我正在使用mesos集群来部署spark job（客户端模式）。我有三台服务器，能够运行spark工作。但是，过了一会儿（几天），我收到了错误：
5/11/03 19:55:50 ERROR Executor: Managed memory leak detected; size = 33554432 bytes, TID = 387939
15/11/03 19:55:50 ERROR Executor: Exception in task 2.1 in stage 6534.0 (TID 387939)
java.io.FileNotFoundException: /tmp/blockmgr-3acec504-4a55-4aa8-a3e5-dda97ce5d055/03/temp_shuffle_cb37f147-c055-4014-a6ae-fd505cb49f57 (Too many open files)
at java.io.FileOutputStream.open(Native Method)
at java.io.FileOutputStream.<init>(FileOutputStream.java:221)
at org.apache.spark.storage.DiskBlockObjectWriter.open(DiskBlockObjectWriter.scala:88)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.insertAll(BypassMergeSortShuffleWriter.java:110)
at org.apache.spark.shuffle.sort.SortShuffleWriter.write(SortShuffleWriter.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:88)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
现在，它会导致所有流式传输批次排队并显示为＆＃34;处理＆＃34; （4042 /流/）。在手动重新启动spark作业并再次重新提交之前，他们都无法继续。
我的火花工作只是从kafka读取数据并对mongo进行了一些更新（有相当多的更新查询通过;但我将火花流持续时间配置为大约5分钟;所以它不应该导致问题）
过了一会儿，因为没有工作能够成功; spark-kafka读者开始显示错误：
ERROR Executor: Exception in task 5.3 in stage 7561.0 (TID 392220)
org.apache.spark.SparkException: Couldn't connect to leader for topic bid_inventory 9: java.nio.channels.ClosedChannelException
java.nio.channels.ClosedChannelException
java.nio.channels.ClosedChannelException
at org.apache.spark.streaming.kafka.KafkaRDD$KafkaRDDIterator$$anonfun$connectLeader$1.apply(KafkaRDD.scala:164)
at org.apache.spark.streaming.kafka.KafkaRDD$KafkaRDDIterator$$anonfun$connectLeader$1.apply(KafkaRDD.scala:164)
但是一旦重新启动，一切都会正常运转。
任何人都知道它为什么会发生？感谢。