? 另外一个hadoop的入门demo，求平均数。是对WordCount这个demo的一个小小的修改。输入一堆成绩单（人名，成绩），然后求每个人成绩平均数，比如： //? subject1.txt ? a 90 ? b 80 ? c 70 ?// subject2.txt ? a 100 ? b 90 ? c 80 ? 求a,b,c这三个人的平均
? 另外一个hadoop的入门demo，求平均数。是对WordCount这个demo的一个小小的修改。输入一堆成绩单（人名，成绩），然后求每个人成绩平均数，比如：
//? subject1.txt
? a 90
? b 80
? c 70
?// subject2.txt
? a 100
? b 90
? c 80
? 求a,b,c这三个人的平均分。解决思路很简单，在map阶段key是名字，value是成绩，直接output。reduce阶段得到了map输出的key名字，values是该名字对应的一系列的成绩，那么对其求平均数即可。
? 这里我们实现了两个版本的代码，分别用TextInputFormat和 KeyValueTextInputFormat来作为输入格式。
? TextInputFormat版本：
?
import java.util.*;
import java.io.*;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
public class AveScore {
public static class AveMapper extends Mapper
{
@Override
public void map(Object key, Text value, Context context) throws IOException, InterruptedException
{
String line = value.toString();
String[] strs = line.split(" ");
String name = strs[0];
int score = Integer.parseInt(strs[1]);
context.write(new Text(name), new IntWritable(score));
}
}
public static class AveReducer extends Reducer
{
@Override
public void reduce(Text key, Iterable values, Context context) throws IOException, InterruptedException
{
int sum = 0;
int count = 0;
for(IntWritable val : values)
{
sum += val.get();
count++;
}
int aveScore = sum / count;
context.write(key, new IntWritable(aveScore));
}
}
public static void main(String[] args) throws Exception
{
Configuration conf = new Configuration();
Job job = new Job(conf,"AverageScore");
job.setJarByClass(AveScore.class);
job.setMapperClass(AveMapper.class);
job.setReducerClass(AveReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
FileInputFormat.addInputPath(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
System.exit( job.waitForCompletion(true) ? 0 : 1);
}
}
KeyValueTextInputFormat版本；
import java.util.*;
import java.io.*;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.mapreduce.lib.input.KeyValueTextInputFormat;
import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
public class AveScore_KeyValue {
public static class AveMapper extends Mapper
{
@Override
public void map(Text key, Text value, Context context) throws IOException, InterruptedException
{
int score = Integer.parseInt(value.toString());
context.write(key, new IntWritable(score) );
}
}
public static class AveReducer extends Reducer
{
@Override
public void reduce(Text key, Iterable values, Context context) throws IOException, InterruptedException
{
int sum = 0;
int count = 0;
for(IntWritable val : values)
{
sum += val.get();
count++;
}
int aveScore = sum / count;
context.write(key, new IntWritable(aveScore));
}
}
public static void main(String[] args) throws Exception
{
Configuration conf = new Configuration();
conf.set("mapreduce.input.keyvaluelinerecordreader.key.value.separator", " ");
Job job = new Job(conf,"AverageScore");
job.setJarByClass(AveScore_KeyValue.class);
job.setMapperClass(AveMapper.class);
job.setReducerClass(AveReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
job.setInputFormatClass(KeyValueTextInputFormat.class);
job.setOutputFormatClass(TextOutputFormat.class) ;
FileInputFormat.addInputPath(job, new Path(args[0]));
FileOutputFormat.setOutputPath(job, new Path(args[1]));
System.exit( job.waitForCompletion(true) ? 0 : 1);
}
}
输出结果为：
? a 95
? b 85
? c 75
?
作者：qiul12345 发表于2013-8-23 21:51:03 原文链接
阅读：113 评论：0 查看评论
原文地址：Hadoop HelloWord Examples- 求平均数, 感谢原作者分享。
