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Scientific distributed graph computing made easy
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Booking 1 core on 4 nodes for 1 hour on the dellc6220 rack of the NEF cluster: ResourceManager rm = new Nef(); NodeNameSet nodes = rm.bookNodes(4, 1, 3600, "dellc6220");

Start BigGrph on 4 nodes (booking 2 cores per node during 1 hour) on the dellc6220 rack of a cluster whose the frontal is nef-frontal: BigGrphCluster cluster = BigGrphCluster.torque("jdoe", "nef-frontal", 4, 2, 3600, "dellc6220");

Loading (a subset of) the Twitter graph (): EdgeListDataSet dataset = new EdgeListDataSet("twitter-small.tsv", cluster); BigAdjacencyTable g = dataset.load(false, true);

Computing the average degree of the Twitter graph: long avgDegree = g.getAverageDegree();

Computing the diameter of the Twitter graph, using the iFUB algorithm, setting the src vertex using a 2-sweep search: long diameter = g.getDiameter_iFUB();

Computing distance distribution from vertex 45: BFSDistanceAssigner bfsResult = g.bfs(45); DistributionForLongs d = new DistanceDistribution(bfsResult.getDistancesMap());