org.apache.spark.rdd

InstrumentedRDD

object InstrumentedRDD extends Serializable

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

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  3. final def ##(): Int

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  7. var clock: Clock

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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 functionRecorder(): FunctionRecorder

    Obtains a metrics recorder suitable for passing-in to a function that operates on an RDD.

    Obtains a metrics recorder suitable for passing-in to a function that operates on an RDD. See the class-level documentation for a usage example.

  13. var functionTimer: Timer

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

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  15. def hashCode(): Int

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  16. def instrument[B](rdd: RDD[B])(implicit arg0: ClassTag[B]): RDD[B]

    Instruments the passed-in RDD, returning an InstrumentedRDD

  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 recordFunction[B](function: ⇒ B)(implicit functionRecorder: FunctionRecorder): B

    Instruments a function call that acts on the data in an RDD.

    Instruments a function call that acts on the data in an RDD. The recorder should have been obtained from the metricsRecorder method. The passed-in functionTimer is used to time the function call. See the class-level documentation for a usage example.

    The overhead of instrumenting a function call has been measured at around 120 nanoseconds on an Intel i7-3720QM. The overhead of calling this method when no metrics are being recorded (a recorder is not defined) is negligible.

  22. def recordOperation[A](operation: ⇒ A): A

    Instruments an RDD operation.

    Instruments an RDD operation. All RDD operations that need to be instrumented should be wrapped in this method. See the class-level documentation for a usage example.

  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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