MapReduce单词统计

WordcountMapper类

package com.sky.mr.wordcount;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 org.junit.Test;import java.io.IOException;public class WordcountMapper extends Mapper {    //由于每读一行文本数据，就要调用一次map方法，为了避免多次创建对象，浪费内存资源，将Text,IntWritable对象创建在    //map方法之外   Text k = new Text();   IntWritable v  = new IntWritable(1);    @Override    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {        //获取每一行的文本内容        String line = value.toString();        //按空格分割        String[] words = line.split(" ");        //转换数据格式，输出        for ( String word: words) {            k.set(word);            context.write(k, v);        }    }}

WordcountReducer类

package com.sky.mr.wordcount;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 {    IntWritable v  = new IntWritable();    @Override    protected void reduce(Text key, Iterable values, Context context) throws IOException, InterruptedException {        //求每组相同key的总个数        int sum = 0;        for ( IntWritable count:values) {            sum += count.get();        }        //输出        v.set(sum);        context.write(key, v);    }}

WordcountDriver类

package com.sky.mr.wordcount;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、获取配置信息以及job对象        Configuration conf = new Configuration();        Job job = Job.getInstance(conf);        //2、设置jar包路径        job.setJarByClass(WordcountDriver.class);        //3、关联自定义mapper和reducer类        job.setMapperClass(WordcountMapper.class);        job.setReducerClass(WordcountReducer.class);        //4、设置Map输出key和value类型         job.setMapOutputKeyClass(Text.class);         job.setMapOutputValueClass(IntWritable.class);        //5、设置最终结果key，value类型         job.setOutputKeyClass(Text.class);         job.setOutputValueClass(IntWritable.class);        //6、设置文件输入输出路径        FileInputFormat.setInputPaths(job,new Path(args[0]));        FileOutputFormat.setOutputPath(job,new Path(args[1]));        //7、将封装了MapReduce程序运行参数的job对象，提交到Yarn集群        boolean result = job.waitForCompletion(true);        System.exit(result?0:1);    }}

输入文件

import org apache hadoop io
import org apache hadoop io
import org apache hadoop
import java io IOException

输出文件

IOException 1
apache 3
hadoop 3
import 4
io 3
java 1
org 3