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class TraceGenerator extends Serializable

This class is responsible to generate random traces of random event types. All the trace will have length randomly picked (using uniform distribution) between minTraceSize and maxTraceSize It can be used to evaluate the performance of SIESTA in throughput and correctness.

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  1. TraceGenerator
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Instance Constructors

  1. new TraceGenerator(numberOfTraces: Int, numberOfDifferentActivities: Int, minTraceSize: Int, maxTraceSize: Int)

    numberOfTraces

    The number of traces to be produced

    numberOfDifferentActivities

    The number of different event types

    minTraceSize

    The minimum trace length

    maxTraceSize

    The maximum trace length

Value Members

  1. final def !=(arg0: Any): Boolean
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  9. def hashCode(): Int
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  10. final def isInstanceOf[T0]: Boolean
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  11. val maxTraceSize: Int
  12. val minTraceSize: Int
  13. final def ne(arg0: AnyRef): Boolean
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  14. final def notify(): Unit
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  15. final def notifyAll(): Unit
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  16. val numberOfDifferentActivities: Int
  17. val numberOfTraces: Int
  18. def produce(t: List[Int]): RDD[Sequence]

    Utilizes the createSequence function (private) to generate random traces and then use spark to parallelize distribute them.

    Utilizes the createSequence function (private) to generate random traces and then use spark to parallelize distribute them. The difference with the produce() function, is that this one generate traces with ids that are passed as parameters

    t

    A list with the trace ids

    returns

    An RDD that contains the randomly generated traces

  19. def produce(t: Iterable[Long]): RDD[Sequence]

    Utilizes the createSequence function (private) to generate random traces and then use spark to parallelize distribute them.

    Utilizes the createSequence function (private) to generate random traces and then use spark to parallelize distribute them. The difference with the produce() function, is that this one generate traces with ids that are passed as parameters

    t

    A list with the trace ids

    returns

    An RDD that contains the randomly generated traces

  20. def produce(): RDD[Sequence]

    Utilizes the createSequence function (private) to generate random traces and then use spark to parallelize distribute them

    Utilizes the createSequence function (private) to generate random traces and then use spark to parallelize distribute them

    returns

    An RDD that contains the randomly generated traces

  21. final def synchronized[T0](arg0: ⇒ T0): T0
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  22. def toString(): String
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  23. final def wait(arg0: Long, arg1: Int): Unit
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  25. final def wait(): Unit
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  1. def finalize(): Unit
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