1、处理输入文本为<k,v>对，继承Mapper方法

package com.cr.hdfs;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 map extends Mapper
     
       {    /**     * WordCountMapper 处理文本为
      
       对     * @param key 每一行字节数的偏移量     * @param value 每一行的文本     * @param context 上下文     * @throws IOException     * @throws InterruptedException     */    @Override    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {        Text keyOut = new Text();        IntWritable valueout = new IntWritable();        String[] arr = value.toString().split(" ");        for(String s : arr){            keyOut.set(s);            valueout.set(1);            context.write(keyOut,valueout);        }    }}
      
     

2、对Mapper的输入进行reduce操作，继承reducer方法

package com.cr.hdfs;import org.apache.hadoop.io.IntWritable;import org.apache.hadoop.io.Text;import org.apache.hadoop.mapreduce.Reducer;import java.io.IOException;public class reduce extends Reducer
      
       {    @Override    protected void reduce(Text key, Iterable
       
         values, Context context) throws IOException, InterruptedException {        int count = 0;        for(IntWritable iw : values){            count += iw.get();        }        context.write(key,new IntWritable(count));    }}
       
      

3、wordcountApp

package com.cr.hdfs;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;/** * wordcount单词统计 */public class wordcount {    public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException {        //单例作业        Configuration conf = new Configuration();//        conf.set("fs.defaultFS","file:///");        Job job = Job.getInstance(conf);        //设置job的各种属性        job.setJobName("wordcountAPP");                 //设置job名称        job.setJarByClass(wordcount.class);              //设置搜索类//        job.setInputFormatClass(org.apache.hadoop.mapreduce.lib.input.TextInputFormat.class);  //设置输入格式        FileInputFormat.addInputPath(job, new Path(args[0])); //添加输入路径        FileOutputFormat.setOutputPath(job,new Path(args[1]));//设置输出路径        job.setInputFormatClass(org.apache.hadoop.mapreduce.lib.input.TextInputFormat.class);        job.setMapperClass(map.class);                   //设置mapper类        job.setReducerClass(reduce.class);               //设置reduecer类        job.setNumReduceTasks(1);                         //设置reduce个数        job.setMapOutputKeyClass(Text.class);            //设置之map输出key        job.setMapOutputValueClass(IntWritable.class);   //设置map输出value        job.setOutputKeyClass(Text.class);               //设置mapreduce 输出key        job.setOutputValueClass(IntWritable.class);      //设置mapreduce输出value        job.waitForCompletion(true);    }}

4、设置参数输入路径和输出路径

5、运行结果