[
https://issues.apache.org/jira/browse/SPARK-5744?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Sean Owen resolved SPARK-5744.
------------------------------
Resolution: Fixed
Fix Version/s: 1.4.0
Issue resolved by pull request 4698
[https://github.com/apache/spark/pull/4698]
> RDD.isEmpty / take fails for (empty) RDD of Nothing
> ---------------------------------------------------
>
> Key: SPARK-5744
> URL: https://issues.apache.org/jira/browse/SPARK-5744
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Reporter: Tobias Bertelsen
> Assignee: Tobias Bertelsen
> Priority: Minor
> Fix For: 1.4.0
>
> Original Estimate: 0h
> Remaining Estimate: 0h
>
> The implementation of {{RDD.isEmpty()}} fails if there is empty partitions.
> It was introduce by https://github.com/apache/spark/pull/4074
> Example:
> {code}
> sc.parallelize(Seq(), 1).isEmpty()
> {code}
> The above code throws an exception like this:
> {code}
> org.apache.spark.SparkDriverExecutionException: Execution error
> at
> org.apache.spark.scheduler.DAGScheduler.handleTaskCompletion(DAGScheduler.scala:977)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1374)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1338)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> Cause: java.lang.ArrayStoreException: [Ljava.lang.Object;
> at scala.runtime.ScalaRunTime$.array_update(ScalaRunTime.scala:88)
> at
> org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1466)
> at
> org.apache.spark.SparkContext$$anonfun$runJob$4.apply(SparkContext.scala:1466)
> at org.apache.spark.scheduler.JobWaiter.taskSucceeded(JobWaiter.scala:56)
> at
> org.apache.spark.scheduler.DAGScheduler.handleTaskCompletion(DAGScheduler.scala:973)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1374)
> at
> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1338)
> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
> {code}
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