case class AvgStringDFMetricCalculator(metricId: String, columns: Seq[String]) extends DFMetricCalculator with Product with Serializable

Calculates average string length of processed elements

metricId

Id of the metric.

columns

Sequence of columns which are used for metric calculation

Note

Null values are omitted: For values: "foo", "bar-buz", null Metric result would be: (3 + 7) / 2 = 5

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

Instance Constructors

  1. new AvgStringDFMetricCalculator(metricId: String, columns: Seq[String])

    metricId

    Id of the metric.

    columns

    Sequence of columns which are used for metric calculation

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
    AvgStringDFMetricCalculator → DFMetricCalculator
  7. val emptyValue: Column

    Avg string return NaN when DF is empty.

    Avg string return NaN when DF is empty.

    Attributes
    protected
    Definition Classes
    AvgStringDFMetricCalculator → DFMetricCalculator
  8. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  9. def errorConditionExpr(implicit colTypes: Map[String, DataType]): Column

    If expression summing all string lengths returned null, then it is a signal that all values in requested columns of processed row were nulls.

    If expression summing all string lengths returned null, then it is a signal that all values in requested columns of processed row were nulls. Thus, average string length couldn't be calculated. 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
    AvgStringDFMetricCalculator → 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

    Metric error message for cases when all requested column values are nulls for processed rows.

    Metric error message for cases when all requested column values are nulls for processed rows.

    returns

    Metric increment failure message.

    Definition Classes
    AvgStringDFMetricCalculator → 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 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
    AvgStringDFMetricCalculator → DFMetricCalculator
  18. val metricName: MetricName
    Definition Classes
    AvgStringDFMetricCalculator → DFMetricCalculator
  19. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  20. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  21. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  22. 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
  23. val resultAggregateFunction: (Column) ⇒ Column

    Average string length is aggregated as ration of sum of all string length to number of cells that were processed (excluding null cells).

    Average string length is aggregated as ration of sum of all string length to number of cells that were processed (excluding null cells).

    Attributes
    protected
    Definition Classes
    AvgStringDFMetricCalculator → DFMetricCalculator
  24. val resultCol: String

    Name of the column that will store metric result

    Name of the column that will store metric result

    Definition Classes
    DFMetricCalculator
  25. 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
    AvgStringDFMetricCalculator → DFMetricCalculator
  26. 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
  27. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  28. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  29. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  30. 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 DFMetricCalculator

Inherited from AnyRef

Inherited from Any

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