import java.io.IOException; import java.util.*; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.*; import org.apache.hadoop.mapreduce.Job; import org.apache.hadoop.mapreduce.Mapper; import org.apache.hadoop.mapreduce.Reducer; import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; import org.apache.hadoop.util.GenericOptionsParser; public class Merge { /********** Begin **********/ /********** End **********/ }

好的，这是一个基本的MapReduce程序的框架。在这个程序中，你需要完成mapper和reducer函数，然后将它们添加到这个框架中。下面是一个可能的实现：

import java.io.IOException;
import java.util.*;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.*;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.GenericOptionsParser;

public class Merge {

    public static class MyMapper extends Mapper<LongWritable, Text, Text, IntWritable> {
        private Text line = new Text();

        public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException {
            String[] words = value.toString().split("\\s+");

            for (String word : words) {
                line.set(word);
                context.write(line, new IntWritable(1));
            }
        }
    }

    public static class MyReducer extends Reducer<Text, IntWritable, Text, IntWritable> {
        private IntWritable result = new IntWritable();

        public void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException {
            int sum = 0;
            for (IntWritable val : values) {
                sum += val.get();
            }
            result.set(sum);
            context.write(key, result);
        }
    }

    public static void main(String[] args) throws Exception {
        Configuration conf = new Configuration();
        String[] otherArgs = new GenericOptionsParser(conf, args).getRemainingArgs();
        if (otherArgs.length != 2) {
            System.err.println("Usage: Merge <in> <out>");
            System.exit(2);
        }
        Job job = Job.getInstance(conf, "Merge");
        job.setJarByClass(Merge.class);
        job.setMapperClass(MyMapper.class);
        job.setCombinerClass(MyReducer.class);
        job.setReducerClass(MyReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(IntWritable.class);
        FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
        FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
        System.exit(job.waitForCompletion(true) ? 0 : 1);
    }
}

在这个程序中，mapper函数将文件中的每一行作为输入，将每个单词作为键，并输出键值对，其中值为1。reducer函数将相同的键组合在一起，并将它们的值相加。最后，不重复的单词作为输出键，它们的出现次数作为输出值。

你可以将这个代码复制到你的Java文件中，并根据你的要求进行修改。请注意，你需要将输入和输出路径替换为你自己的路径。