object StatsGenerator
StatsGenerator takes care of computation of metadata for dataframes as well as measuring differences between two dataframes. This applies to drifts as well between two dataframes.
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- case class MetricTransform(name: String, expression: Column, operation: Operation, argMap: Map[String, String] = null) extends Product with Serializable
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final
def
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final
def
##(): Int
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def
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def
anyTransforms(column: Column): Seq[MetricTransform]
Stats applied to any column
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final
def
asInstanceOf[T0]: T0
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def
buildAggregator(metrics: Seq[MetricTransform], inputDf: DataFrame): RowAggregator
Build RowAggregator to use for computing stats on a dataframe based on metrics
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def
buildMetrics(fields: Array[(String, DataType)]): Seq[MetricTransform]
For the schema of the data define metrics to be aggregated
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def
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- @throws( classOf[java.lang.Throwable] )
- val finalizedPercentiles: IndexedSeq[Double]
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getClass(): Class[_]
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hashCode(): Int
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- val ignoreColumns: Seq[String]
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def
notifyAll(): Unit
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- val nullPrefix: String
- val nullRatePrefix: String
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def
numericTransforms(column: Column): Seq[MetricTransform]
Stats applied to numeric columns
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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def
toString(): String
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- val totalColumn: String
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def
wait(): Unit
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wait(arg0: Long, arg1: Int): Unit
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