Hadoop 倒排索引的Java程序

Hadoop倒排索引是一种常见的分布式计算应用，它可以高效地处理大规模的文本数据，并生成倒排索引。下面是一个基于Java实现的Hadoop倒排索引程序的示例代码：

import java.io.IOException;
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;

public class InvertedIndex {

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

    private Text word = new Text();
    private Text docID = new Text();

    public void map(Object key, Text value, Context context)
        throws IOException, InterruptedException {
      String[] line = value.toString().split("\t");
      String id = line[0];
      String text = line[1];
      docID.set(id);
      StringTokenizer itr = new StringTokenizer(text);
      while (itr.hasMoreTokens()) {
        word.set(itr.nextToken());
        context.write(word, docID);
      }
    }
  }

  public static class IntSumReducer extends Reducer<Text, Text, Text, Text> {

    public void reduce(Text key, Iterable<Text> values, Context context)
        throws IOException, InterruptedException {
      StringBuilder sb = new StringBuilder();
      for (Text val : values) {
        sb.append(val.toString()).append(",");
      }
      context.write(key, new Text(sb.toString()));
    }
  }

  public static void main(String[] args) throws Exception {
    Configuration conf = new Configuration();
    Job job = Job.getInstance(conf, "inverted index");
    job.setJarByClass(InvertedIndex.class);
    job.setMapperClass(TokenizerMapper.class);
    job.setCombinerClass(IntSumReducer.class);
    job.setReducerClass(IntSumReducer.class);
    job.setOutputKeyClass(Text.class);
    job.setOutputValueClass(Text.class);
    FileInputFormat.addInputPath(job, new Path(args[0]));
    FileOutputFormat.setOutputPath(job, new Path(args[1]));
    System.exit(job.waitForCompletion(true) ? 0 : 1);
  }
}

该程序包含两个Mapper和Reducer类。第一个Mapper类用于将输入文本数据切分成单词，并将单词作为Key，文档ID作为Value输出。第一个Reducer类用于将相同单词的文档ID合并为一个字符串，并将单词作为Key，文档ID字符串作为Value输出。在第一个Mapper和Reducer之后，可以添加多个Mapper和Reducer进行进一步的处理和优化。

要运行该程序，可以使用以下命令：

hadoop jar InvertedIndex.jar InvertedIndex input output

其中，InvertedIndex.jar是程序的打包文件，input是输入数据的路径，output是输出结果的路径。