org.apache.spark.util

StatCounter

class StatCounter extends Serializable

A class for tracking the statistics of a set of numbers (count, mean and variance) in a numerically robust way. Includes support for merging two StatCounters. Based on Welford and Chan's algorithms for running variance.

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Instance Constructors

  1. new StatCounter()

    Initialize the StatCounter with no values.

  2. new StatCounter(values: TraversableOnce[Double])

    Initialize the StatCounter with the given values.

Value Members

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

    Definition Classes
    AnyRef

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

    Definition Classes
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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 def asInstanceOf[T0]: T0

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  7. def clone(): AnyRef

    Attributes
    protected[java.lang]
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    Annotations
    @throws( ... )

  8. def copy(): StatCounter

    Clone this StatCounter

  9. def count: Long

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

    Definition Classes
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  11. def equals(arg0: Any): Boolean

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  12. def finalize(): Unit

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    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )

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

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  14. def hashCode(): Int

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  15. final def isInstanceOf[T0]: Boolean

    Definition Classes
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  16. def max: Double

  17. def mean: Double

  18. def merge(other: StatCounter): StatCounter

    Merge another StatCounter into this one, adding up the internal statistics.

  19. def merge(values: TraversableOnce[Double]): StatCounter

    Add multiple values into this StatCounter, updating the internal statistics.

  20. def merge(value: Double): StatCounter

    Add a value into this StatCounter, updating the internal statistics.

  21. def min: Double

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

    Definition Classes
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  23. final def notify(): Unit

    Definition Classes
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  24. final def notifyAll(): Unit

    Definition Classes
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  25. def sampleStdev: Double

    Return the sample standard deviation of the values, which corrects for bias in estimating the variance by dividing by N-1 instead of N.

  26. def sampleVariance: Double

    Return the sample variance, which corrects for bias in estimating the variance by dividing by N-1 instead of N.

  27. def stdev: Double

    Return the standard deviation of the values.

  28. def sum: Double

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

    Definition Classes
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  30. def toString(): String

    Definition Classes
    StatCounter → AnyRef → Any

  31. def variance: Double

    Return the variance of the values.

  32. final def wait(): Unit

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

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    @throws( ... )

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

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