abstract class PercentileDFCalculator extends DFMetricCalculator

Base class for all metrics thad compute percentiles based on T-Digest.

Linear Supertypes
DFMetricCalculator, AnyRef, Any
Known Subclasses
FirstQuantileDFMetricCalculator, GetPercentileDFMetricCalculator, GetQuantileDFMetricCalculator, MedianValueDFMetricCalculator, ThirdQuantileDFMetricCalculator
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. PercentileDFCalculator
  2. DFMetricCalculator
  3. AnyRef
  4. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Instance Constructors

  1. new PercentileDFCalculator()

Abstract Value Members

  1. abstract val accuracyError: Double
  2. abstract val columns: Seq[String]
    Definition Classes
    DFMetricCalculator
  3. abstract val emptyValue: Column

    Value which is returned when metric result is null.

    Value which is returned when metric result is null.

    Attributes
    protected
    Definition Classes
    DFMetricCalculator
  4. abstract val isDirect: Boolean
  5. abstract val metricId: String

    Unlike RDD calculators, DF calculators are not groped by its type.

    Unlike RDD calculators, DF calculators are not groped by its type. For each metric defined in DQ job, there will be created its own instance of DF calculator. Thus, DF metric calculators can be linked to metric definitions by metricId.

    Definition Classes
    DFMetricCalculator
  6. abstract val metricName: MetricName
    Definition Classes
    DFMetricCalculator
  7. abstract val target: Double

Concrete Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  5. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  6. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  7. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  8. def errorConditionExpr(implicit colTypes: Map[String, DataType]): Column

    If casting value to DoubleType yields null, then it is a signal that value is not a number.

    If casting value to DoubleType yields null, then it is a signal that value is not a number. Thus, percentile computation can't be incremented for this row. This is a metric increment failure.

    colTypes

    Map of column names to their datatype.

    returns

    Spark row-level expression yielding boolean result.

    Attributes
    protected
    Definition Classes
    PercentileDFCalculator → DFMetricCalculator
  9. def errorExpr(rowData: Column)(implicit colTypes: Map[String, DataType]): Column

    Error collection expression: collects row data in case of metric error.

    Error collection expression: collects row data in case of metric error.

    rowData

    Array of row data from columns related to this metric calculator (source keyFields + metric columns + window start time column for streaming applications)

    colTypes

    Map of column names to their datatype.

    returns

    Spark expression that will yield row data in case of metric error.

    Attributes
    protected
    Definition Classes
    DFMetricCalculator
  10. def errorMessage: String

    Metric error message for cases when column value cannot be cast to number (double).

    Metric error message for cases when column value cannot be cast to number (double).

    returns

    Metric increment failure message.

    Definition Classes
    PercentileDFCalculator → DFMetricCalculator
  11. def errors(implicit errorDumpSize: Int, keyFields: Seq[String], colTypes: Map[String, DataType]): Column

    Final metric errors aggregation expression.

    Final metric errors aggregation expression. Collects all metric errors into an array column. The size of array is limited by maximum allowed error dump size parameter.

    errorDumpSize

    Maximum allowed number of errors to be collected per single metric.

    keyFields

    Sequence of source/stream key fields.

    colTypes

    Map of column names to their datatype.

    returns

    Spark expression that will yield array of metric errors.

    Definition Classes
    DFMetricCalculator
  12. val errorsCol: String

    Name of the column that will store metric errors

    Name of the column that will store metric errors

    Definition Classes
    DFMetricCalculator
  13. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  14. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  15. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  16. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  17. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  18. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  19. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  20. def result(implicit colTypes: Map[String, DataType]): Column

    Final metric aggregation expression that MUST yield double value.

    Final metric aggregation expression that MUST yield double value.

    colTypes

    Map of column names to their datatype.

    returns

    Spark expression that will yield double metric calculator result

    Definition Classes
    DFMetricCalculator
  21. val resultAggregateFunction: (Column) ⇒ Column

    Use custom aggregation function to find percentile value based on T-Digest.

    Use custom aggregation function to find percentile value based on T-Digest.

    Attributes
    protected
    Definition Classes
    PercentileDFCalculator → DFMetricCalculator
  22. val resultCol: String

    Name of the column that will store metric result

    Name of the column that will store metric result

    Definition Classes
    DFMetricCalculator
  23. def resultExpr(implicit colTypes: Map[String, DataType]): Column

    Retrieves number from requested column of row.

    Retrieves number from requested column of row.

    colTypes

    Map of column names to their datatype.

    returns

    Spark row-level expression yielding numeric result.

    Attributes
    protected
    Definition Classes
    PercentileDFCalculator → DFMetricCalculator
  24. def rowDataExpr(keyFields: Seq[String]): Column

    Row data collection expression: collects values of selected columns to array for row where metric error occurred.

    Row data collection expression: collects values of selected columns to array for row where metric error occurred.

    keyFields

    Sequence of source/stream key fields.

    returns

    Spark expression that will yield array of row data for column related to this metric calculator.

    Attributes
    protected
    Definition Classes
    DFMetricCalculator
  25. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  26. def toString(): String
    Definition Classes
    AnyRef → Any
  27. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  28. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  29. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()

Inherited from DFMetricCalculator

Inherited from AnyRef

Inherited from Any

Ungrouped