Details
Major Description
The following code example:
case class Foo(bar: Option[String]) val ds = List(Foo(Some("bar"))).toDS val result = ds.flatMap(_.bar).distinct result.rdd.isEmpty
Produces the following stacktrace
[info] org.apache.spark.SparkException: Job aborted due to stage failure: Task 42 in stage 7.0 failed 1 times, most recent failure: Lost task 42.0 in stage 7.0 (TID 125, localhost, executor driver): org.apache.spark.SparkException: Managed memory leak detected; size = 16777216 bytes, TID = 125 [info] at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:358) [info] at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) [info] at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) [info] at java.lang.Thread.run(Thread.java:748) [info] [info] Driver stacktrace: [info] at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1602) [info] at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1590) [info] at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1589) [info] at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) [info] at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) [info] at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1589) [info] at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831) [info] at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831) [info] at scala.Option.foreach(Option.scala:257) [info] at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:831) [info] at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1823) [info] at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1772) [info] at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1761) [info] at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) [info] at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642) [info] at org.apache.spark.SparkContext.runJob(SparkContext.scala:2034) [info] at org.apache.spark.SparkContext.runJob(SparkContext.scala:2055) [info] at org.apache.spark.SparkContext.runJob(SparkContext.scala:2074) [info] at org.apache.spark.rdd.RDD$$anonfun$take$1.apply(RDD.scala:1358) [info] at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) [info] at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) [info] at org.apache.spark.rdd.RDD.withScope(RDD.scala:363) [info] at org.apache.spark.rdd.RDD.take(RDD.scala:1331) [info] at org.apache.spark.rdd.RDD$$anonfun$isEmpty$1.apply$mcZ$sp(RDD.scala:1466) [info] at org.apache.spark.rdd.RDD$$anonfun$isEmpty$1.apply(RDD.scala:1466) [info] at org.apache.spark.rdd.RDD$$anonfun$isEmpty$1.apply(RDD.scala:1466) [info] at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) [info] at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112) [info] at org.apache.spark.rdd.RDD.withScope(RDD.scala:363) [info] at org.apache.spark.rdd.RDD.isEmpty(RDD.scala:1465)
The code example doesn't produce any error when `distinct` function is not called.
