去重

package com.duking.hadoop;

 
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 {
 
    // map将输入中的value复制到输出数据的key上，并直接输出
 
    public static class Map extends Mapper<Object, Text, Text, Text> {
 
        private static Text line = new Text();// 每行数据
 
        // 实现map函数
        public void map(Object key, Text value, Context context)
 
        throws IOException, InterruptedException {
 
            line = value;
 
            context.write(line, new Text(""));
        }
    }
 
    // reduce将输入中的key复制到输出数据的key上，并直接输出    这是数据区重的思想
    public static class Reduce extends Reducer<Text, Text, Text, Text> {
 
        // 实现reduce函数
 
        public void reduce(Text key, Iterable<Text> values, Context context)
 
        throws IOException, InterruptedException {
 
            context.write(key, new Text(""));
 
        }
 
    }
 
    public static void main(String[] args) throws Exception {
 
        Configuration conf = new Configuration();
 
        // 这句话很关键
        conf.set("mapred.job.tracker", "192.168.60.129:9000");
 
        //指定带运行参数的目录为输入输出目录
        String[] otherArgs = new GenericOptionsParser(conf, args)
        .getRemainingArgs();
         
        /*      指定工程下的input2为文件输入目录    output2为文件输出目录
        String[] ioArgs = new String[] { "input2", "output2" };
 
        String[] otherArgs = new GenericOptionsParser(conf, ioArgs)
                .getRemainingArgs();*/
 
        if (otherArgs.length != 2) {    //判断路径参数是否为2个
 
            System.err.println("Usage: Data Deduplication <in> <out>");
 
            System.exit(2);
 
        }
 
        //set maprduce job name
        Job job = new Job(conf, "Data Deduplication");
 
        job.setJarByClass(Dedup.class);
 
        // 设置Map、Combine和Reduce处理类
 
        job.setMapperClass(Map.class);
 
        job.setCombinerClass(Reduce.class);
 
        job.setReducerClass(Reduce.class);
 
        // 设置输出类型
 
        job.setOutputKeyClass(Text.class);
 
        job.setOutputValueClass(Text.class);
 
        // 设置输入和输出目录
 
        FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
 
        FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
 
        System.exit(job.waitForCompletion(true) ? 0 : 1);
 
    }
 
}