Hadoop MapReduce排序程序

    package com.hadoop.sample;  
      
    import java.io.IOException;  
    import java.util.StringTokenizer;  
      
    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 Sort {  
        //map将输入中的value化成IntWritable类型，作为输出的key  
        public static class Map extends Mapper{  
            private static IntWritable data = new IntWritable();  
            public void map(Object key,Text value,Context context) throws IOException,InterruptedException{  
                 String line = value.toString();  
                 data.set(Integer.parseInt(line));  
                 context.write(data, new IntWritable(1));  
            }  
        }  
        //reduce将输入中的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  
        //用全局的linenum来代表key的位次  
        public static class Reduce extends Reducer{  
            private static IntWritable linenum = new IntWritable(1);  
            public void reduce(IntWritable key,Iterable values,Context context) throws IOException,InterruptedException{  
                for(IntWritable val:values){  
                    context.write(linenum, key);  
                    linenum = new IntWritable(linenum.get()+1);  
                }  
                  
            }  
        }  
        /** 
         * @param args 
         */  
        public static void main(String[] args) throws Exception{  
            // TODO Auto-generated method stub  
            Configuration conf = new Configuration();  
            String[] otherArgs = new GenericOptionsParser(conf,args).getRemainingArgs();  
            if(otherArgs.length != 2){  
                System.err.println("Usage WordCount  ");  
                System.exit(2);  
            }  
            Job job = new Job(conf,"Sort");  
            job.setJarByClass(Sort.class);  
            job.setMapperClass(Map.class);  
            job.setCombinerClass(Reduce.class);  
            job.setReducerClass(Reduce.class);  
            job.setOutputKeyClass(IntWritable.class);  
            job.setOutputValueClass(IntWritable.class);  
            FileInputFormat.addInputPath(job, new Path(otherArgs[0]));  
            FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));  
            System.exit(job.waitForCompletion(true) ? 0 : 1);  
        }  
      
    }