java - mapreduce 中永无止境的工作

Question

我已经在我的 main 方法中设置了一些 MapReduce 配置

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，会跟踪该进程(我可以在我的集群仪表板(监听端口 8088 的仪表板)中看到它)，但该进程从未完成。它在以下行仍然被阻止:

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

有人有想法吗？

编辑:在我的 yarn nodemanager 日志中，我有这条消息

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:

我在 yarn manager 日志中也有一些较早发生的异常(对于先例 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:我杀死了所有守护进程并再次重新启动 hadoop !事实上，当我运行 jps 时，我仍然得到 hadoop daemons，尽管我已经停止了它们。这是 HADOOP_PID_DIR

的不匹配

Answer 1

yarn的nodemanage默认端口是8040，报错说端口已经被占用。停止所有的 hadoop 进程，如果你没有数据，可以格式化 namenode 一次并尝试再次运行作业。从您的两次编辑来看，问题肯定出在节点管理器上