Packages

  • package root
    Definition Classes
    root
  • package org
    Definition Classes
    root
  • package apache
    Definition Classes
    org
  • package spark

    Core Spark functionality.

    Core Spark functionality. org.apache.spark.SparkContext serves as the main entry point to Spark, while org.apache.spark.rdd.RDD is the data type representing a distributed collection, and provides most parallel operations.

    In addition, org.apache.spark.rdd.PairRDDFunctions contains operations available only on RDDs of key-value pairs, such as groupByKey and join; org.apache.spark.rdd.DoubleRDDFunctions contains operations available only on RDDs of Doubles; and org.apache.spark.rdd.SequenceFileRDDFunctions contains operations available on RDDs that can be saved as SequenceFiles. These operations are automatically available on any RDD of the right type (e.g. RDD[(Int, Int)] through implicit conversions.

    Java programmers should reference the org.apache.spark.api.java package for Spark programming APIs in Java.

    Classes and methods marked with Experimental are user-facing features which have not been officially adopted by the Spark project. These are subject to change or removal in minor releases.

    Classes and methods marked with Developer API are intended for advanced users want to extend Spark through lower level interfaces. These are subject to changes or removal in minor releases.

    Definition Classes
    apache
  • package graphx

    ALPHA COMPONENT GraphX is a graph processing framework built on top of Spark.

    ALPHA COMPONENT GraphX is a graph processing framework built on top of Spark.

    Definition Classes
    spark
  • package impl
    Definition Classes
    graphx
  • EdgeActiveness
  • EdgeRDDImpl
  • GraphImpl
  • VertexRDDImpl

object GraphImpl extends Serializable

Source
GraphImpl.scala
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Serializable, Serializable, AnyRef, Any
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  1. GraphImpl
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  1. final def !=(arg0: Any): Boolean
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  4. def apply[VD, ED](vertices: VertexRDD[VD], edges: EdgeRDD[ED])(implicit arg0: ClassTag[VD], arg1: ClassTag[ED]): GraphImpl[VD, ED]

    Create a graph from a VertexRDD and an EdgeRDD with arbitrary replicated vertices.

    Create a graph from a VertexRDD and an EdgeRDD with arbitrary replicated vertices. The VertexRDD must already be set up for efficient joins with the EdgeRDD by calling VertexRDD.withEdges or an appropriate VertexRDD constructor.

  5. def apply[VD, ED](vertices: RDD[(VertexId, VD)], edges: RDD[Edge[ED]], defaultVertexAttr: VD, edgeStorageLevel: StorageLevel, vertexStorageLevel: StorageLevel)(implicit arg0: ClassTag[VD], arg1: ClassTag[ED]): GraphImpl[VD, ED]

    Create a graph from vertices and edges, setting missing vertices to defaultVertexAttr.

  6. def apply[VD, ED](edges: RDD[Edge[ED]], defaultVertexAttr: VD, edgeStorageLevel: StorageLevel, vertexStorageLevel: StorageLevel)(implicit arg0: ClassTag[VD], arg1: ClassTag[ED]): GraphImpl[VD, ED]

    Create a graph from edges, setting referenced vertices to defaultVertexAttr.

  7. final def asInstanceOf[T0]: T0
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  8. def clone(): AnyRef
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  9. final def eq(arg0: AnyRef): Boolean
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  11. def finalize(): Unit
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  12. def fromEdgePartitions[VD, ED](edgePartitions: RDD[(PartitionID, EdgePartition[ED, VD])], defaultVertexAttr: VD, edgeStorageLevel: StorageLevel, vertexStorageLevel: StorageLevel)(implicit arg0: ClassTag[VD], arg1: ClassTag[ED]): GraphImpl[VD, ED]

    Create a graph from EdgePartitions, setting referenced vertices to defaultVertexAttr.

  13. def fromExistingRDDs[VD, ED](vertices: VertexRDD[VD], edges: EdgeRDD[ED])(implicit arg0: ClassTag[VD], arg1: ClassTag[ED]): GraphImpl[VD, ED]

    Create a graph from a VertexRDD and an EdgeRDD with the same replicated vertex type as the vertices.

    Create a graph from a VertexRDD and an EdgeRDD with the same replicated vertex type as the vertices. The VertexRDD must already be set up for efficient joins with the EdgeRDD by calling VertexRDD.withEdges or an appropriate VertexRDD constructor.

  14. final def getClass(): Class[_]
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  20. final def synchronized[T0](arg0: ⇒ T0): T0
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  21. def toString(): String
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  23. final def wait(arg0: Long, arg1: Int): Unit
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