Hadop使用Partitioner后,结果还是一个文件,怎样解决??

近期看了一下partitioner。于是照着写了一个列子。最后发现程序并没有将结果分开写入对应的文件,结果还是一个文件,于是乎感觉是不是没实用集群去执行程序,发现control中还是本地执行的代码:

<span style="font-size:12px;">2015-08-09 09:53:02,193 WARN  [main] conf.Configuration (Configuration.java:loadProperty(2172)) - file:/tmp/hadoop-cau/mapred/staging/cau1745029252/.staging/job_local1745029252_0001/job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.retry.interval;  Ignoring.
2015-08-09 09:53:02,195 WARN  [main] conf.Configuration (Configuration.java:loadProperty(2172)) - file:/tmp/hadoop-cau/mapred/staging/cau1745029252/.staging/job_local1745029252_0001/job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.attempts;  Ignoring.
2015-08-09 09:53:02,632 WARN  [main] conf.Configuration (Configuration.java:loadProperty(2172)) - file:/tmp/hadoop-cau/mapred/local/localRunner/cau/job_local1745029252_0001/job_local1745029252_0001.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.retry.interval;  Ignoring.
2015-08-09 09:53:02,634 WARN  [main] conf.Configuration (Configuration.java:loadProperty(2172)) - file:/tmp/hadoop-cau/mapred/local/localRunner/cau/job_local1745029252_0001/job_local1745029252_0001.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.attempts;  Ignoring.
2015-08-09 09:53:02,657 INFO  [main] mapreduce.Job (Job.java:submit(1272)) - The url to track the job: http://localhost:8080/
2015-08-09 09:53:02,659 INFO  [main] mapreduce.Job (Job.java:monitorAndPrintJob(1317)) - Running job: job_local1745029252_0001
2015-08-09 09:53:02,662 INFO  [Thread-12] mapred.LocalJobRunner (LocalJobRunner.java:createOutputCommitter(323)) - OutputCommitter set in config null
2015-08-09 09:53:02,679 INFO  [Thread-12] mapred.LocalJobRunner (LocalJobRunner.java:createOutputCommitter(341)) - OutputCommitter is org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter
2015-08-09 09:53:02,810 INFO  [Thread-12] mapred.LocalJobRunner (LocalJobRunner.java:run(389)) - Waiting for map tasks</span>


于是乎,想着打包到集群去执行看看,结果节点报了各种错!


<span style="font-size:12px;">15/08/09 10:02:41 INFO mapreduce.Job: The url to track the job: http://master:8088/proxy/application_1438842873940_0002/
15/08/09 10:02:41 INFO mapreduce.Job: Running job: job_1438842873940_0002
15/08/09 10:02:54 INFO mapreduce.Job: Job job_1438842873940_0002 running in uber mode : false
15/08/09 10:02:54 INFO mapreduce.Job:  map 0% reduce 0%
15/08/09 10:02:55 INFO mapreduce.Job: Task Id : attempt_1438842873940_0002_m_000000_0, Status : FAILED
Container launch failed for container_1438842873940_0002_01_000002 : java.lang.IllegalArgumentException: java.net.UnknownHostException: slave7
	at org.apache.hadoop.security.SecurityUtil.buildTokenService(SecurityUtil.java:377)
	at org.apache.hadoop.security.SecurityUtil.setTokenService(SecurityUtil.java:356)
	at org.apache.hadoop.yarn.util.ConverterUtils.convertFromYarn(ConverterUtils.java:237)
	at org.apache.hadoop.yarn.client.api.impl.ContainerManagementProtocolProxy$ContainerManagementProtocolProxyData.newProxy(ContainerManagementProtocolProxy.java:218)
	at org.apache.hadoop.yarn.client.api.impl.ContainerManagementProtocolProxy$ContainerManagementProtocolProxyData.<init>(ContainerManagementProtocolProxy.java:196)
	at org.apache.hadoop.yarn.client.api.impl.ContainerManagementProtocolProxy.getProxy(ContainerManagementProtocolProxy.java:117)
	at org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl.getCMProxy(ContainerLauncherImpl.java:403)
	at org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl$Container.launch(ContainerLauncherImpl.java:138)
	at org.apache.hadoop.mapreduce.v2.app.launcher.ContainerLauncherImpl$EventProcessor.run(ContainerLauncherImpl.java:369)
	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
	at java.lang.Thread.run(Thread.java:722)
Caused by: java.net.UnknownHostException: slave7</span>

终于问题还是没解决,哪位大侠指点一下吧。

小弟还没入门。在此叩谢!!!

原文地址:https://www.cnblogs.com/yangykaifa/p/6937829.html