首先編寫wordcountMap類

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 WordCountMap extends Mapper<LongWritable, Text,Text, IntWritable> {
    
 
/*
    * LongWritable:偏移量,表示該行在檔案中的位置，而不是行號
    * Text map階段的輸入資料，一行文字資訊，字串型別String
    * Text map階段的資料字串型別String
    * IntWritable map階段輸出的value型別，對應Java中的int型別，表示行號
    * */

    @Override
    protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
        
 
//讀取每行文字
        String line = value.toString();
        //splite拆分
        String[] words= line.split(" ");
        //取出每個單詞
        for (String word:words){
            //將單詞轉換為Text型別的
            Text wordText = new Text(word);
            //將1轉變為IntWritablele
            IntWritable outValue = new IntWritable(1);
            
 
//寫出單詞跟對應1
            context.write(wordText,outValue);
        }
    }
}

再編寫wordcountreduce類

import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Reducer;

import java.io.IOException;

public class WordCountReduce extends Reducer<Text, IntWritable,Text,IntWritable> {
    /*
    * Text:輸入的字串型別，序列化
    * IntWritable:輸入一串1，序列化
    * Text：輸出的字串型別，序列化
    * IntWritable：輸出的求和陣列，序列化
    * */
    @Override
    protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
        /*
        * key:輸入的單詞的名字
        * values:輸入一串1
        * context:輸入的工具
        * */
        int sum=0;
        for(IntWritable number:values){
            sum+=number.get();
        }
        context.write(key,new IntWritable(sum));
    }
}

最後編寫wordcount類將前面的兩個類結合起來

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;

public class WordCount {
    public static void main(String[] args) throws Exception {
        // 建立本次mr程式的job例項
        Configuration conf = new Configuration();
        Job job = Job.getInstance(conf);

        // 指定本次job執行的主類
        job.setJarByClass(WordCount.class);

        // 指定本次job的具體mapper reducer實現類
        job.setMapperClass(WordCountMap.class);
        job.setReducerClass(WordCountReduce.class);

        // 指定本次job map階段的輸出資料型別
        job.setMapOutputKeyClass(Text.class);
        job.setMapOutputValueClass(IntWritable.class);

        // 指定本次job reduce階段的輸出資料型別 也就是整個mr任務的最終輸出型別
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);

        // 指定本次job待處理資料的目錄 和程式執行完輸出結果存放的目錄
        FileInputFormat.setInputPaths(job, "E:\\Demo\\hadoop\\input\\Wordcount.txt");
        FileOutputFormat.setOutputPath(job, new Path("E:\\Demo\\hadoop\\output"));

        // 提交本次job
        boolean b = job.waitForCompletion(true);

        System.exit(b ? 0 : 1);
    }
}

（需要提前在Wordcount.txt中寫入文字）