Hadoop MultipleInputs组合在同一个映射器中

Question

说，我们接受两个输入文件：

file1 content: a b c d

file2 content: b c d e

我希望TokenizerMapper.class在

下创建结果

ab ac ad ae bd bc bd be cb cc cd ce db dc dd de

一个词与另一个词对齐 我将file1内容存储到一个数组中，将file2内容存储到另一个数组中 并运行循环来创建它。 问题是如何使用MultipleInputs将两个文件内容组合在同一个类中？

自爆代码有MultipleIputs：

public class WordCount {

  public static class TokenizerMapper
       extends Mapper<Object, Text, Text, IntWritable>{

    private final static IntWritable one = new IntWritable(1);
    private Text word = new Text();

    public void map(Object key, Text value, Context context
                    ) throws IOException, InterruptedException {
      StringTokenizer itr = new StringTokenizer(value.toString());
      while (itr.hasMoreTokens()) {
        word.set(itr.nextToken());
        context.write(word, one);
      }
    }
  }

  public static class IntSumReducer
       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();
    Job job = Job.getInstance(conf, "word count");
    job.setJarByClass(WordCount.class);
    job.setMapperClass(TokenizerMapper.class);
    job.setCombinerClass(IntSumReducer.class);
    job.setReducerClass(IntSumReducer.class);
    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(IntWritable.class);
    //FileInputFormat.addInputPath(job, new Path(args[0]));
    MultipleInputs.addInputPath(job, new Path(args[0]), TextInputFormat.class, TokenizerMapper.class);
    MultipleInputs.addInputPath(job, new Path(args[1]), TextInputFormat.class, TokenizerMapper.class);
    FileOutputFormat.setOutputPath(job, new Path(args[2]));
    System.exit(job.waitForCompletion(true) ? 0 : 1);
  }
}