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org.checkita.dqf.core.metrics.df.regular.MultiColumnDFMetrics

MultiColumnConditionalDFCalculator

abstract class MultiColumnConditionalDFCalculator extends DFMetricCalculator with ReversibleDFCalculator

Abstract class for conditional multi-column DF metric calculators. Specific of multi-column conditional metrics is that metric condition is a function of all input columns and need to be applied to all of them at once. Unlike for columns which can work with arbitrary number of columns where metric condition is applied to each of the input column separately.

All conditional metrics are reversible: direct error collection logic implies metric increment fails when condition is not met. Correspondingly, for reversed error collection logic, metric increment fails when condition IS met.

Linear Supertypes
ReversibleDFCalculator, DFMetricCalculator, AnyRef, Any
Known Subclasses
ColumnEqDFMetricCalculator, DayDistanceDFMetricCalculator, LevenshteinDistanceDFMetricCalculator
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. MultiColumnConditionalDFCalculator
  2. ReversibleDFCalculator
  3. DFMetricCalculator
  4. AnyRef
  5. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new MultiColumnConditionalDFCalculator()

Abstract Value Members

  1. abstract val columns: Seq[String]
    Definition Classes
    DFMetricCalculator
  2. abstract def errorMessage: String

    Error message that will be returned when metric increment fails.

    Error message that will be returned when metric increment fails.

    returns

    Metric increment failure message.

    Definition Classes
    DFMetricCalculator
  3. abstract def metricCondExpr: Column

    Create spark expression which checks if metric condition applied to multiple columns is met.

    Create spark expression which checks if metric condition applied to multiple columns is met.

    Attributes
    protected
  4. 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
  5. abstract val metricName: MetricName
    Definition Classes
    DFMetricCalculator
  6. abstract val reversed: Boolean
    Attributes
    protected
    Definition Classes
    ReversibleDFCalculator

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. 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
    MultiColumnConditionalDFCalculator → DFMetricCalculator
  7. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  8. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  9. def errorConditionExpr(implicit colTypes: Map[String, DataType]): Column

    Spark expression yielding boolean result for processed row.

    Spark expression yielding boolean result for processed row. Indicates whether metric increment failed or not.

    colTypes

    Map of column names to their datatype.

    returns

    Spark row-level expression yielding boolean result.

    Attributes
    protected
    Definition Classes
    MultiColumnConditionalDFCalculator → DFMetricCalculator
  10. 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
  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

    Aggregation function for all conditional metrics is just a summation.

    Aggregation function for all conditional metrics is just a summation.

    Attributes
    protected
    Definition Classes
    MultiColumnConditionalDFCalculator → 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

    Spark expression yielding numeric result for processed row.

    Spark expression yielding numeric result for processed row. Metric will be incremented with this result using associated aggregation function.

    colTypes

    Map of column names to their datatype.

    returns

    Spark row-level expression yielding numeric result.

    Attributes
    protected
    Definition Classes
    MultiColumnConditionalDFCalculator → DFMetricCalculator
    Note

    Spark expression MUST process single row but not aggregate multiple rows.

  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 ReversibleDFCalculator

Inherited from DFMetricCalculator

Inherited from AnyRef

Inherited from Any

Ungrouped