我有一个流作业，它读取kafka（@1min批处理），并在一些操作之后将其发布到http端点。每隔几个小时，它就会陷入“处理”阶段，然后开始排队作业：

在检查正在运行的“executors”（在appui页面中）之后，我发现6个executors中只有1个显示了2个“活动任务”。

在为此执行线程转储时，它显示了“executor task launch worker”线程池（源）的2个线程。这些线程都出现了相同的错误：

完全可读错误：

java.lang.Object.wait(Native Method)
java.lang.Object.wait(Object.java:502)
java.net.InetAddress.checkLookupTable(InetAddress.java:1393)
java.net.InetAddress.getAddressesFromNameService(InetAddress.java:1310)
java.net.InetAddress.getAllByName0(InetAddress.java:1276)
java.net.InetAddress.getAllByName(InetAddress.java:1192)
java.net.InetAddress.getAllByName(InetAddress.java:1126)
java.net.InetAddress.getByName(InetAddress.java:1076)
java.net.InetSocketAddress.<init>(InetSocketAddress.java:220)
kafka.network.BlockingChannel.liftedTree1$1(BlockingChannel.scala:59)
kafka.network.BlockingChannel.connect(BlockingChannel.scala:49)
kafka.consumer.SimpleConsumer.connect(SimpleConsumer.scala:44)
kafka.consumer.SimpleConsumer.getOrMakeConnection(SimpleConsumer.scala:151)
kafka.consumer.SimpleConsumer.liftedTree1$1(SimpleConsumer.scala:69)
kafka.consumer.SimpleConsumer.kafka$consumer$SimpleConsumer$$sendRequest(SimpleConsumer.scala:68)
kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(SimpleConsumer.scala:112)
kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply(SimpleConsumer.scala:112)
kafka.consumer.SimpleConsumer$$anonfun$fetch$1$$anonfun$apply$mcV$sp$1.apply(SimpleConsumer.scala:112)
kafka.metrics.KafkaTimer.time(KafkaTimer.scala:33)
kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply$mcV$sp(SimpleConsumer.scala:111)
kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply(SimpleConsumer.scala:111)
kafka.consumer.SimpleConsumer$$anonfun$fetch$1.apply(SimpleConsumer.scala:111)
kafka.metrics.KafkaTimer.time(KafkaTimer.scala:33)
kafka.consumer.SimpleConsumer.fetch(SimpleConsumer.scala:110)
org.apache.spark.streaming.kafka.KafkaRDD$KafkaRDDIterator.fetchBatch(KafkaRDD.scala:193)
org.apache.spark.streaming.kafka.KafkaRDD$KafkaRDDIterator.getNext(KafkaRDD.scala:209)
org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:461)
scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
org.apache.spark.shuffle.sort.UnsafeShuffleWriter.write(UnsafeShuffleWriter.java:161)
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47)
org.apache.spark.scheduler.Task.run(Task.scala:85)
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
java.lang.Thread.run(Thread.java:745)

这似乎是一个jdk错误，必须在jdk 7中修复-我确保我使用的是“1.8.0\u 101（oracle corporation）”。我尝试在命令行中添加以下内容（如这里所建议的），但没有解决问题：

-Djava.net.preferIPv4Stack=true -Dnetworkaddress.cache.ttl=60

有人对调试/修复这个问题有什么想法吗？

• 编辑：重命名问题以删除混淆的jdk原因