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

CompletenessDFMetricCalculator

case class CompletenessDFMetricCalculator(metricId: String, columns: Seq[String], includeEmptyStrings: Boolean, reversed: Boolean) extends DFMetricCalculator with ReversibleDFCalculator with Product with Serializable

Calculates completeness of values in the specified columns

metricId

Id of the metric.

columns

Sequence of columns which are used for metric calculation

includeEmptyStrings

Flag which sets whether empty strings are considered in addition to null values.

reversed

Boolean flag indicating whether error collection logic should be reversed for this metric

Linear Supertypes
Serializable, Serializable, Product, Equals, ReversibleDFCalculator, DFMetricCalculator, AnyRef, Any
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Inherited
  1. CompletenessDFMetricCalculator
  2. Serializable
  3. Serializable
  4. Product
  5. Equals
  6. ReversibleDFCalculator
  7. DFMetricCalculator
  8. AnyRef
  9. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new CompletenessDFMetricCalculator(metricId: String, columns: Seq[String], includeEmptyStrings: Boolean, reversed: Boolean)

    metricId

    Id of the metric.

    columns

    Sequence of columns which are used for metric calculation

    includeEmptyStrings

    Flag which sets whether empty strings are considered in addition to null values.

    reversed

    Boolean flag indicating whether error collection logic should be reversed for this metric

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 columns: Seq[String]
    Definition Classes
    CompletenessDFMetricCalculator → DFMetricCalculator
  7. val emptyValue: Column

    Completeness metric returns NaN when DF is empty.

    Completeness metric returns NaN when DF is empty.

    Attributes
    protected
    Definition Classes
    CompletenessDFMetricCalculator → DFMetricCalculator
  8. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  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. Usually checks the outcome of resultExpr.

    colTypes

    Map of column names to their datatype.

    returns

    Spark row-level expression yielding boolean result.

    Attributes
    protected
    Definition Classes
    CompletenessDFMetricCalculator → 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 errorMessage: String

    For direct error collection logic any non-null (or non-empty if includeEmptyStrings is true) values are considered as metric failure.

    For direct error collection logic any non-null (or non-empty if includeEmptyStrings is true) values are considered as metric failure. For reversed error collection logic null (or empty if includeEmptyStrings is true) values are considered as metric failure

    returns

    Metric increment failure message.

    Definition Classes
    CompletenessDFMetricCalculator → DFMetricCalculator
  12. 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
  13. val errorsCol: String

    Name of the column that will store metric errors

    Name of the column that will store metric errors

    Definition Classes
    DFMetricCalculator
  14. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  15. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  16. val includeEmptyStrings: Boolean
  17. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  18. def metricCondExpr(colName: String): Column
    Attributes
    protected
  19. 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
    CompletenessDFMetricCalculator → DFMetricCalculator
  20. val metricName: MetricName
    Definition Classes
    CompletenessDFMetricCalculator → DFMetricCalculator
  21. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  22. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  23. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  24. 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
  25. val resultAggregateFunction: (Column) ⇒ Column

    Completeness metric is aggregated as ration of total number of non-null (or non-empty) cells to total number of cells that were processed.

    Completeness metric is aggregated as ration of total number of non-null (or non-empty) cells to total number of cells that were processed.

    Attributes
    protected
    Definition Classes
    CompletenessDFMetricCalculator → DFMetricCalculator
  26. val resultCol: String

    Name of the column that will store metric result

    Name of the column that will store metric result

    Definition Classes
    DFMetricCalculator
  27. 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 by number of non-null (or non-empty if includeEmptyStrings is true) values within requested columns.

    colTypes

    Map of column names to their datatype.

    returns

    Spark row-level expression yielding numeric result.

    Attributes
    protected
    Definition Classes
    CompletenessDFMetricCalculator → DFMetricCalculator
  28. val reversed: Boolean
    Attributes
    protected
    Definition Classes
    CompletenessDFMetricCalculator → ReversibleDFCalculator
  29. 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
  30. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  31. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  32. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  33. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from ReversibleDFCalculator

Inherited from DFMetricCalculator

Inherited from AnyRef

Inherited from Any

Ungrouped