我在我的系统中设置了一些mapreduce配置 main 方法本身

configuration.set("mapreduce.jobtracker.address", "localhost:54311");
configuration.set("mapreduce.framework.name", "yarn");
configuration.set("yarn.resourcemanager.address", "localhost:8032");

现在当我启动 mapreduce 任务时，进程被跟踪（我可以在集群 Jmeter 板（在端口8088上侦听的 Jmeter 板）中看到它），但进程永远不会完成。它在以下线路上保持阻塞状态：

15/06/30 15:56:17 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
15/06/30 15:56:17 INFO client.RMProxy: Connecting to ResourceManager at localhost/127.0.0.1:8032
15/06/30 15:56:18 WARN mapreduce.JobResourceUploader: Hadoop command-line option parsing not performed. Implement the Tool interface and execute your application with ToolRunner to remedy this.
15/06/30 15:56:18 INFO input.FileInputFormat: Total input paths to process : 1
15/06/30 15:56:18 INFO mapreduce.JobSubmitter: number of splits:1
15/06/30 15:56:18 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1435241671439_0008
15/06/30 15:56:19 INFO impl.YarnClientImpl: Submitted application application_1435241671439_0008
15/06/30 15:56:19 INFO mapreduce.Job: The url to track the job: http://10.0.0.10:8088/proxy/application_1435241671439_0008/
15/06/30 15:56:19 INFO mapreduce.Job: Running job: job_1435241671439_0008

有人有主意吗？
编辑：在我的 yarn nodemanager 洛格，我有这个消息

org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl: Event EventType: KILL_CONTAINER sent to absent container container_1435241671439_0003_03_000001
2015-06-30 15:44:38,396 WARN org.apache.hadoop.yarn.server.nodemanager.containermanager.ContainerManagerImpl: Event EventType: KILL_CONTAINER sent to absent container container_1435241671439_0002_04_000001

编辑2：
我也曾在 yarn manager 日志中，发生较早的异常（对于以前的mapreduce调用）：

org.apache.hadoop.yarn.exceptions.YarnRuntimeException: java.net.BindException: Problem binding to [0.0.0.0:8040] java.net.BindException: Address already in use; For more details see:

解决方案：我杀死了所有的守护进程，然后重新启动 hadoop ! 事实上，当我跑的时候 jps ，我仍然在 hadoop daemons 尽管我阻止了他们。这是不匹配的 HADOOP_PID_DIR