org.bdgenomics.utils.instrumentation

Metrics

object Metrics extends Serializable

Manages recording of metrics in an application. Metrics collection is turned on for a particular thread by calling the initialize method. After initialize is called the Metrics.Recorder field is set, and the application can use that to record metrics. To print metrics, call the print method, and to stop recording metrics for a particular thread, call the stopRecording method.

If an application does not want to record metrics, it can simply avoid calling the initialize method (or can call the stopRecording method if there is a chance that initialize has been called on that thread previously). Attempting to record metrics when the initialize method has not been called will not produce an error, and incurs very little overhead. However, attempting to call the print method to print the metrics will produce an error.

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

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  3. final def ##(): Int

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  4. final def ==(arg0: AnyRef): Boolean

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  5. final def ==(arg0: Any): Boolean

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  6. final val Recorder: DynamicVariable[Option[MetricsRecorder]]

    Dynamic variable (thread-local) which allows metrics to be recorded for the current thread.

    Dynamic variable (thread-local) which allows metrics to be recorded for the current thread. Note that this will be set to None if metrics have not been initialized for the current thread, so callers should deal with this appropriately (normally by avoiding recording any metrics or propagating the recorder to other threads).

  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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  10. def equals(arg0: Any): Boolean

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  11. def finalize(): Unit

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  12. def generateNewSequenceId(): Int

    Generates a new sequence ID for operations that we wish to appear in sequence

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

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  14. def hashCode(): Int

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  15. def initialize(sparkContext: SparkContext): Unit

    Starts recording metrics for this thread.

    Starts recording metrics for this thread. Any previously-recorded metrics for this thread will be cleared. This method must always be called before recording metrics.

  16. final def isInstanceOf[T0]: Boolean

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  17. def isRecording: Boolean

    Returns true if metrics are being recorded for the current thread, or false otherwise

  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 print(out: PrintWriter, sparkStageTimings: Option[Seq[StageTiming]]): Unit

    Prints the metrics recorded by this instance to the specified PrintWriter, using the specified SparkMetrics to print details of any Spark operations that have occurred.

  22. def stopRecording(): Unit

    Stops recording metrics for the current thread.

    Stops recording metrics for the current thread. This avoids the (slight) overhead of recording metrics if they are not going to be used. Calling the print method after calling this one will result in an IllegalStateException.

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

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  24. def toString(): String

    Definition Classes
    Metrics → AnyRef → Any
  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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