Object/Class

com.github.timgent.dataflare.checks.metrics

SingleMetricCheck

Related Docs: class SingleMetricCheck | package metrics

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object SingleMetricCheck extends Serializable

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  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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  6. def complianceCheck(threshold: AbsoluteThreshold[Double], complianceFn: ComplianceFn, filter: MetricFilter = MetricFilter.noFilter): SingleMetricCheck[DoubleMetric]

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    Checks the fraction of rows that are compliant with the given complianceFn

    Checks the fraction of rows that are compliant with the given complianceFn

    threshold

    - the threshold for what fraction of rows is acceptable

    complianceFn

    - the function rows are tested with to see if they are compliant

    filter

    - the filter that is applied before the compliance fraction is calculated

  7. def distinctValuesCheck(threshold: AbsoluteThreshold[Long], onColumns: List[String], filter: MetricFilter = MetricFilter.noFilter): SingleMetricCheck[LongMetric]

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    Checks the number of distinct values across the given columns

    Checks the number of distinct values across the given columns

    threshold

    - the threshold for what number of distinct values is acceptable

    onColumns

    - the columns to check for distinct values in

    filter

    - the filter that is applied before the distinct value count is done

  8. def distinctnessCheck(threshold: AbsoluteThreshold[Double], onColumns: List[String], filter: MetricFilter = MetricFilter.noFilter): SingleMetricCheck[DoubleMetric]

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    Checks the distinctness level of values across the given columns (result of 1 means every value is distinct)

    Checks the distinctness level of values across the given columns (result of 1 means every value is distinct)

    threshold

    - the threshold for what number of distinct values is acceptable

    onColumns

    - the columns to check for distinct values in

    filter

    - the filter that is applied before the distinct value count is done

  9. final def eq(arg0: AnyRef): Boolean

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  10. def equals(arg0: Any): Boolean

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  11. def finalize(): Unit

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  12. final def getClass(): Class[_]

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  13. def hashCode(): Int

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  14. final def isInstanceOf[T0]: Boolean

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  15. final def ne(arg0: AnyRef): Boolean

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  16. final def notify(): Unit

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  17. final def notifyAll(): Unit

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  18. def sizeCheck(threshold: AbsoluteThreshold[Long], filter: MetricFilter = MetricFilter.noFilter): SingleMetricCheck[LongMetric]

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    Checks the count of rows in a dataset after the given filter is applied is within the given threshold

    Checks the count of rows in a dataset after the given filter is applied is within the given threshold

    filter

    - filter to be applied before rows are counted

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

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  20. def thresholdBasedCheck[MV <: MetricValue](metricDescriptor: MetricDescriptor { type MetricType = MV }, description: String, threshold: AbsoluteThreshold[SingleMetricCheck.thresholdBasedCheck.MV.T]): SingleMetricCheck[MV]

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    A check based on a single metric that checks if that metric is within the given threshold

    A check based on a single metric that checks if that metric is within the given threshold

    MV

    - the type of the MetricValue that will be calculated in order to complete this check

    metricDescriptor

    - describes the metric the check will be done on

    description

    - the user friendly description for this check

    threshold

    - the threshold that the metric must be within to pass

  21. def toString(): String

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  22. final def wait(): Unit

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

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  24. final def wait(arg0: Long): Unit

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