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