对于两个输入文件，即文件A 和文件B ,请编写MapReduce程序，对两个文件进行合并排除其中重复的内容，得到一个新的输出文件C。

package org.apache.hadoop.examples;
import java.util.HashMap;
import java.io.IOException;
import java.util.Iterator;
import java.util.Map;
import java.util.StringTokenizer;
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.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 A_formatSameString {
    public A_formatSameString() {
    }

    public static void main(String[] args) throws Exception {
        Configuration conf = new Configuration();
        conf.set("fs.defaultFS", "hdfs://localhost:9000");
        String[] otherArgs = new String[]{"input","output"};
        if(otherArgs.length < 2) {
            System.err.println("Usage: wordcount <in> [<in>...] <out>");
            System.exit(2);
        }

        Job job = Job.getInstance(conf, "clearSame");
        job.setJarByClass(A_formatSameString.class);
        job.setMapperClass(A_formatSameString.TokenizerMapper.class);
        job.setCombinerClass(A_formatSameString.IntSumReducer.class);
        job.setReducerClass(A_formatSameString.IntSumReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(Text.class);

        for(int i = 0; i < otherArgs.length - 1; ++i) {
            FileInputFormat.addInputPath(job, new Path(otherArgs[i]));
        }

        FileOutputFormat.setOutputPath(job, new Path(otherArgs[otherArgs.length - 1]));
        System.exit(job.waitForCompletion(true)?0:1);
    }

    public static class IntSumReducer extends Reducer<Text, Text, Text, Text> {
    	private Text word2 = new Text();

        public IntSumReducer() {
        }

        public void reduce(Text key, Iterable<Text> values, Reducer<Text, Text, Text, Text>.Context context) throws IOException, InterruptedException {
        	Map dict = new HashMap();
            for(Iterator i$ = values.iterator(); i$.hasNext(); ) {
            	Text value = (Text)i$.next();
            	if(!dict.containsKey(value)){
                	dict.put(value,1);
                	this.word2.set(value);
                	context.write(key, this.word2);
            	}

            }
            //System.out.println(key.toString()+"\n"+result.toString());
        }
    }

    public static class TokenizerMapper extends Mapper<Object, Text, Text, Text> {
        private static final IntWritable one = new IntWritable(1);
        private Text word = new Text();
        private Text word2 = new Text();
        public TokenizerMapper() {
        }

        public void map(Object key, Text value, Mapper<Object, Text, Text, Text>.Context context) throws IOException, InterruptedException {
            StringTokenizer itr = new StringTokenizer(value.toString());
            //System.out.println(itr.toString());
            while(itr.hasMoreTokens()) {
            	String tmpstr = itr.nextToken();
            	String tmpstr2 = itr.nextToken();
                this.word.set(tmpstr);
                this.word2.set(tmpstr2);
                //System.out.println(tmpstr);
                context.write(this.word, this.word2);
            }

        }
    }
}