MapReduce编程：平均成绩

提示：扫一扫查出行
【扫一扫了解最新限行尾号】
复制提示

问题描述

现在有三个文件分别代表学生的各科成绩，编程求各位同学的平均成绩。

编程思想

map函数将姓名作为key，成绩作为value输出，reduce根据key即可将三门成绩相加。

代码

package org.apache.hadoop.examples; import java.io.IOException;
import java.util.Iterator;
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; public class calcGPA {
public calcGPA() {
} public static void main(String[] args) throws Exception {
Configuration conf = new Configuration(); String fileAddress = "hdfs://localhost:9000/user/hadoop/"; //String[] otherArgs = (new GenericOptionsParser(conf, args)).getRemainingArgs();
String[] otherArgs = new String[]{fileAddress+"score1.txt", fileAddress+"score2.txt", fileAddress+"score3.txt", fileAddress+"output"};
if(otherArgs.length < 2) {
System.err.println("Usage: calcGPA <in> [<in>...] <out>");
System.exit(2);
} Job job = Job.getInstance(conf, "calc GPA");
job.setJarByClass(calcGPA.class);
job.setMapperClass(calcGPA.TokenizerMapper.class);
job.setCombinerClass(calcGPA.IntSumReducer.class);
job.setReducerClass(calcGPA.IntSumReducer.class);
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class); for(int i = 0; i < otherArgs.length - 1; ++i) {
FileInputFormat.addInputPath(job, new Path(otherArgs[i]));
} FileOutputFormat.setOutputPath(job, new Path(otherArgs[otherArgs.length - 1]));
System.exit(job.waitForCompletion(true)?0:1);
} public static class IntSumReducer extends Reducer<Text, IntWritable, Text, IntWritable> { public IntSumReducer() {
} public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
int sum = 0;
int count = 0; IntWritable val;
for(Iterator i$ = values.iterator(); i$.hasNext(); sum += val.get(),count++) {
val = (IntWritable)i$.next();
} int average = (int)sum/count;
context.write(key, new IntWritable(average));
}
} public static class TokenizerMapper extends Mapper<Object, Text, Text, IntWritable> { public TokenizerMapper() {
} public void map(Object key, Text value, Context context) throws IOException, InterruptedException {
StringTokenizer itr = new StringTokenizer(value.toString(), "\n"); while(itr.hasMoreTokens()) {
StringTokenizer iitr = new StringTokenizer(itr.nextToken());
String name = iitr.nextToken();
String score = iitr.nextToken();
context.write(new Text(name), new IntWritable(Integer.parseInt(score)));
} }
}
}