Spark 1.3.1
on Mesos, fine-grained mode). Is this a known problem or should I file a
JIRA for it ?
org.apache.spark.SparkException: Can only zip RDDs with same number of
elements in each partition
at
org.apache.spark.rdd.RDD$$anonfun$zip$1$$anon$1.hasNext(RDD.scala:746)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:327)
at
org.apache.spark.util.random.SamplingUtils$.reservoirSampleAndCount(SamplingUtils.scala:56)
at
org.apache.spark.RangePartitioner$$anonfun$8.apply(Partitioner.scala:259)
at
org.apache.spark.RangePartitioner$$anonfun$8.apply(Partitioner.scala:257)
at org.apache.spark.rdd.RDD$$anonfun$15.apply(RDD.scala:647)
at org.apache.spark.rdd.RDD$$anonfun$15.apply(RDD.scala:647)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:244)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
at org.apache.spark.scheduler.Task.run(Task.scala:64)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203)
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:745)
