Class

org.apache.spark.rdd

Timer

Related Doc: package rdd

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class Timer extends Serializable

Represents a timer, for timing a function. Call the time function, passing the function to time.

For recording metrics the Timer either uses the passed-in MetricsRecorder if it is defined, or it looks in the Metrics.Recorder field for a recorder. If neither of these are defined then no metrics are recorded (the function is executed without recording metrics).

The overhead of recording metrics has been measured at around 100 nanoseconds on an Intel i7-3720QM. The overhead of calling the time method when no metrics are being recorded (a recorder is not defined) is negligible.

Note

This class needs to be in the org.apache.spark.rdd package, otherwise Spark records somewhere in the time method as the call site (which in turn becomes the stage name). This can be fixed when Spark 1.1.1 is released (needs SPARK-1853).

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Instance Constructors

  1. new Timer(name: String, clock: Clock = new Clock(), recorder: Option[MetricsRecorder] = None, sequenceId: Option[Int] = None, isRDDOperation: Boolean = false)

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Value Members

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

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  2. final def ##(): Int

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  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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  7. def equals(arg0: Any): Boolean

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  8. def finalize(): Unit

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

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  11. final def isInstanceOf[T0]: Boolean

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

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  13. final def notify(): Unit

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  14. final def notifyAll(): Unit

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

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  16. def time[A](f: ⇒ A): A

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    Runs f, recording its duration, and returns its result.

  17. val timerName: String

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  18. def toString(): String

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  19. final def wait(): Unit

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

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

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