Windows平台开发Mapreduce程序远程调用运行在Hadoop集群—Yarn调度引擎异常

共享原因：虽然用一篇博文写问题感觉有点奢侈，但是搜索百度，相关文章太少了，苦苦探寻日志才找到解决方案。

遇到问题：在windows平台上开发的mapreduce程序，运行迟迟没有结果。

Mapreduce程序

public class Test {
    public static void main(String [] args) throws Exception{
        Configuration conf = new Configuration();
       conf.set("fs.defaultFS", "hdfs://master:9000/");
    conf.set(</span>"mapreduce.job.jar", "D:/intelij-workspace/aaron-bigdata/aaorn-mapreduce/target/aaorn-mapreduce-1.0-SNAPSHOT.jar"<span style="color: #000000;">.trim());
    conf.set(</span>"mapreduce.framework.name", "yarn"<span style="color: #000000;">);
    conf.set(</span>"yarn.resourcemanager.hostname", "master"<span style="color: #000000;">);
    conf.set(</span>"mapreduce.app-submission.cross-platform", "true"<span style="color: #000000;">);
    Job job </span>=<span style="color: #000000;"> Job.getInstance(conf);
    job.setMapperClass(WordCountMapper.</span><span style="color: #0000ff;">class</span><span style="color: #000000;">);
    job.setReducerClass(WordCountReducer.</span><span style="color: #0000ff;">class</span><span style="color: #000000;">);

    job.setMapOutputKeyClass(Text.</span><span style="color: #0000ff;">class</span><span style="color: #000000;">);
    job.setMapOutputValueClass(LongWritable.</span><span style="color: #0000ff;">class</span><span style="color: #000000;">);

    job.setOutputKeyClass(Text.</span><span style="color: #0000ff;">class</span><span style="color: #000000;">);
    job.setOutputValueClass(LongWritable.</span><span style="color: #0000ff;">class</span><span style="color: #000000;">);

    FileInputFormat.setInputPaths(job,</span>"hdfs://master:9000/input/"<span style="color: #000000;">);
    FileOutputFormat.setOutputPath(job,</span><span style="color: #0000ff;">new</span> Path("hdfs://master:9000/output3/"<span style="color: #000000;">));

    job.waitForCompletion(</span><span style="color: #0000ff;">true</span><span style="color: #000000;">);
}

}

运行结果

[QC] INFO [main] org.apache.hadoop.yarn.client.RMProxy.createRMProxy(98) | Connecting to ResourceManager at master/192.168.56.100:8032
[QC] WARN [main] org.apache.hadoop.mapreduce.JobResourceUploader.uploadFiles(64) | Hadoop
command-line option parsing not performed. Implement the Tool interface and execute your application with ToolRunner to remedy this.
[QC] INFO [main] org.apache.hadoop.mapreduce.lib.input.FileInputFormat.listStatus(283) | Total input paths to process : 2
[QC] INFO [main] org.apache.hadoop.mapreduce.JobSubmitter.submitJobInternal(198) | number of splits:2
[QC] INFO [main] org.apache.hadoop.mapreduce.JobSubmitter.printTokens(287) | Submitting tokens for job: job_1496627557122_0004
[QC] INFO [main] org.apache.hadoop.yarn.client.api.impl.YarnClientImpl.submitApplication(273) | Submitted application application_1496627557122_0004
[QC] INFO [main] org.apache.hadoop.mapreduce.Job.submit(1294) | The url to track the job: http://master:8088/proxy/application_1496627557122_0004/
[QC] INFO [main] org.apache.hadoop.mapreduce.Job.monitorAndPrintJob(1339) | Running job: job_1496627557122_0004

Master(NameNode)日志

java.io.IOException: Connection reset by peer
        at sun.nio.ch.FileDispatcherImpl.read0(Native Method)
        at sun.nio.ch.SocketDispatcher.read(SocketDispatcher.java:39)
        at sun.nio.ch.IOUtil.readIntoNativeBuffer(IOUtil.java:223)
        at sun.nio.ch.IOUtil.read(IOUtil.java:197)
        at sun.nio.ch.SocketChannelImpl.read(SocketChannelImpl.java:380)
        at org.apache.hadoop.ipc.Server.channelRead(Server.java:2603)
        at org.apache.hadoop.ipc.Server.access$2800(Server.java:136)
        at org.apache.hadoop.ipc.Server$Connection.readAndProcess(Server.java:1481)
        at org.apache.hadoop.ipc.Server$Listener.doRead(Server.java:771)
        at org.apache.hadoop.ipc.Server$Listener$Reader.doRunLoop(Server.java:637)
        at org.apache.hadoop.ipc.Server$Listener$Reader.run(Server.java:608

Slave(DataNode)的日志异常

2017-06-05 09:49:40,464 INFO org.apache.hadoop.ipc.Client: Retrying connect to server: 0.0.0.0/0.0.0.0:8031. Already tried 2 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)
2017-06-05 09:49:41,464 INFO org.apache.hadoop.ipc.Client: Retrying connect to server: 0.0.0.0/0.0.0.0:8031. Already tried 3 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)
2017-06-05 09:49:42,465 INFO org.apache.hadoop.ipc.Client: Retrying connect to server: 0.0.0.0/0.0.0.0:8031. Already tried 4 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)
2017-06-05 09:49:43,467 INFO org.apache.hadoop.ipc.Client: Retrying connect to server: 0.0.0.0/0.0.0.0:8031. Already tried 5 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)
2017-06-05 09:49:44,468 INFO org.apache.hadoop.ipc.Client: Retrying connect to server: 0.0.0.0/0.0.0.0:8031. Already tried 6 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)
2017-06-05 09:49:45,470 INFO org.apache.hadoop.ipc.Client: Retrying connect to server: 0.0.0.0/0.0.0.0:8031. Already tried 7 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)
2017-06-05 09:49:46,472 INFO org.apache.hadoop.ipc.Client: Retrying connect to server: 0.0.0.0/0.0.0.0:8031. Already tried 8 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)
2017-06-05 09:49:47,474 INFO org.apache.hadoop.ipc.Client: Retrying connect to server: 0.0.0.0/0.0.0.0:8031. Already tried 9 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)

 

说明

我的hadoop集群是Master(namenode)、Slave1、Slave2、Slave3

 

解决办法

在所有的Slave机器的yarn-site.xml,之前我只在Master机器上添加了这些内容

<configuration>
　　<property>
    　　<name>yarn.resourcemanager.hostname</name>
    　　<value>master</value>
　　</property>
　　<property>
    　　<name>yarn.nodemanager.aux-services</name>
    　　<value>mapreduce_shuffle</value>
　　</property>
　　<property>
    　　<name>yarn.nodemanager.auxservices.mapreduce.shuffle.class</name>
    　　<value>org.apache.hadoop.mapred.ShuffleHandler</value>
　　</property>
</configuration>