从word count分析Map Reduce / Map Reduce的word count讲解

public void map(Object key, Text value, Context context
                    ) throws IOException,InterruptedException {//每个mapper对于每个key-value，一次调用map读进一个key-value
      StringTokenizer itr = new StringTokenizer(value.toString());
      while (itr.hasMoreTokens()) {
        word.set(itr.nextToken());
        context.write(word, one);//key是word，key也是reducer读的key；写到‘中间层’
      }
    }
//中间过程，相同hash值的word/key分别汇集到一起，才有key-list的结构，供reducer读
   public void reduce(Text key, Iterable<IntWritable> values, 
                       Context context
                       ) throws IOException, InterruptedException {//每个reducer对于每个key，每次调用reduce读进一个key-values；上一步相同key的value成为一个list即values
      int sum = 0;
      for (IntWritable val : values) {
        sum += val.get();//即+1
      }
      result.set(sum);
      context.write(key, result);//写到指定HDFS（一个）文件

​​https://github.com/apache/hadoop/blob/trunk/hadoop-mapreduce-project/hadoop-mapreduce-examples/src/main/java/org/apache/hadoop/examples/WordCount.java​​