WordCountMapper
package com.neve.Combiner;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Mapper;
import java.io.IOException;
public class WordCountMapper extends Mapper<LongWritable, Text,Text, IntWritable>{
private Text outk = new Text();
//每次读到一个单词都为1
private IntWritable outv = new IntWritable(1);
@Override
protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
//1.将text换为string
String line = value.toString();
//2.分割
String[] words = line.split(" ");
//3.输出
for (String word : words) {
//将String转换为Text
outk.set(word);
//写出
context.write(outk, outv);
}
}
}
WordCountReducer
package com.neve.Combiner;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
import java.io.IOException;
public class WordCountReducer extends Reducer<Text, IntWritable,Text,IntWritable> {
private IntWritable outv = new IntWritable();
@Override
protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
int sum = 0;
for (IntWritable value : values) {
sum += value.get();
}
outv.set(sum);
context.write(key,outv);
}
}
WordCountCombiner
package com.neve.Combiner;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;
import java.io.IOException;
public class WordCountCombiner extends Reducer<Text, IntWritable,Text,IntWritable> {
private IntWritable outv = new IntWritable();
@Override
protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
int sum = 0;
for (IntWritable value : values) {
sum += value.get();
}
outv.set(sum);
context.write(key,outv);
}
}
WordCountDriver
package com.neve.Combiner;
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.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import java.io.IOException;
public class WordCountDriver {
public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {
//1.创建配置
Configuration configuration = new Configuration();
//2.创建job
Job job = Job.getInstance(configuration);
//3.关联驱动类
job.setJarByClass(WordCountDriver.class);
//4.关联mapper和reducer类
job.setMapperClass(WordCountMapper.class);
job.setReducerClass(WordCountReducer.class);
//5.设置mapper的输出值和value
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(IntWritable.class);
//6.设置最终的输出值和value
job.setOutputKeyClass(Text.class);
job.setOutputValueClass(IntWritable.class);
//7.设置输入输出路径
FileInputFormat.setInputPaths(job,new Path("F:\\Workplace\\IDEA_Workplace\\hadoopstudy2\\input"));
FileOutputFormat.setOutputPath(job,new Path("F:\\Workplace\\IDEA_Workplace\\hadoopstudy2\\output"));
//设置combiner
job.setCombinerClass(WordCountCombiner.class);
//8.提交job
job.waitForCompletion(true);
}
}
可以看到combiner与reducer类相同,便可直接将reducer类当做combiner使用(该案例)。
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