(5-3)Mapper源码分析

//一个4个方法：setup()、map()、cleanup()、run()。
//setup()在map任务之前执行，clean()在map任务之后执行，run()方法控制这些函数执行，run()方法由框架调用。
//代码中给出了一个map()实例。

package org.apache.hadoop.mapreduce;
 * <p>Example:</p>
 * <p><blockquote><pre>
 * public class TokenCounterMapper 
 *     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);
 *     }
 *   }
 * }


@InterfaceAudience.Public
@InterfaceStability.Stable
public class Mapper<KEYIN, VALUEIN, KEYOUT, VALUEOUT> {


  public abstract class Context
    implements MapContext<KEYIN,VALUEIN,KEYOUT,VALUEOUT> {
  }
  


  protected void setup(Context context
                       ) throws IOException, InterruptedException {
    // NOTHING
  }




  @SuppressWarnings("unchecked")
  protected void map(KEYIN key, VALUEIN value, 
                     Context context) throws IOException, InterruptedException {
    context.write((KEYOUT) key, (VALUEOUT) value);
  }




  protected void cleanup(Context context
                         ) throws IOException, InterruptedException {
    // NOTHING
  }
  
  public void run(Context context) throws IOException, InterruptedException {
    setup(context);
    try {
      while (context.nextKeyValue()) {
        map(context.getCurrentKey(), context.getCurrentValue(), context);
      }
    } finally {
      cleanup(context);
    }
  }
}