Class GraphGenerators

Object
org.apache.spark.graphx.util.GraphGenerators

public class GraphGenerators extends Object
A collection of graph generating functions.
  • Constructor Details

    • GraphGenerators

      public GraphGenerators()
  • Method Details

    • RMATa

      public static double RMATa()
    • RMATb

      public static double RMATb()
    • RMATd

      public static double RMATd()
    • logNormalGraph

      public static Graph<Object,Object> logNormalGraph(SparkContext sc, int numVertices, int numEParts, double mu, double sigma, long seed)
      Generate a graph whose vertex out degree distribution is log normal.

      The default values for mu and sigma are taken from the Pregel paper:

      Grzegorz Malewicz, Matthew H. Austern, Aart J.C Bik, James C. Dehnert, Ilan Horn, Naty Leiser, and Grzegorz Czajkowski. 2010. Pregel: a system for large-scale graph processing. SIGMOD '10.

      If the seed is -1 (default), a random seed is chosen. Otherwise, use the user-specified seed.

      Parameters:
      sc - Spark Context
      numVertices - number of vertices in generated graph
      numEParts - (optional) number of partitions
      mu - (optional, default: 4.0) mean of out-degree distribution
      sigma - (optional, default: 1.3) standard deviation of out-degree distribution
      seed - (optional, default: -1) seed for RNGs, -1 causes a random seed to be chosen
      Returns:
      Graph object
    • RMATc

      public static double RMATc()
    • generateRandomEdges

      public static Edge<Object>[] generateRandomEdges(int src, int numEdges, int maxVertexId, long seed)
    • rmatGraph

      public static Graph<Object,Object> rmatGraph(SparkContext sc, int requestedNumVertices, int numEdges)
      A random graph generator using the R-MAT model, proposed in "R-MAT: A Recursive Model for Graph Mining" by Chakrabarti et al.

      See http://www.cs.cmu.edu/~christos/PUBLICATIONS/siam04.pdf.

      Parameters:
      sc - (undocumented)
      requestedNumVertices - (undocumented)
      numEdges - (undocumented)
      Returns:
      (undocumented)
    • gridGraph

      public static Graph<scala.Tuple2<Object,Object>,Object> gridGraph(SparkContext sc, int rows, int cols)
      Create rows by cols grid graph with each vertex connected to its row+1 and col+1 neighbors. Vertex ids are assigned in row major order.

      Parameters:
      sc - the spark context in which to construct the graph
      rows - the number of rows
      cols - the number of columns

      Returns:
      A graph containing vertices with the row and column ids as their attributes and edge values as 1.0.
    • starGraph

      public static Graph<Object,Object> starGraph(SparkContext sc, int nverts)
      Create a star graph with vertex 0 being the center.

      Parameters:
      sc - the spark context in which to construct the graph
      nverts - the number of vertices in the star

      Returns:
      A star graph containing nverts vertices with vertex 0 being the center vertex.
    • org$apache$spark$internal$Logging$$log_

      public static org.slf4j.Logger org$apache$spark$internal$Logging$$log_()
    • org$apache$spark$internal$Logging$$log__$eq

      public static void org$apache$spark$internal$Logging$$log__$eq(org.slf4j.Logger x$1)
    • LogStringContext

      public static org.apache.spark.internal.Logging.LogStringContext LogStringContext(scala.StringContext sc)