MapReduce排序输出

hadoop的map是具有输出自动排序功能的~继续学习~

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
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.input.TextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

import java.io.IOException;

public class Sort extends Configured implements Tool {
　　//这里map将输入的value转化成IntWritable类型，作为输出的key
    public static class Map extends Mapper<Object,Text,IntWritable,IntWritable> {
        private static IntWritable data = new IntWritable();

        public void map(Object key,Text value,Context context) throws IOException,InterruptedException {
            String line = value.toString();
            System.out.println("line" + line);
            data.set(Integer.parseInt(line));
            context.write(data, new IntWritable(1));
        }
    }
　　//reduce将输入的key复制到输出的value上，然后根据输入的value-list中的元素的个数决定key的输出次数
    public static class Reduce extends Reducer<IntWritable,IntWritable,IntWritable,IntWritable> {　　　　//全局linenum来代表key的位次
        private static IntWritable linenum = new IntWritable(1);

        public void reduce(IntWritable key,Iterable<IntWritable> values,Context context) throws
                IOException,InterruptedException{
            for(IntWritable val : values){
                context.write(linenum,key);
                System.out.println(linenum+"    "+key);
                linenum = new IntWritable(linenum.get()+1);
            }
        }
    }

    public  int run(String[] args) throws Exception{
        Configuration aaa = new Configuration();
        Job job = Job.getInstance(aaa);
        String InputPaths = "/usr/local/idea-IC-139.1117.1/Hadoop/out/datainput/sort.txt";
        String OutputPath = "/usr/local/idea-IC-139.1117.1/Hadoop/out/dataout/";

        job.setJarByClass(Sort.class);
        job.setJobName("Sort");

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

        job.setMapperClass(Map.class);
        job.setReducerClass(Reduce.class);
        FileInputFormat.setInputPaths(job, new Path(InputPaths));
        FileOutputFormat.setOutputPath(job, new Path(OutputPath));
        job.setOutputKeyClass(IntWritable.class);
        job.setOutputValueClass(IntWritable.class);

        boolean success = job.waitForCompletion(true);
        return success ? 0 : 1;

    }

    public static void main(String[] args) throws Exception{
        int ret = ToolRunner.run(new Sort(),args);
        System.exit(ret);
    }
}