wordcount原理：

1.mapper（Object key,Object value ,Context contex）阶段

2.从数据源读取一行数据传递给mapper函数的value

3.处理数据并将处理结果输出到reduce中去

String line = value.toString（）；

String[] words = line.split(" ");

context.write(word,1)

4.reduce（Object key ,List<value> values ,Context context）阶段

遍历values累加技术结果，并将数据输出

context.write(word,1)

  

代码示例：

Mapper类：

package com.hadoop.mr;import java.io.IOException;import org.apache.hadoop.io.LongWritable;import org.apache.hadoop.io.Text;import org.apache.hadoop.mapreduce.Mapper;/** * Mapper 
     
       * Mapper
      
       //hadoop对上边的数据类型进行了封装 *  LongWritable（Long）:偏移量 *  Text（String）：输入数据的数据类型 *  Text（String）:输出数据的key的数据类型 *  LongWritable（Long）:输出数据的key的数据类型 * @author shiwen */public class WordCountMapper extends Mapper
       
        {    @Override    protected void map(LongWritable key, Text value,            Mapper
        
         .Context context)            throws IOException, InterruptedException {        //1.读取一行        String line = value.toString();        //2.分割单词        String[] words = line.split(" ");        //3.统计单词        for(String word : words){            //4.输出统计            context.write(new Text(word), new LongWritable(1));        }    }}
        
       
      
     

reduce类

package com.hadoop.mr;import java.io.IOException;import org.apache.hadoop.io.LongWritable;import org.apache.hadoop.io.Text;import org.apache.hadoop.mapreduce.Reducer;public class WordCountReduce extends Reducer
     
      {    @Override    protected void reduce(Text key, Iterable
      
        values,            Reducer
       
        .Context context)            throws IOException, InterruptedException {                long count = 0;        //1.遍历vlues统计数据        for(LongWritable value : values){            count += value.get();        }        //输出统计        context.write(key, new LongWritable(count));            }}
       
      
     

运行类：

package com.hadoop.mr;import java.io.IOException;import org.apache.hadoop.conf.Configuration;import org.apache.hadoop.fs.Path;import org.apache.hadoop.io.LongWritable;import org.apache.hadoop.mapreduce.Job;import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;import com.sun.jersey.core.impl.provider.entity.XMLJAXBElementProvider.Text;public class WordCountRunner {    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {        //1.创建配置对象        Configuration config = new Configuration();        //2.Job对象        Job job = new Job(config);                //3.设置mapperreduce所在的jar包        job.setJarByClass(WordCountRunner.class);                //4.设置mapper的类        job.setMapOutputKeyClass(WordCountMapper.class);        //5.设置reduce的类        job.setReducerClass(WordCountReduce.class);                //6.设置reduce输入的key的数据类型        job.setOutputKeyClass(Text.class);        //7.设置reduce输出的value的数据类型        job.setOutputValueClass(LongWritable.class);                //8.设置输入的文件位置        FileInputFormat.setInputPaths(job, new Path("hdfs://192.168.1.10:9000/input"));        //9.设置输出的文件位置        FileOutputFormat.setOutputPath(job, new Path("hdfs://192.168.1.10:9000/input"));                //10.将任务提交给集群        job.waitForCompletion(true);            }}