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pegasus.spark.cc

PACC

Related Docs: object PACC | package cc

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class PACC extends Serializable

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Instance Constructors

  1. new PACC()

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Type Members

  1. case class Config(localThreshold: Int = 100000, numPartitions: Int = 80, inputPath: String = "", outputPath: String = "") extends Product with Serializable

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    command line interface with default parameters

    command line interface with default parameters

    localThreshold

    if the number of remaining edges are lower than this value, pacc run a single machine algorithm (LocalCC)

    numPartitions

    the number of partitions

    inputPath

    input file path

    outputPath

    output file path

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 APP_NAME: String

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  5. val EXEC_NAME: String

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  6. val VERSION: String

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  7. final def asInstanceOf[T0]: T0

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  8. def ccComputation(remains: RDD[(Long, Long)], numPartitions: Int): RDD[(Long, Long)]

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    CC-Computation operation.

    CC-Computation operation. This operation conducts LocalCC in each partition.

    remains

    input RDD

    numPartitions

    the number of partitions

    returns

    final output RDD containing connected components

  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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    @throws( classOf[java.lang.Throwable] )
  13. final def getClass(): Class[_]

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  14. def hashCode(): Int

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  15. final def isInstanceOf[T0]: Boolean

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  16. def largeStar(inputRDD: RDD[(Long, Long)], numPartitions: Int, round: Int, tmpPath: String): (RDD[(Long, Long)], Long, Long, Long, Long)

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    PA-Large-Star Operation.

    PA-Large-Star Operation. For each node n, this operation links each large neighbor v to the minimum node mcu(p(v)) in the same partition p(v) that contains the neighbor v.

    inputRDD

    the input rdd

    numPartitions

    the number of partitions

    round

    current round number

    tmpPath

    the temporary path to save the intermediate results

    returns

    (RDD for next round input, # changed edges, # of 'out' edges, # filtered 'cc' edges, # filtered 'in' edges)

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

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  18. final def notify(): Unit

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  19. final def notifyAll(): Unit

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  20. def run(inputPath: String, localThreshold: Int, numPartitions: Int, sc: SparkContext): RDD[(Long, Long)]

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    submit the spark job.

    submit the spark job.

    inputPath

    input file path.

    localThreshold

    if the number of remaining edges are lower than this value, pacc run a single machine algorithm (LocalCC).

    numPartitions

    the number of partitions

    sc

    spark context.

    returns

    an RDD containing connected components

  21. def runByCLI(args: Array[String]): Unit

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    run by command line interface

  22. def smallStar(inputRDD: RDD[(Long, Long)], numPartitions: Int, round: Int, tmpPath: String): (RDD[(Long, Long)], Long, Long, Long)

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    PA-Small-Star Operation.

    PA-Small-Star Operation. For each node n, this operation links each small neighbor v to the minimum node mcu(p(v)) in the same partition p(v) that contains the neighbor v.

    inputRDD

    the input rdd

    numPartitions

    the number of partitions

    round

    current round number

    tmpPath

    the temporary path to save the intermediate results

    returns

    (RDD for next round input, # changed edges, # of 'out' edges, # filtered 'in' edges)

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

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  24. def toString(): String

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  25. final def wait(): Unit

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

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

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