GraphGenerators

Value Members

1. final def !=(arg0: Any): Boolean

   

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2. final def ##(): Int

   

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3. final def ==(arg0: Any): Boolean

   

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4. val RMATa: Double

   

5. val RMATb: Double

   

6. val RMATc: Double

   

7. val RMATd: Double

   

8. final def asInstanceOf[T0]: T0

   

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9. def clone(): AnyRef

   

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10. final def eq(arg0: AnyRef): Boolean

    

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11. def equals(arg0: Any): Boolean

    

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12. def finalize(): Unit

    

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13. def generateRandomEdges(src: Int, numEdges: Int, maxVertexId: Int, seed: Long = 1): Array[Edge[Int]]

    

14. final def getClass(): Class[_]

    

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15. def gridGraph(sc: SparkContext, rows: Int, cols: Int): Graph[(Int, Int), Double]

    

    Create rows by cols grid graph with each vertex connected to its row+1 and col+1 neighbors.

    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.

    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.

16. def hashCode(): Int

    

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17. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

    

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18. final def isInstanceOf[T0]: Boolean

    

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19. def isTraceEnabled(): Boolean

    

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20. def log: Logger

    

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21. def logDebug(msg: ⇒ String, throwable: Throwable): Unit

    

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22. def logDebug(msg: ⇒ String): Unit

    

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23. def logError(msg: ⇒ String, throwable: Throwable): Unit

    

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24. def logError(msg: ⇒ String): Unit

    

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25. def logInfo(msg: ⇒ String, throwable: Throwable): Unit

    

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26. def logInfo(msg: ⇒ String): Unit

    

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27. def logName: String

    

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28. def logNormalGraph(sc: SparkContext, numVertices: Int, numEParts: Int = 0, mu: Double = 4.0, sigma: Double = 1.3, seed: Long = 1): Graph[Long, Int]

    

    Generate a graph whose vertex out degree distribution is log normal.

    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.

    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

29. def logTrace(msg: ⇒ String, throwable: Throwable): Unit

    

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30. def logTrace(msg: ⇒ String): Unit

    

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31. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

    

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32. def logWarning(msg: ⇒ String): Unit

    

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33. final def ne(arg0: AnyRef): Boolean

    

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34. final def notify(): Unit

    

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35. final def notifyAll(): Unit

    

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36. def rmatGraph(sc: SparkContext, requestedNumVertices: Int, numEdges: Int): Graph[Int, Int]

    

    A random graph generator using the R-MAT model, proposed in "R-MAT: A Recursive Model for Graph Mining" by Chakrabarti et al.

    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.

37. def starGraph(sc: SparkContext, nverts: Int): Graph[Int, Int]

    

    Create a star graph with vertex 0 being the center.

    Create a star graph with vertex 0 being the center.

    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.

38. final def synchronized[T0](arg0: ⇒ T0): T0

    

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39. def toString(): String

    

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40. final def wait(): Unit

    

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41. final def wait(arg0: Long, arg1: Int): Unit

    

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42. final def wait(arg0: Long): Unit

    

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