ERROR Utils:线程SparkListenerBus中的未捕获异常

Question

我尝试用Apache Spark执行简单的项目.这是我的代码SimpleApp.scala

/* SimpleApp.scala */
import org.apache.spark.SparkContext
import org.apache.spark.SparkContext._
import org.apache.spark.SparkConf

object SimpleApp {
  def main(args: Array[String]) {
    val logFile = "/home/hduser/spark-1.2.0-bin-hadoop2.4/README.md" // Should be some file on your system
    // val conf = new SparkConf().setAppName("Simple Application")
    val sc = new SparkContext("local", "Simple Job", "/home/hduser/spark-1.2.0-bin-hadoop2.4/")
    val logData = sc.textFile(logFile, 2).cache()
    val numAs = logData.filter(line => line.contains("hadoop")).count()
    val numBs = logData.filter(line => line.contains("see")).count()
    println("Lines with hadoop: %s, Lines with see: %s".format(numAs, numBs))
  }
}

当我使用命令行手动将此作业发送到Spark时:/home/hduser/spark-1.2.0-hadoop-2.4.0/bin/spark-submit --class "SimpleApp" --master local[4] target/scala-2.10/simple-project_2.10-1.0.jar它已成功运行.

如果我运行sbt run并使用服务apache spark正在运行,它就会成功,但是在日志结束时它会给出如下错误:

15/02/06 15:56:49 ERROR Utils: Uncaught exception in thread SparkListenerBus
java.lang.InterruptedException
    at java.util.concurrent.locks.AbstractQueuedSynchronizer.doAcquireSharedInterruptibly(AbstractQueuedSynchronizer.java:996)
    at java.util.concurrent.locks.AbstractQueuedSynchronizer.acquireSharedInterruptibly(AbstractQueuedSynchronizer.java:1303)
    at java.util.concurrent.Semaphore.acquire(Semaphore.java:317)
    at org.apache.spark.scheduler.LiveListenerBus$$anon$1$$anonfun$run$1.apply$mcV$sp(LiveListenerBus.scala:48)
    at org.apache.spark.scheduler.LiveListenerBus$$anon$1$$anonfun$run$1.apply(LiveListenerBus.scala:47)
    at org.apache.spark.scheduler.LiveListenerBus$$anon$1$$anonfun$run$1.apply(LiveListenerBus.scala:47)
    at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1460)
    at org.apache.spark.scheduler.LiveListenerBus$$anon$1.run(LiveListenerBus.scala:46)
15/02/06 15:56:49 ERROR ContextCleaner: Error in cleaning thread
java.lang.InterruptedException
    at java.lang.Object.wait(Native Method)
    at java.lang.ref.ReferenceQueue.remove(ReferenceQueue.java:135)
    at org.apache.spark.ContextCleaner$$anonfun$org$apache$spark$ContextCleaner$$keepCleaning$1.apply$mcV$sp(ContextCleaner.scala:136)
    at org.apache.spark.ContextCleaner$$anonfun$org$apache$spark$ContextCleaner$$keepCleaning$1.apply(ContextCleaner.scala:134)
    at org.apache.spark.ContextCleaner$$anonfun$org$apache$spark$ContextCleaner$$keepCleaning$1.apply(ContextCleaner.scala:134)
    at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1460)
    at org.apache.spark.ContextCleaner.org$apache$spark$ContextCleaner$$keepCleaning(ContextCleaner.scala:133)
    at org.apache.spark.ContextCleaner$$anon$3.run(ContextCleaner.scala:65)

我的代码有什么不对吗？提前致谢.我使用apache spark 1.2.0-bin-hadoop-2.4,scala 2.10.4

Answer 1

的SparkContext或SparkSession当火花码是通过将运行(火花> = 2.0.0)应该被停止sc.stop或spark.stop(火花> = 2.0.0)的代码的末尾.

Answer 2

根据此邮件存档,即:

嗨好明,

您可以放心地忽略此错误.当我们清理并终止守护进程上下文清理线程时,在执行结束时打印.在将来,将这个特定的消息静音会很好,因为它可能会让用户感到困惑.

安德鲁

错误可以忽略不计.