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org.graphframes.examples

Graphs

Related Docs: class Graphs | package examples

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object Graphs extends Graphs

Example GraphFrames for testing the API

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  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. def ALSSyntheticData(): GraphFrame

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    Some synthetic data that sits in Spark.

    Some synthetic data that sits in Spark.

    No description available.

    Definition Classes
    Graphs
  5. final def asInstanceOf[T0]: T0

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  6. def chain(n: Long): GraphFrame

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    Returns a chain graph of the given size with Long ID type.

    Returns a chain graph of the given size with Long ID type. The vertex IDs are 0, 1, ..., n-1, and the edges are (0, 1), (1, 2), ...., (n-2, n-1).

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    Graphs
  7. def clone(): AnyRef

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    @throws( ... )
  8. def empty[T](implicit arg0: scala.reflect.api.JavaUniverse.TypeTag[T]): GraphFrame

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    Returns an empty GraphFrame of the given ID type.

    Returns an empty GraphFrame of the given ID type.

    Definition Classes
    Graphs
  9. final def eq(arg0: AnyRef): Boolean

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  10. def equals(arg0: Any): Boolean

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  11. def finalize(): Unit

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    @throws( classOf[java.lang.Throwable] )
  12. def friends: GraphFrame

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    Graph of friends in a social network.

    Graph of friends in a social network.

    Definition Classes
    Graphs
  13. final def getClass(): Class[_]

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  14. def gridIsingModel(sqlContext: SQLContext, n: Int): GraphFrame

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    Version of gridIsingModel with vStd, eStd set to 1.0.

    Version of gridIsingModel with vStd, eStd set to 1.0.

    Definition Classes
    Graphs
  15. def gridIsingModel(sqlContext: SQLContext, n: Int, vStd: Double, eStd: Double): GraphFrame

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    This method generates a grid Ising model with random parameters.

    This method generates a grid Ising model with random parameters.

    Ising models are probabilistic graphical models over binary variables xi. Each binary variable xi corresponds to one vertex, and it may take values -1 or +1. The probability distribution P(X) (over all xi) is parameterized by vertex factors ai and edge factors bij:

    P(X) = (1/Z) * exp[ \sum_i a_i x_i + \sum_{ij} b_{ij} x_i x_j ]

    where Z is the normalization constant (partition function). See Wikipedia for more information on Ising models.

    Each vertex is parameterized by a single scalar ai. Each edge is parameterized by a single scalar bij.

    n

    Length of one side of the grid. The grid will be of size n x n.

    vStd

    Standard deviation of normal distribution used to generate vertex factors "a". Default of 1.0.

    eStd

    Standard deviation of normal distribution used to generate edge factors "b". Default of 1.0.

    returns

    GraphFrame. Vertices have columns "id" and "a". Edges have columns "src", "dst", and "b". Edges are directed, but they should be treated as undirected in any algorithms run on this model. Vertex IDs are of the form "i,j". E.g., vertex "1,3" is in the second row and fourth column of the grid.

    Definition Classes
    Graphs
  16. def hashCode(): Int

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  17. final def isInstanceOf[T0]: Boolean

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

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  19. final def notify(): Unit

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  20. final def notifyAll(): Unit

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  21. def star(n: Long): GraphFrame

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    Returns a star graph with Long ID type, consisting of a central element indexed 0 (the root) and the n other leaf vertices 1, 2, ..., n.

    Returns a star graph with Long ID type, consisting of a central element indexed 0 (the root) and the n other leaf vertices 1, 2, ..., n.

    n

    the number of leaves

    Definition Classes
    Graphs
  22. final def synchronized[T0](arg0: ⇒ T0): T0

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  23. def toString(): String

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  24. def twoBlobs(blobSize: Int): GraphFrame

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    Two densely connected blobs (vertices 0->n-1 and n->2n-1) connected by a single edge (0->n)

    Two densely connected blobs (vertices 0->n-1 and n->2n-1) connected by a single edge (0->n)

    blobSize

    the size of each blob.

    Definition Classes
    Graphs
  25. final def wait(): Unit

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    @throws( ... )
  26. final def wait(arg0: Long, arg1: Int): Unit

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

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Inherited from Graphs

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