Question

我在群集模式下在纱线上运行火花作业。该作业从kafka直接流中获取消息。我每30秒使用一次广播变量和检查点。当我第一次开始工作时它运行正常没有任何问题。如果我杀死了这个工作并重新启动它，它会在收到来自kafka的消息时抛出执行器中的异常：

java.io.IOException: org.apache.spark.SparkException: Failed to get broadcast_1_piece0 of broadcast_1
    at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:1178)
    at org.apache.spark.broadcast.TorrentBroadcast.readBroadcastBlock(TorrentBroadcast.scala:165)
    at org.apache.spark.broadcast.TorrentBroadcast._value$lzycompute(TorrentBroadcast.scala:64)
    at org.apache.spark.broadcast.TorrentBroadcast._value(TorrentBroadcast.scala:64)
    at org.apache.spark.broadcast.TorrentBroadcast.getValue(TorrentBroadcast.scala:88)
    at org.apache.spark.broadcast.Broadcast.value(Broadcast.scala:70)
    at net.juniper.spark.stream.LogDataStreamProcessor$2.call(LogDataStreamProcessor.java:177)
    at net.juniper.spark.stream.LogDataStreamProcessor$2.call(LogDataStreamProcessor.java:1)
    at org.apache.spark.streaming.api.java.JavaDStreamLike$$anonfun$fn$1$1.apply(JavaDStreamLike.scala:172)
    at org.apache.spark.streaming.api.java.JavaDStreamLike$$anonfun$fn$1$1.apply(JavaDStreamLike.scala:172)
    at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
    at scala.collection.Iterator$$anon$14.hasNext(Iterator.scala:388)
    at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:308)
    at scala.collection.Iterator$class.foreach(Iterator.scala:727)
    at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
    at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
    at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
    at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
    at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
    at scala.collection.AbstractIterator.to(Iterator.scala:1157)
    at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
    at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
    at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
    at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
    at org.apache.spark.rdd.RDD$$anonfun$take$1$$anonfun$28.apply(RDD.scala:1298)
    at org.apache.spark.rdd.RDD$$anonfun$take$1$$anonfun$28.apply(RDD.scala:1298)
    at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1850)
    at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1850)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
    at org.apache.spark.scheduler.Task.run(Task.scala:88)
    at org.apache.spark.executor.Executor$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)

有谁知道如何解决此错误？

Spark版本：1.5.0

CDH 5.5.1

Answer 1

当遇到只有第一次运行的问题时，它总是导致检查点数据的循环问题。此外，只有在需要检查的情况下才会使用检查点，这是来自kafka的第一条消息。我建议你检查你的工作是否确实已经死了，也就是说，进程仍然可以在执行它的机器上运行。尝试运行一个简单的ps -fe，看看是否还在运行。如果有2个进程试图使用相同的检查点文件夹，它将始终失败。希望这有帮助

无法在Spark Streaming作业中获得broadcast_1的broadcast_1_piece0

1 个答案: