org.anduril.runtime.table.processor

ColumnStatistics

final class ColumnStatistics extends (Row) ⇒ Unit

Compute statistics for a numeric column.

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(Row) ⇒ Unit, AnyRef, Any
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Instance Constructors

  1. new ColumnStatistics(column: Column, quantileLimit: Int, quantileEpsilon: Double)

    Initialize for a given column.

    Initialize for a given column.

    column

    The column object.

    quantileLimit

    Number of rows that is the threshold for computing exact quantiles. When there are more rows than this limit, an approximation algorithm is used for computing quantiles.

    quantileEpsilon

    Accuracy for computing approximate quantiles. The approximate quantiles will be within the given eplison of the real quantile. For example, with quantileEpsilon = 0.01, the median (quantile 0.5) is approximated as a quantile between 0.49 and 0.51. Approximate quantiles are disabled with quantileEpsilon = 0.

Value Members

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

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

    Definition Classes
    Any
  3. final def ##(): Int

    Definition Classes
    AnyRef → Any
  4. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  5. final def ==(arg0: Any): Boolean

    Definition Classes
    Any
  6. def andThen[A](g: (Unit) ⇒ A): (Row) ⇒ A

    Definition Classes
    Function1
    Annotations
    @unspecialized()
  7. def apply(row: Row): Unit

    Add a new numeric value to the statistics.

    Add a new numeric value to the statistics.

    Definition Classes
    ColumnStatistics → Function1
  8. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  9. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws()
  10. val column: Column

    The column object.

  11. def compose[A](g: (A) ⇒ Row): (A) ⇒ Unit

    Definition Classes
    Function1
    Annotations
    @unspecialized()
  12. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  13. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  14. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws()
  15. def geometricMean(): Double

    Return the geometric mean of values.

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

    Definition Classes
    AnyRef → Any
  17. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  18. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  19. def max(): Double

    Return the maximum of values.

  20. def mean(): Double

    Return the arithmetic mean of values.

  21. def median(): Double

    Return the median of values.

    Return the median of values. This is equal to quantile(0.5).

  22. def min(): Double

    Return the minimum of values.

  23. def missing(): Long

    Return the number of missing values.

  24. def n(): Long

    Return the total number of non-missing values.

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

    Definition Classes
    AnyRef
  26. final def notify(): Unit

    Definition Classes
    AnyRef
  27. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  28. def quantile(quantile: Double): Double

    Return the given quantile of values.

    Return the given quantile of values. The quantile is exact if the number of observed rows is less than quantileLimit or approximate otherwise.

    quantile

    Quantile between 0 and 1.

  29. val quantileEpsilon: Double

    Accuracy for computing approximate quantiles.

    Accuracy for computing approximate quantiles. The approximate quantiles will be within the given eplison of the real quantile. For example, with quantileEpsilon = 0.01, the median (quantile 0.5) is approximated as a quantile between 0.49 and 0.51. Approximate quantiles are disabled with quantileEpsilon = 0.

  30. val quantileLimit: Int

    Number of rows that is the threshold for computing exact quantiles.

    Number of rows that is the threshold for computing exact quantiles. When there are more rows than this limit, an approximation algorithm is used for computing quantiles.

  31. def sd(): Double

    Return the standard deviation of values.

  32. def sum(): Double

    Return the sum of values.

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

    Definition Classes
    AnyRef
  34. def toString(): String

    Definition Classes
    ColumnStatistics → Function1 → AnyRef → Any
  35. def variance(): Double

    Return the variance of values.

  36. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws()
  37. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws()
  38. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws()

Inherited from (Row) ⇒ Unit

Inherited from AnyRef

Inherited from Any

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