使用 YARN 的 Mapreduce 无法领先于 0% map 和 0% reduce。我在谷歌计算高内存实例(13 GM RAM)上使用 Cloudera CDH。机器上有 8 GB 可用内存。你能帮我解决一下吗？

sunny@hadoop-m:~$ hadoop jar /opt/cloudera/parcels/CDH-5.3.0-1.cdh5.3.0.p0.30/jars/hadoop-mapreduce-examples-2.5.0-cdh5.3.0.jar  grep input output 'dfs[a-z.]+' 
14/12/24 00:13:53 INFO client.RMProxy: Connecting to ResourceManager at hadoop-m.c.sunny-hadoop-trial.internal/10.240.253.233:8032 
14/12/24 00:13:53 WARN mapreduce.JobSubmitter: No job jar file set.  User classes may not be found. See Job or Job#setJar(String). 
14/12/24 00:13:54 INFO input.FileInputFormat: Total input paths to process : 5 
14/12/24 00:13:54 INFO mapreduce.JobSubmitter: number of splits:5 
14/12/24 00:13:54 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1419360146634_0001 
14/12/24 00:13:54 INFO mapred.YARNRunner: Job jar is not present. Not adding any jar to the list of resources. 
14/12/24 00:13:54 INFO impl.YarnClientImpl: Submitted application application_1419360146634_0001 
14/12/24 00:13:55 INFO mapreduce.Job: The url to track the job: http://hadoop-m.c.sunny-hadoop-trial.internal:8088/proxy/application_1419360146634_0001/ 
14/12/24 00:13:55 INFO mapreduce.Job: Running job: job_1419360146634_0001 

资源管理器输出 一些关于工作的更多信息

yarn-site.xml:http://pastebin.mozilla.org/8113782
mapred-site.xml:http://pastebin.mozilla.org/8113813

请您参考如下方法:

由于 DHCP 服务，服务器的 IP 已更改。 HDFS 和 YARN 的客户端配置变得陈旧。我需要更新客户端配置，我使用 Cloudera 管理器进行了更新，现在集群运行良好。