Windows Eclipse运行虚拟机Hadoop集群WordCount程序报异常，求解决

Exception in thread "main" java.lang.NullPointerException

	at java.lang.ProcessBuilder.start(ProcessBuilder.java:442)

	at org.apache.hadoop.util.Shell.runCommand(Shell.java:404)

	at org.apache.hadoop.util.Shell.run(Shell.java:379)

	at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:589)

	at org.apache.hadoop.util.Shell.execCommand(Shell.java:678)

	at org.apache.hadoop.util.Shell.execCommand(Shell.java:661)

	at org.apache.hadoop.fs.RawLocalFileSystem.setPermission(RawLocalFileSystem.java:639)

	at org.apache.hadoop.fs.RawLocalFileSystem.mkdirs(RawLocalFileSystem.java:435)

	at org.apache.hadoop.fs.FilterFileSystem.mkdirs(FilterFileSystem.java:277)

	at org.apache.hadoop.mapreduce.JobSubmissionFiles.getStagingDir(JobSubmissionFiles.java:125)

	at org.apache.hadoop.mapreduce.JobSubmitter.submitJobInternal(JobSubmitter.java:344)

	at org.apache.hadoop.mapreduce.Job$10.run(Job.java:1268)

	at org.apache.hadoop.mapreduce.Job$10.run(Job.java:1265)

	at java.security.AccessController.doPrivileged(Native Method)

	at javax.security.auth.Subject.doAs(Subject.java:396)

	at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1491)

	at org.apache.hadoop.mapreduce.Job.submit(Job.java:1265)

	at org.apache.hadoop.mapreduce.Job.waitForCompletion(Job.java:1286)

	at com.armslee.study.test.WordCount.main(WordCount.java:85)

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 * distributed with this work for additional information

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 * to you under the Apache License, Version 2.0 (the

 * "License"); you may not use this file except in compliance

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 *

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 *

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package com.armslee.study.test;



import java.io.IOException;

import java.util.StringTokenizer;



import org.apache.hadoop.conf.Configuration;

import org.apache.hadoop.fs.Path;

import org.apache.hadoop.io.IntWritable;

import org.apache.hadoop.io.Text;

import org.apache.hadoop.mapreduce.Job;

import org.apache.hadoop.mapreduce.Mapper;

import org.apache.hadoop.mapreduce.Reducer;

import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;

import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

import org.apache.hadoop.util.GenericOptionsParser;



public class WordCount {



  public static class TokenizerMapper 

       extends Mapper<Object, Text, Text, IntWritable>{

    

    private final static IntWritable one = new IntWritable(1);

    private Text word = new Text();

      

    public void map(Object key, Text value, Context context

                    ) throws IOException, InterruptedException {

      StringTokenizer itr = new StringTokenizer(value.toString());

      while (itr.hasMoreTokens()) {

        word.set(itr.nextToken());

        context.write(word, one);

      }

    }

  }

  

  public static class IntSumReducer 

       extends Reducer<Text,IntWritable,Text,IntWritable> {

    private IntWritable result = new IntWritable();



    public void reduce(Text key, Iterable<IntWritable> values, 

                       Context context

                       ) throws IOException, InterruptedException {

      int sum = 0;

      for (IntWritable val : values) {

        sum += val.get();

      }

      result.set(sum);

      context.write(key, result);

    }

  }



  public static void main(String[] args) throws Exception {

    Configuration conf = new Configuration();

    String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();

    if (otherArgs.length != 2) {

      System.err.println("Usage: wordcount <in> <out>");

      System.exit(2);

    }

    @SuppressWarnings("deprecation")

	Job job = new Job(conf, "word count");

    job.setJarByClass(WordCount.class);

    job.setMapperClass(TokenizerMapper.class);

    job.setCombinerClass(IntSumReducer.class);

    job.setReducerClass(IntSumReducer.class);

    job.setOutputKeyClass(Text.class);

    job.setOutputValueClass(IntWritable.class);

    FileInputFormat.addInputPath(job, new Path(otherArgs[0]));

    FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));

    System.exit(job.waitForCompletion(true) ? 0 : 1);

  }

}