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/*
 * Cloud9: A Hadoop toolkit for working with big data
 *
 * 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 edu.umd.cloud9.example.pagerank;

import java.io.BufferedReader;
import java.io.FileInputStream;
import java.io.IOException;
import java.io.InputStreamReader;
import java.util.Arrays;
import java.util.PriorityQueue;
import java.util.Set;

import org.apache.commons.cli.CommandLine;
import org.apache.commons.cli.CommandLineParser;
import org.apache.commons.cli.GnuParser;
import org.apache.commons.cli.HelpFormatter;
import org.apache.commons.cli.OptionBuilder;
import org.apache.commons.cli.Options;
import org.apache.commons.cli.ParseException;
import org.apache.hadoop.util.ToolRunner;

import edu.uci.ics.jung.algorithms.cluster.WeakComponentClusterer;
import edu.uci.ics.jung.algorithms.importance.Ranking;
import edu.uci.ics.jung.algorithms.scoring.PageRank;
import edu.uci.ics.jung.graph.DirectedSparseGraph;

/**
 * 

* Program that computes PageRank for a graph using the JUNG 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). *

* *

* 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). *

* * @author Jimmy Lin */ public class SequentialPageRank { private SequentialPageRank() {} private static final String INPUT = "input"; private static final String JUMP = "jump"; @SuppressWarnings({ "static-access" }) public static void main(String[] args) throws IOException { Options options = new Options(); options.addOption(OptionBuilder.withArgName("path").hasArg() .withDescription("input path").create(INPUT)); options.addOption(OptionBuilder.withArgName("val").hasArg() .withDescription("random jump factor").create(JUMP)); CommandLine cmdline = null; CommandLineParser parser = new GnuParser(); try { cmdline = parser.parse(options, args); } catch (ParseException exp) { System.err.println("Error parsing command line: " + exp.getMessage()); System.exit(-1); } if (!cmdline.hasOption(INPUT)) { System.out.println("args: " + Arrays.toString(args)); HelpFormatter formatter = new HelpFormatter(); formatter.setWidth(120); formatter.printHelp(SequentialPageRank.class.getName(), options); ToolRunner.printGenericCommandUsage(System.out); System.exit(-1); } String infile = cmdline.getOptionValue(INPUT); float alpha = cmdline.hasOption(JUMP) ? Float.parseFloat(cmdline.getOptionValue(JUMP)) : 0.15f; int edgeCnt = 0; DirectedSparseGraph graph = new DirectedSparseGraph(); 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(); WeakComponentClusterer clusterer = new WeakComponentClusterer(); Set> 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); // Compute PageRank. PageRank ranker = new PageRank(graph, alpha); ranker.evaluate(); // Use priority queue to sort vertices by PageRank values. PriorityQueue> q = new PriorityQueue>(); int i = 0; for (String pmid : graph.getVertices()) { q.add(new Ranking(i++, ranker.getVertexScore(pmid), pmid)); } // Print PageRank values. System.out.println("\nPageRank of nodes, in descending order:"); Ranking r = null; while ((r = q.poll()) != null) { System.out.println(r.rankScore + "\t" + r.getRanked()); } } }




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