MapReduce编程实例3

MapReduce编程实例：

MapReduce编程实例（一）,详细介绍在集成环境中运行第一个MapReduce程序 WordCount及代码分析

MapReduce编程实例（二），计算学生平均成绩

MapReduce编程实例（三），数据去重

MapReduce编程实例（四），排序

MapReduce编程实例（五），MapReduce实现单表关联

MapReduce编程实例（六），MapReduce实现多表关联

 

输入：

2013-11-01 aa
2013-11-02 bb
2013-11-03 cc
2013-11-04 aa
2013-11-05 dd
2013-11-06 dd
2013-11-07 aa
2013-11-09 cc
2013-11-10 ee

2013-11-01 bb 
2013-11-02 33 
2013-11-03 cc
2013-11-04 bb
2013-11-05 23 
2013-11-06 dd
2013-11-07 99 
2013-11-09 99
2013-11-10 ee

.....

.....

.....

数据重复，map中每一行做为一个key，value值任意，经过shuffle之后输入到reduce中利用key的唯一性直接输出key

代码太简单，不解释，上代码：

package com.t.hadoop;

import java.io.IOException;
import java.util.HashSet;
import java.util.StringTokenizer;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
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;

/**
 * 数据去重
 * @author daT dev.tao@gmail.com
 *
 */
public class Dedup {

    public static class MyMapper extends Mapper<Object, Text, Text, Text>{

        @Override
        protected void map(Object key, Text value, Context context)
                throws IOException, InterruptedException {
                context.write(value, new Text(""));
        }
    }

    public static class MyReducer extends Reducer<Text, Text, Text, Text>{

        @Override
        protected void reduce(Text key, Iterable<Text> value,
                Context context)
                throws IOException, InterruptedException {
            context.write(key, new Text(""));
        }
    }


    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException{
        Configuration conf = new Configuration();
        String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();

        if(otherArgs.length<2){
            System.out.println("parameter errors!");
            System.exit(2);
        }

        Job job = new org.apache.hadoop.mapreduce.Job(conf, "Dedup");
        job.setJarByClass(Dedup.class);
        job.setMapperClass(MyMapper.class);
        job.setCombinerClass(MyReducer.class);
        job.setReducerClass(MyReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(Text.class);

        FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
        FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));

        System.exit(job.waitForCompletion(true)?0:1);

    }

}

输出结果
2013-11-01 aa
2013-11-01 bb 
2013-11-02 33 
2013-11-02 bb
2013-11-03 cc
2013-11-03 cc 
2013-11-04 98
2013-11-04 aa
2013-11-04 bb
2013-11-05 23 
2013-11-05 93
2013-11-05 dd
2013-11-06 99
2013-11-06 dd
2013-11-07 92
2013-11-07 99 
2013-11-07 aa
2013-11-09 99
2013-11-09 aa 
2013-11-09 cc
2013-11-10 ee

版权声明：本文为博主原创文章，未经博主允许不得转载。