Combiner-Reduce之前处理过程

简介

• Combiner是Mapper和Reducer之外的组件。
• Combiner是在Reducer运行之前，对Mapper数据进行处理的。

Wordcount实例

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）。