使用eclipse的快捷键自动生成的map或者reduce函数的参数中：“org.apache.hadoop.mapreduce.Reducer.Context context”

今天在测试mapreduce的程序时，就是简单的去重，对照课本上的程序和自己的程序，唯一不同的就是“org.apache.hadoop.mapreduce.Reducer.Context context”，我写的程序如下：

package com.pro.bq;

import java.io.IOException;

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 Dedup {
    public static class Map extends Mapper<Object,Text, Text, Text>{
        private Text line=new Text();

    @Override
    protected void map(Object key, Text value,
            Context context)
            throws IOException, InterruptedException {
        // TODO Auto-generated method stub
          line=value;
          context.write(line, new Text(""));

    }

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

        @SuppressWarnings("unchecked")
        protected void reduce(Text key, Iterable<Text> value,
                org.apache.hadoop.mapreduce.Reducer.Context context)
                throws IOException, InterruptedException {
            // TODO Auto-generated method stub
            context.write(key, new Text(""));

        }
    }
    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
        Configuration conf=new Configuration();
//        conf.set("mapred.job.tracker", "localhost:9001");
        String hdfs=new String("hdfs://localhost:9000/user/haduser/");
        String[] ioStr=new String[]{hdfs+"input",hdfs+"output/outDedup"};

        //自己在代码中定义路径，否则的话就要就要在程序的输入参数中设置了
        String[] otherStr=new GenericOptionsParser(conf, ioStr).getRemainingArgs();

        if(otherStr.length!=2)
        {
            System.err.println("Usage: Data deduplication <in> <out>");
            System.exit(2);
        }

        Job job=new Job(conf, "Data deduplication");
        job.setJarByClass(Dedup.class);

        job.setMapperClass(Map.class);
        job.setCombinerClass(Reduce.class);
        job.setReducerClass(Reduce.class);

        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(Text.class);

        FileInputFormat.addInputPath(job, new Path(otherStr[0]));
        FileOutputFormat.setOutputPath(job, new Path(otherStr[1]));
        System.exit(job.waitForCompletion(true) ? 0:1);

    }

}

课本上给出的程序如下：

package com.pro.bq;

import java.io.IOException;

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 Dedup {
    public static class Map extends Mapper<Object,Text, Text, Text>{
        private Text line=new Text();

    protected void map(Object key, Text value,
            Context context)
            throws IOException, InterruptedException {
        // TODO Auto-generated method stub
          line=value;
          context.write(line, new Text(""));

    }

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

        protected void reduce(Text key, Iterable<Text> value,
                Context context)
                throws IOException, InterruptedException {
            // TODO Auto-generated method stub
            context.write(key, new Text(""));

        }
    }
    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
        Configuration conf=new Configuration();
//        conf.set("mapred.job.tracker", "localhost:9001");
        String hdfs=new String("hdfs://localhost:9000/user/haduser/");
        String[] ioStr=new String[]{hdfs+"input",hdfs+"output/outDedup"};

        //自己在代码中定义路径，否则的话就要就要在程序的输入参数中设置了
        String[] otherStr=new GenericOptionsParser(conf, ioStr).getRemainingArgs();

        if(otherStr.length!=2)
        {
            System.err.println("Usage: Data deduplication <in> <out>");
            System.exit(2);
        }

        Job job=new Job(conf, "Data deduplication");
        job.setJarByClass(Dedup.class);

        job.setMapperClass(Map.class);
        job.setCombinerClass(Reduce.class);
        job.setReducerClass(Reduce.class);

        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(Text.class);

        FileInputFormat.addInputPath(job, new Path(otherStr[0]));
        FileOutputFormat.setOutputPath(job, new Path(otherStr[1]));
        System.exit(job.waitForCompletion(true) ? 0:1);

    }

}

测试的文件file1.txt是：

2012-3-1 a
2012-3-2 b
2012-3-3 c
2012-3-4 d
2012-3-5 a
2012-3-6 b
2012-3-7 c
2012-3-3 c

file2.txt:

2012-3-1 b
2012-3-2 a
2012-3-3 b
2012-3-4 d
2012-3-5 a
2012-3-6 c
2012-3-7 d
2012-3-3 c

按照我写的运行的结果是：

2012-3-1 a
2012-3-1 b
2012-3-2 a
2012-3-2 b
2012-3-3 b
2012-3-3 c
2012-3-3 c
2012-3-3 c
2012-3-4 d
2012-3-4 d
2012-3-5 a
2012-3-5 a
2012-3-6 b
2012-3-6 c
2012-3-7 c
2012-3-7 d    

想要的结果是:

2012-3-1 a
2012-3-1 b
2012-3-2 a
2012-3-2 b
2012-3-3 b
2012-3-3 c
2012-3-4 d
2012-3-5 a
2012-3-6 b
2012-3-6 c
2012-3-7 c
2012-3-7 d

不知道为什么？暂且记下，有懂的希望不吝赐教，我是菜鸟...