hadoop学习笔记-6-倒排索引InverseIndex

介绍

倒排索引是将文章中的单词挑出来，排序，便于检索。利用map-reduce思想来实现，如下：

原始文本及内容：

doc1.txt：MapReduce is simple

doc2.txt：MapReduce ispowerful is simple

doc3.txt：Hello MapReduce byeMapReduce

那么输出结果应该是这样子的：

MapReduce：doc1.txt:1;doc2.txt:1;doc3.txt:2;

is：doc1.txt:1;doc2.txt:2;

simple：doc1.txt:1;doc2.txt:1;

Hello：doc3.txt:1;

MapReduce：doc3.txt:1;

其中冒号之前表示文档，之后表示在这个文档中出现的次数，分号分隔各个文档。例如：MapReduce：doc1.txt:1;doc2.txt:1;doc3.txt:2; 表示MapReduce在doc1.txt中出现一次，在doc2.txt中出现一次，在doc3.txt中出现两次。

明白了原理之后，看如何用MapReduce来实现。

原始文件作为输入，经过Map之后变成以下格式：

经过Combiner之后变成以下格式：

经过reduce之后变成以下内容：

 

可以考虑考虑为什么这么做。

 

源代码

Mapper类：

 

package cn.kepu.littlefu;
 
import java.io.IOException;
 
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapred.MapReduceBase;
import org.apache.hadoop.mapred.Mapper;
import org.apache.hadoop.mapred.OutputCollector;
import org.apache.hadoop.mapred.Reporter;
 
 
@SuppressWarnings("deprecation")
public class InverseIndexMapper extends MapReduceBaseimplements Mapper {
   
     StringinputFile;
   
     public voidconfigure(JobConf job) {
         StringinputFileFull = job.get("map.input.file");
        inputFile =inputFileFull.substring(inputFileFull.lastIndexOf("/")+1);
      }
   
     @Override 
      public void map(Object key, Text value,OutputCollector output, Reporter reporter) throwsIOException{
 
        Stringline = value.toString();
        String[]word = line.split(" ");
       
        for(Strings : word){
            //output
            output.collect(newText(s+":"+inputFile), new Text("1"));
        }
       
    }
 
}

 

Combiner类：

 

package cn.kepu.littlefu;
 
import java.io.IOException;
import java.util.Iterator;
 
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.MapReduceBase;
import org.apache.hadoop.mapred.OutputCollector;
import org.apache.hadoop.mapred.Reducer;
import org.apache.hadoop.mapred.Reporter;
 
public class InverseIndexCombiner extendsMapReduceBase implements
Reducer{
 
    @Override
    public void reduce(Text key, Iteratorvalues,
            OutputCollector output, Reporter reporter)
            throwsIOException {
        //total
        int sum =0;
        while(values.hasNext()){
            sum+= Integer.parseInt(values.next().toString());
        }
        //outputposition
        int pos =key.toString().indexOf(":");
        //output
        TextoutKey = new Text(key.toString().subSequence(0, pos).toString());
        TextoutValue = new Text(key.toString().substring(pos+1).toString()+":"+sum);
        System.out.print("combiner:");
        output.collect(outKey, outValue);
    }
 
}
 

 

Reduce类：

 

package cn.kepu.littlefu;
 
import java.io.IOException;
import java.util.Iterator;
 
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.MapReduceBase;
import org.apache.hadoop.mapred.OutputCollector;
import org.apache.hadoop.mapred.Reducer;
import org.apache.hadoop.mapred.Reporter;
 
public class InverseIndexReducer extends MapReduceBaseimplements
        Reducer {
 
    @Override
    public voidreduce(Text key, Iterator values,
            OutputCollector output, Reporter reporter)
            throwsIOException {
       
        StringfileList = new String();
        while(values.hasNext()){
            fileList+= values.next().toString()+";";
        }
        //output
        output.collect(key,new Text(fileList));
    }
}
 

 

Main类：

package cn.kepu.littlefu;
 
import java.io.IOException;
 
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.FileInputFormat;
import org.apache.hadoop.mapred.FileOutputFormat;
import org.apache.hadoop.mapred.JobClient;
import org.apache.hadoop.mapred.JobConf;
 
public class InverseIndexLuncher {
   
    public staticvoid main(String[] args) throws IOException{
   
        if(args.length != 2){
            System.err.println("Usage :InverseIndex  
");
            System.exit(-1);
        }
       
        JobConfconf = new JobConf(InverseIndexLuncher.class);
        conf.setJobName("inverseindex");
       
        FileInputFormat.addInputPath(conf,new Path(args[0]));
        FileOutputFormat.setOutputPath(conf,new Path(args[1]));
       
        conf.setMapperClass(InverseIndexMapper.class);
        conf.setCombinerClass(InverseIndexCombiner.class);
        conf.setReducerClass(InverseIndexReducer.class);
       
        conf.setMapOutputKeyClass(Text.class);
        conf.setMapOutputValueClass(Text.class);
       
        conf.setOutputKeyClass(Text.class);
        conf.setOutputValueClass(Text.class);
       
        JobClient.runJob(conf);
    }
}
 

 

 

运行截图

 

 

 

 

参考：《实战Hadoop--开启通向云计算的捷径》P74-P83