hadoop实现的一个简单的Pagerank例子

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 *      http://www.apache.org/licenses/LICENSE-2.0
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package org.apache.hadoop.examples;

import java.io.IOException;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.TaskTracker;
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 Pagerank {
	
  public static  double dampFactor = 0.85; 
  public static  int  iterations = 10 ; 
	
  public static class PagerankMapper 
       extends Mapper<LongWritable, Text, Text, DoubleWritable>{

	  public void map(LongWritable key, Text value, Context context
                    ) throws IOException, InterruptedException {
      String line = value.toString(); 
      String urls[] = line.split("\t"); 
      int urlSize = urls.length; 
//      TaskTracker.LOG.info("line: " + line + " urlSize: " + urlSize) ; 
      
      //urls[0] is the srcUrl. 
      double outLinkNum = urlSize-1; 
      double srcPageRank = 0.25 ;
      double pageRank_part = srcPageRank/outLinkNum; 
      for(int i = 1; i < urlSize; i++) { 
        context.write(new Text(urls[i]), new DoubleWritable(pageRank_part)); 
      } 
    }
  }
  
  public static class PagerankReducer 
       extends Reducer<Text,DoubleWritable,Text,DoubleWritable> {
    public void reduce(Text key, Iterable<DoubleWritable> values, 
                       Context context) throws IOException, InterruptedException {
//      TaskTracker.LOG.info("Reducer key: " + key) ; 
      double pageRank = 0; 
      for(DoubleWritable value : values) { 
        pageRank += value.get(); 
//        TaskTracker.LOG.info("Reducer value: " + value) ; 
      } 
      pageRank = 1-dampFactor+dampFactor*pageRank; 
      context.write(key, new DoubleWritable(pageRank)); 
    }
  }

  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: pagerank <in> <out>");
      System.exit(2);
    }
    
        Job job = new Job(conf, "pagerank");
        job.setJarByClass(Pagerank.class);
        job.setMapperClass(PagerankMapper.class);
        job.setCombinerClass(PagerankReducer.class);
        job.setReducerClass(PagerankReducer.class);
        job.setOutputKeyClass(Text.class);
        job.setOutputValueClass(DoubleWritable.class);
        FileInputFormat.addInputPath(job, new Path(otherArgs[0]));
        FileOutputFormat.setOutputPath(job, new Path(otherArgs[1]));
        System.exit(job.waitForCompletion(true) ? 0 : 1);
  }
}

输入数据格式为:

1\t2\t\4  //以\t隔开，即起始顶点\t边1\t边2...

这里有个问题就是一轮迭代结束后，顶点的边的信息无法传入下一轮中，如何改进? 

批量测试脚本;

for i in `seq 1 10` ; do  hadoop jar hadoop-examples-1.2.1.jar pagerank /test/soc-LiveJournal_final.txt /output ; hadoop fs -rmr /output ; done