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org.apache.spark.groupon.metrics

UserMetricsSystem

Related Doc: package metrics

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object UserMetricsSystem

Entry point for collecting user-defined metrics.

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  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 DefaultNamespace: String

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  5. final def asInstanceOf[T0]: T0

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  6. def clone(): AnyRef

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    @throws( ... )
  7. def counter(metricName: String): SparkCounter

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    Create a SparkCounter that pushes data points to the driver for aggregation.

    Create a SparkCounter that pushes data points to the driver for aggregation.

    metricName

    name of the metric

    returns

    the SparkCounter instance

  8. final def eq(arg0: AnyRef): Boolean

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  9. def equals(arg0: Any): Boolean

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  10. def finalize(): Unit

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  11. def gauge(metricName: String): SparkGauge

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    Create a SparkGauge that pushes data points to the driver for aggregation.

    Create a SparkGauge that pushes data points to the driver for aggregation.

    metricName

    name of the metric

    returns

    the SparkGauge instance

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

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  13. def hashCode(): Int

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  14. def histogram(metricName: String, reservoirClass: Class[_ <: Reservoir] = ...): SparkHistogram

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    Create a SparkHistogram that pushes data points to the driver for aggregation.

    Create a SparkHistogram that pushes data points to the driver for aggregation.

    metricName

    name of the metric

    reservoirClass

    Class of the Reservoir that backs the com.codahale.metrics.Histogram on the driver. By default, it is the com.codahale.metrics.ExponentiallyDecayingReservoir.

    returns

    the SparkHistogram instance

  15. def initialize(sparkContext: SparkContext, metricNamespace: String = DefaultNamespace): Unit

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    Initialize the metrics system.

    Initialize the metrics system.

    Must be invoked in the driver before the SparkContext is started.

    sparkContext

    app's SparkContext

    metricNamespace

    namespace of metrics used for publishing. By default, it is UserMetrics.

  16. final def isInstanceOf[T0]: Boolean

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  17. def meter(metricName: String): SparkMeter

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    Create a SparkMeter that pushes data points to the driver for aggregation.

    Create a SparkMeter that pushes data points to the driver for aggregation.

    metricName

    name of the metric

    returns

    the SparkMeter instance

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

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  22. def timer(metricName: String, reservoirClass: Class[_ <: Reservoir] = ..., clockClass: Class[_ <: Clock] = ClockClass.UserTime): SparkTimer

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    Create a SparkTimer that pushes data points to the driver for aggregation.

    Create a SparkTimer that pushes data points to the driver for aggregation.

    metricName

    name of the metric

    reservoirClass

    Class of the Reservoir that backs the com.codahale.metrics.Timer on the driver. By default, it is the com.codahale.metrics.ExponentiallyDecayingReservoir.

    clockClass

    Class of the Clock that backs the com.codahale.metrics.Timer on the driver. By default, it is the com.codahale.metrics.Clock.UserTimeClock

    returns

    the SparkTimer instance

  23. def toString(): String

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  24. final def wait(): Unit

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

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

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