source: sample/hadoop-0.17/tw/org/nchc/demo/SequentialPageRank.java @ 32

/*
 * Cloud9: A MapReduce Library for Hadoop
 * 
 * Licensed under the Apache License, Version 2.0 (the "License"); you
 * may not use this file except in compliance with the License. You may
 * obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0 
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
 * implied. See the License for the specific language governing
 * permissions and limitations under the License.
 */

package tw.org.nchc.demo;

import java.io.BufferedReader;
import java.io.FileInputStream;
import java.io.IOException;
import java.io.InputStreamReader;
import java.util.Collection;
import java.util.List;

import edu.uci.ics.jung.algorithms.cluster.WeakComponentGraphClusterer;
import edu.uci.ics.jung.algorithms.importance.PageRank;
import edu.uci.ics.jung.algorithms.importance.Ranking;
import edu.uci.ics.jung.graph.DirectedSparseGraph;
import edu.uci.ics.jung.graph.Graph;

/**
 * <p>
 * Program that computes PageRank for a graph using the <a
 * href="http://jung.sourceforge.net/">JUNG</a> package (2.0 alpha1). Program
 * takes two command-line arguments: the first is a file containing the graph
 * data, and the second is the random jump factor (a typical setting is 0.15).
 * </p>
 * 
 * <p>
 * The graph should be represented as an adjacency list. Each line should have
 * at least one token; tokens should be tab delimited. The first token
 * represents the unique id of the source node; subsequent tokens represent its
 * link targets (i.e., outlinks from the source node). For completeness, there
 * should be a line representing all nodes, even nodes without outlinks (those
 * lines will simply contain one token, the source node id).
 * </p>
 * 
 */
public class SequentialPageRank {

  private SequentialPageRank() {
  }

  /**
   * Runs the program
   */
  public static void main(String[] args) throws IOException {
    if (args.length != 2) {
      System.err
          .println("usage: SequentialPageRage [graph-adjacency-list] [random-jump-factor]");
      System.exit(-1);
    }
    String infile = args[0];
    float alpha = Float.parseFloat(args[1]);

    int edgeCnt = 0;
    DirectedSparseGraph<String, Integer> graph = new DirectedSparseGraph<String, Integer>();

    BufferedReader data = new BufferedReader(new InputStreamReader(
        new FileInputStream(infile)));

    String line;
    while ((line = data.readLine()) != null) {
      line.trim();
      String[] arr = line.split("\\t");

      for (int i = 1; i < arr.length; i++) {
        graph.addEdge(new Integer(edgeCnt++), arr[0], arr[i]);
      }
    }

    data.close();

    WeakComponentGraphClusterer<String, Integer> clusterer = new WeakComponentGraphClusterer<String, Integer>();

    Collection<Graph<String, Integer>> components = clusterer
        .transform(graph);
    int numComponents = components.size();
    System.out.println("Number of components: " + numComponents);
    System.out.println("Number of edges: " + graph.getEdgeCount());
    System.out.println("Number of nodes: " + graph.getVertexCount());
    System.out.println("Random jump factor: " + alpha);

    PageRank<String, Integer> ranker = new PageRank<String, Integer>(graph,
        alpha);
    ranker.evaluate();

    System.out.println("\nPageRank of nodes, in descending order:");
    for (Ranking<?> s : (List<Ranking<?>>) ranker.getRankings()) {
      String pmid = s.getRanked().toString();

      System.out.println(pmid + " " + s.rankScore);
    }
  }

}