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

   TopNDFMetricCalculator → DFMetricCalculator

7.  val emptyValue: Column

   TopN metric return empty string as value and NaN as frequency when applied to empty sequence.

   TopN metric return empty string as value and NaN as frequency when applied to empty sequence.

   Attributes

   protected

   Definition Classes

   TopNDFMetricCalculator → DFMetricCalculator

8.  final def eq(arg0: AnyRef): Boolean

   Definition Classes

   AnyRef

9.  def errorConditionExpr(implicit colTypes: Map[String, DataType]): Column

   If casting value to StringType yields null, then it is a signal that value is not a string.

   If casting value to StringType yields null, then it is a signal that value is not a string. Thus, TopN 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

   TopNDFMetricCalculator → 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

    Error message that will be returned when column value cannot be cast to string.

    Error message that will be returned when column value cannot be cast to string.

    returns

    Metric increment failure message.

    Definition Classes

    TopNDFMetricCalculator → 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.  final def isInstanceOf[T0]: Boolean

    Definition Classes

    Any

17.  val maxCapacity: Int
18.  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

    TopNDFMetricCalculator → DFMetricCalculator

19.  val metricName: MetricName

    Definition Classes

    TopNDFMetricCalculator → DFMetricCalculator

20.  final def ne(arg0: AnyRef): Boolean

    Definition Classes

    AnyRef

21.  final def notify(): Unit

    Definition Classes

    AnyRef

    Annotations

    @native()

22.  final def notifyAll(): Unit

    Definition Classes

    AnyRef

    Annotations

    @native()

23.  def result(implicit colTypes: Map[String, DataType]): Column

    Overriding result expression since for TopN metric the result is not a double value but an array with top-N values from column along with their occurrence frequencies.

    Overriding result expression since for TopN metric the result is not a double value but an array with top-N values from column along with their occurrence frequencies.

    colTypes

    Map of column names to their datatype.

    returns

    Spark expression that will yield result of following type: array(struct(string, double)).

    Definition Classes

    TopNDFMetricCalculator → DFMetricCalculator

24.  val resultAggregateFunction: (Column) ⇒ Column

    User custom aggregation function to find topN values based on SpaceSaver.

    User custom aggregation function to find topN values based on SpaceSaver.

    Attributes

    protected

    Definition Classes

    TopNDFMetricCalculator → DFMetricCalculator

25.  val resultCol: String

    Name of the column that will store metric result

    Name of the column that will store metric result

    Definition Classes

    DFMetricCalculator

26.  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

    TopNDFMetricCalculator → DFMetricCalculator

    Note

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

27.  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

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

    Definition Classes

    AnyRef

29.  val targetNumber: Int
30.  final def wait(): Unit

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

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

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

32.  final def wait(arg0: Long): Unit

    Definition Classes

    AnyRef

    Annotations

    @throws( ... ) @native()