MapReduce程序--成绩统计

package cn.edu.ruc.cloudcomputing.book.chapter04;

import java.io.IOException;
import java.util.*;

import org.apache.hadoop.fs.Path;
import org.apache.hadoop.conf.*;
import org.apache.hadoop.io.*;
import org.apache.hadoop.mapreduce.*;
import org.apache.hadoop.mapreduce.lib.input.*;
import org.apache.hadoop.mapreduce.lib.output.*;
import org.apache.hadoop.util.*;

public class WordCount extends Configured implements Tool {
    public static class Map extends Mapper<LongWritable, Text, Text, IntWritable> {
        public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
            String line = value.toString(); //toString将输入的纯文本文件的数据转化成String
            System.out.println(line);//为了便于程序的调试，输出读入的内容   
                //将输入的数据先按行进行分割
            StringTokenizer tokenizerArticle = new StringTokenizer(line,"
");         
             //分别对每一行进行处理
            while(tokenizerArticle.hasMoreTokens()){
                   //每行按空格划分
                StringTokenizer tokenizerLine = new StringTokenizer(tokenizerArticle.nextToken()); 
                String strName = tokenizerLine.nextToken(); //学生姓名部分  
                String strScore = tokenizerLine.nextToken();//成绩部分
                Text name = new Text(strName);//学生姓名  
                int scoreInt = Integer.parseInt(strScore);//学生成绩score of student
                context.write(name, new IntWritable(scoreInt));//输出姓名和成绩
            }
        }
    }
    
    public static class Reduce extends Reducer<Text, IntWritable, Text, IntWritable> {
        public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
            int sum = 0;
            int count=0;
            Iterator<IntWritable> iterator = values.iterator();
            while (iterator.hasNext()) {
                sum += iterator.next().get();    //计算总分
                count++;//统计总的科目数
            } 
            int average = (int) sum/count;//计算平均成绩
            context.write(key, new IntWritable(average));
        }
    } 
    public int run(String [] args) throws Exception {
         Job job = new Job(getConf());
         job.setJarByClass(Score_Process.class);
         job.setJobName("Score_Process");
         job.setOutputKeyClass(Text.class);
         job.setOutputValueClass(IntWritable.class);
         job.setMapperClass(Map.class);
         job.setCombinerClass(Reduce.class);
         job.setReducerClass(Reduce.class);
         job.setInputFormatClass(TextInputFormat.class);
         job.setOutputFormatClass(TextOutputFormat.class);
    
         FileInputFormat.setInputPaths(job, new Path(args[0]));
         FileOutputFormat.setOutputPath(job, new Path(args[1]));
         boolean success = job.waitForCompletion(true);
         return success ? 0 : 1;
    }
    public static void main(String[] args) throws Exception {
         int ret = ToolRunner.run(new Score_Process(), args);
         System.exit(ret);
    }
}