在我们的应用程序（Spark 2.0.1）中，这个异常经常出现。
我找不到任何关于此的信息。
可能是什么原因 ？
16/10/27 11:18:24 ERROR LiveListenerBus: Listener EventLoggingListener threw an exception
java.util.ConcurrentModificationException
at java.util.ArrayList$Itr.checkForComodification(ArrayList.java:901)
at java.util.ArrayList$Itr.next(ArrayList.java:851)
at scala.collection.convert.Wrappers$JIteratorWrapper.next(Wrappers.scala:43)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at scala.collection.IterableLike$class.foreach(IterableLike.scala:72)
at scala.collection.AbstractIterable.foreach(Iterable.scala:54)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
at scala.collection.mutable.ListBuffer.$plus$plus$eq(ListBuffer.scala:183)
at scala.collection.mutable.ListBuffer.$plus$plus$eq(ListBuffer.scala:45)
at scala.collection.TraversableLike$class.to(TraversableLike.scala:590)
at scala.collection.AbstractTraversable.to(Traversable.scala:104)
at scala.collection.TraversableOnce$class.toList(TraversableOnce.scala:294)
at scala.collection.AbstractTraversable.toList(Traversable.scala:104)
at org.apache.spark.util.JsonProtocol$.accumValueToJson(JsonProtocol.scala:314)
at org.apache.spark.util.JsonProtocol$$anonfun$accumulableInfoToJson$5.apply(JsonProtocol.scala:291)
at org.apache.spark.util.JsonProtocol$$anonfun$accumulableInfoToJson$5.apply(JsonProtocol.scala:291)
at scala.Option.map(Option.scala:146)
at org.apache.spark.util.JsonProtocol$.accumulableInfoToJson(JsonProtocol.scala:291)
at org.apache.spark.util.JsonProtocol$$anonfun$taskInfoToJson$12.apply(JsonProtocol.scala:283)
at org.apache.spark.util.JsonProtocol$$anonfun$taskInfoToJson$12.apply(JsonProtocol.scala:283)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.immutable.List.foreach(List.scala:381)
at scala.collection.generic.TraversableForwarder$class.foreach(TraversableForwarder.scala:35)
at scala.collection.mutable.ListBuffer.foreach(ListBuffer.scala:45)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
at scala.collection.AbstractTraversable.map(Traversable.scala:104)
at org.apache.spark.util.JsonProtocol$.taskInfoToJson(JsonProtocol.scala:283)
at org.apache.spark.util.JsonProtocol$.taskEndToJson(JsonProtocol.scala:145)
at org.apache.spark.util.JsonProtocol$.sparkEventToJson(JsonProtocol.scala:76)
at org.apache.spark.scheduler.EventLoggingListener.logEvent(EventLoggingListener.scala:137)
at org.apache.spark.scheduler.EventLoggingListener.onTaskEnd(EventLoggingListener.scala:157)
at org.apache.spark.scheduler.SparkListenerBus$class.doPostEvent(SparkListenerBus.scala:45)
at org.apache.spark.scheduler.LiveListenerBus.doPostEvent(LiveListenerBus.scala:36)
at org.apache.spark.scheduler.LiveListenerBus.doPostEvent(LiveListenerBus.scala:36)
at org.apache.spark.util.ListenerBus$class.postToAll(ListenerBus.scala:63)
at org.apache.spark.scheduler.LiveListenerBus.postToAll(LiveListenerBus.scala:36)
at org.apache.spark.scheduler.LiveListenerBus$$anon$1$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(LiveListenerBus.scala:94)
at org.apache.spark.scheduler.LiveListenerBus$$anon$1$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply(LiveListenerBus.scala:79)
at org.apache.spark.scheduler.LiveListenerBus$$anon$1$$anonfun$run$1$$anonfun$apply$mcV$sp$1.apply(LiveListenerBus.scala:79)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
at org.apache.spark.scheduler.LiveListenerBus$$anon$1$$anonfun$run$1.apply$mcV$sp(LiveListenerBus.scala:78)
at org.apache.spark.util.Utils$.tryOrStopSparkContext(Utils.scala:1249)
at org.apache.spark.scheduler.LiveListenerBus$$anon$1.run(LiveListenerBus.scala:77)
EDIT:另请注意，我们的应用程序是长时间运行的，为了从可能失败的 Spark 上下文中恢复，我们在两个“作业”之间使用 SparkBuilder.getOrCreate() 方法。这会扰乱听众吗？
这是一个已知问题Spark 2.0.1 (SPARK-17816 https://issues.apache.org/jira/browse/SPARK-17816）并将被修复Spark 2.0.2/2.1.0 (相关拉取请求 https://github.com/apache/spark/pull/15425).
无需等待即可摆脱异常Spark 2.0.2/2.1.0，克隆最新的、不稳定的 Spark 版本 https://github.com/apache/spark/tree/branch-2.0 and 手动构建 apache-spark http://spark.apache.org/docs/latest/programming-guide.html.
Update:他们释放了Spark 2.0.2 http://spark.apache.org/downloads.html!
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