Java PageRankParameters类代码示例

import science.atlarge.graphalytics.domain.algorithms.PageRankParameters; //导入依赖的package包/类
private PageRankOutput execute(GraphStructure graph, PageRankParameters parameters, boolean directed)
		throws Exception {
	File edgesFile = File.createTempFile("edges.", ".txt");
	File verticesFile = File.createTempFile("vertices.", ".txt");
	File outputFile = File.createTempFile("output.", ".txt");

	Utils.writeEdgeToFile(graph, directed, edgesFile);
	Utils.writeVerticesToFile(graph, verticesFile);

	String jobId = "RandomJobId";
	String logPath = "RandomLogDir";

	PageRankJob job = new PageRankJob(
			Utils.loadConfiguration(),
			verticesFile.getAbsolutePath(), edgesFile.getAbsolutePath(),
			directed, parameters, jobId, logPath);
	job.setOutputFile(outputFile);
	job.run();
	
	return new PageRankOutput(Utils.readResults(outputFile, Double.class));
}
 

import science.atlarge.graphalytics.domain.algorithms.PageRankParameters; //导入依赖的package包/类
@Test
public final void testDirectedPageRankOnValidationGraph() throws Exception {
	final String inputPath = "/validation-graphs/pr/dir-input";
	final String outputPath = "/validation-graphs/pr/dir-output";
	final float dampingFactor = 0.85f;
	final int numberOfIterations = 14;

	GraphStructure inputGraph = GraphParser.parseGraphStructureFromVertexBasedDataset(
			getClass().getResourceAsStream(inputPath), true);

	PageRankParameters parameters = new PageRankParameters(dampingFactor, numberOfIterations);
	PageRankOutput executionResult = executeDirectedPageRank(inputGraph, parameters);

	validatePageRank(executionResult, outputPath);
}
 

import science.atlarge.graphalytics.domain.algorithms.PageRankParameters; //导入依赖的package包/类
@Test
public final void testUndirectedPageRankOnValidationGraph() throws Exception {
	final String inputPath = "/validation-graphs/pr/undir-input";
	final String outputPath = "/validation-graphs/pr/undir-output";
	final float dampingFactor = 0.85f;
	final int numberOfIterations = 26;

	GraphStructure inputGraph = GraphParser.parseGraphStructureFromVertexBasedDataset(
			getClass().getResourceAsStream(inputPath), true);

	PageRankParameters parameters = new PageRankParameters(dampingFactor, numberOfIterations);
	PageRankOutput executionResult = executeUndirectedPageRank(inputGraph, parameters);

	validatePageRank(executionResult, outputPath);
}
 

import science.atlarge.graphalytics.domain.algorithms.PageRankParameters; //导入依赖的package包/类
@Override
public void run(RunSpecification runSpecification) throws PlatformExecutionException {

	BenchmarkRun benchmarkRun = runSpecification.getBenchmarkRun();
	BenchmarkRunSetup benchmarkRunSetup = runSpecification.getBenchmarkRunSetup();
	RuntimeSetup runtimeSetup = runSpecification.getRuntimeSetup();

	PowergraphJob job;
	Object params = benchmarkRun.getAlgorithmParameters();

	String logPath = benchmarkRunSetup.getLogDir().resolve("platform").toString();

	boolean graphDirected = benchmarkRun.getFormattedGraph().isDirected();
	String vertexFilePath = runtimeSetup.getLoadedGraph().getVertexPath();
	String edgeFilePath = runtimeSetup.getLoadedGraph().getEdgePath();

	switch(benchmarkRun.getAlgorithm()) {
		case BFS:
			job = new BreadthFirstSearchJob(benchmarkConfig, vertexFilePath, edgeFilePath,
					graphDirected, (BreadthFirstSearchParameters) params, benchmarkRun.getId(), logPath);
			break;
		case WCC:
			job = new ConnectedComponentsJob(benchmarkConfig, vertexFilePath, edgeFilePath,
					graphDirected, benchmarkRun.getId(), logPath);
			break;
		case LCC:
			job = new LocalClusteringCoefficientJob(benchmarkConfig, vertexFilePath, edgeFilePath,
					graphDirected, benchmarkRun.getId(), logPath);
			break;
		case CDLP:
			job = new CommunityDetectionJob(benchmarkConfig, vertexFilePath, edgeFilePath,
					graphDirected, (CommunityDetectionLPParameters) params, benchmarkRun.getId(), logPath);
			break;
		case PR:
			job = new PageRankJob(benchmarkConfig, vertexFilePath, edgeFilePath,
					graphDirected, (PageRankParameters) params, benchmarkRun.getId(), logPath);
			break;
		case SSSP:
			job = new SingleSourceShortestPathsJob(benchmarkConfig, vertexFilePath, edgeFilePath,
					graphDirected, (SingleSourceShortestPathsParameters) params, benchmarkRun.getId(), logPath);
			break;
		default:
			throw new PlatformExecutionException("Unsupported algorithm");
	}

	if (benchmarkRunSetup.isOutputRequired()) {
		Path outputFile = benchmarkRunSetup.getOutputDir().resolve(benchmarkRun.getName());
		job.setOutputFile(outputFile.toFile());
	}

	try {
		job.run();
	} catch (IOException|InterruptedException e) {
		throw new PlatformExecutionException("failed to execute command", e);
	}

}
 

import science.atlarge.graphalytics.domain.algorithms.PageRankParameters; //导入依赖的package包/类
public PageRankJob(Configuration config, String verticesPath, String edgesPath,
				   boolean graphDirected, PageRankParameters params, String jobId, String logPath) {
	super(config, verticesPath, edgesPath, graphDirected, jobId, logPath);
	this.params = params;
}
 

import science.atlarge.graphalytics.domain.algorithms.PageRankParameters; //导入依赖的package包/类
@Override
public PageRankOutput executeDirectedPageRank(GraphStructure graph, PageRankParameters parameters)
		throws Exception {
	return execute(graph, parameters, true);
}
 

import science.atlarge.graphalytics.domain.algorithms.PageRankParameters; //导入依赖的package包/类
@Override
public PageRankOutput executeUndirectedPageRank(GraphStructure graph, PageRankParameters parameters)
		throws Exception {
	return execute(graph, parameters, false);
}
 

import science.atlarge.graphalytics.domain.algorithms.PageRankParameters; //导入依赖的package包/类
/**
 * Executes the platform-specific implementation of the PageRank algorithm on an in-memory directed graph with given
 * parameters, and returns the output of the execution.
 * <p/>
 * This function is called with sample graphs and the output is compared with known-correct results.
 *
 * @param graph      the graph to execute the PageRank algorithm on
 * @param parameters the values for the algorithm parameters to use
 * @return the output of the PageRank algorithm
 * @throws Exception
 */
public abstract PageRankOutput executeDirectedPageRank(GraphStructure graph, PageRankParameters parameters)
		throws Exception;
 

import science.atlarge.graphalytics.domain.algorithms.PageRankParameters; //导入依赖的package包/类
/**
 * Executes the platform-specific implementation of the PageRank algorithm on an in-memory undirected graph with
 * given parameters, and returns the output of the execution.
 * <p/>
 * This function is called with sample graphs and the output is compared with known-correct results.
 *
 * @param graph      the graph to execute the PageRank algorithm on
 * @param parameters the values for the algorithm parameters to use
 * @return the output of the PageRank algorithm
 * @throws Exception
 */
public abstract PageRankOutput executeUndirectedPageRank(GraphStructure graph, PageRankParameters parameters)
		throws Exception;