第一个WordCount类运行

import java.io.IOException;

import java.util.*;

import org.apache.hadoop.fs.Path;

import org.apache.hadoop.conf.*;

import org.apache.hadoop.io.*;

import org.apache.hadoop.mapreduce.*;

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

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

import org.apache.hadoop.util.*;

public class WordCount extends Configured implements Tool {

 public static class Map extends Mapper<LongWritable, Text, Text, IntWritable> {

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

      private Text word = new Text();

      public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {

        String line = value.toString();

        StringTokenizer tokenizer = new StringTokenizer(line);

        while (tokenizer.hasMoreTokens()) {

          word.set(tokenizer.nextToken());

          context.write(word, one);

        }

      }

    }

 

 public static class Reduce extends Reducer<Text, IntWritable, Text, IntWritable> {

public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {

     int sum = 0;

      for (IntWritable val : values) {

        sum += val.get();

      }

      context.write(key, new IntWritable(sum));

 }

}

 

public int run(String [] args) throws Exception {

     Job job = new Job(getConf());

     job.setJarByClass(WordCount.class);

     job.setJobName("wordcount");

job.setOutputKeyClass(Text.class);

     job.setOutputValueClass(IntWritable.class);

 

     job.setMapperClass(Map.class);

     job.setReducerClass(Reduce.class);

job.setInputFormatClass(TextInputFormat.class);

     job.setOutputFormatClass(TextOutputFormat.class);

FileInputFormat.setInputPaths(job, new Path(args[0]));

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

boolean success = job.waitForCompletion(true);

     return success ? 0 : 1;

}

 

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

      int ret = ToolRunner.run(new WordCount(), args);

      System.exit(ret);

   }

}

新建成WordCount.java ,  把上面代码拷贝进去。

然后编译，打成jar包。

然后新建  touch file01  ，里面写入hello world bye world

touch file02  ，  里面写入hello hadoop bye hadoop

然后   hadoop dfs -put  file0*  input  ，放进HDFS文件系统中

然后运行hadoop  jar   WordCount.jar   WordCount  input output

输出结果：

bye 2

hadoop 2

hello2

world 2