Docker的Spark顶上不接受工作

我正在尝试使用spark + docker制作一个hello world示例,这是我的代码.

object Generic {
  def main(args: Array[String]) {
    val sc = new SparkContext("spark://172.17.0.3:7077", "Generic", "/opt/spark-0.9.0")

    val NUM_SAMPLES = 100000
    val count = sc.parallelize(1 to NUM_SAMPLES).map{i =>
      val x = Math.random * 2 - 1
      val y = Math.random * 2 - 1
      if (x * x + y * y < 1) 1.0 else 0.0
    }.reduce(_ + _)

    println("Pi is roughly " + 4 * count / NUM_SAMPLES)
  }
}

当我跑步时sbt run,我明白了

14/05/28 15:19:58 INFO client.AppClient$ClientActor: Connecting to master spark://172.17.0.3:7077...
14/05/28 15:20:08 WARN scheduler.TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient memory

我检查了集群UI,我有3个节点,每个节点有1.5g内存,以及namenode UI,我看到同样的事情.

docker日志显示工作人员的输出和主人员的以下内容

14/05/28 21:20:38 ERROR EndpointWriter: AssociationError [akka.tcp://sparkMaster@master:7077] -> [akka.tcp://spark@10.0.3.1:48085]: Error [Association failed with [akka.tcp://spark@10.0.3.1:48085]] [
akka.remote.EndpointAssociationException: Association failed with [akka.tcp://spark@10.0.3.1:48085]
Caused by: akka.remote.transport.netty.NettyTransport$$anonfun$associate$1$$anon$2: Connection refused: /10.0.3.1:48085

]

这种情况发生了几次,然后程序超时并死亡

[error] (run-main-0) org.apache.spark.SparkException: Job aborted: Spark cluster looks down

当我在docker0界面上执行tcpdump时,看起来工作者和主节点正在交谈.

但是,火花控制台可以工作.

如果我设置sc为val sc = new SparkContext("local", "Generic", System.getenv("SPARK_HOME")),则程序运行