case class StdNumberDFMetricCalculator(metricId: String, columns: Seq[String]) extends DFMetricCalculator with Product with Serializable
Calculates standard deviation calculated from provided elements
Works for single column only!
- metricId
Id of the metric.
- columns
Sequence of columns which are used for metric calculation
- Note
Null values are omitted.
,Computes population standard deviation.
- Alphabetic
- By Inheritance
- StdNumberDFMetricCalculator
- Serializable
- Serializable
- Product
- Equals
- DFMetricCalculator
- AnyRef
- Any
- Hide All
- Show All
- Public
- All
Instance Constructors
Value Members
-
final
def
!=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
-
final
def
##(): Int
- Definition Classes
- AnyRef → Any
-
final
def
==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
-
final
def
asInstanceOf[T0]: T0
- Definition Classes
- Any
-
def
clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws( ... ) @native()
-
val
columns: Seq[String]
- Definition Classes
- StdNumberDFMetricCalculator → DFMetricCalculator
-
val
emptyValue: Column
Std number metric calculator should return NaN value when DF is empty.
Std number metric calculator should return NaN value when DF is empty.
- Attributes
- protected
- Definition Classes
- StdNumberDFMetricCalculator → DFMetricCalculator
-
final
def
eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
-
def
errorConditionExpr(implicit colTypes: Map[String, DataType]): Column
If casting value to DoubleType yields null, then it is a signal that value is not a number.
If casting value to DoubleType yields null, then it is a signal that value is not a number. Thus, standard deviation 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
- StdNumberDFMetricCalculator → DFMetricCalculator
-
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
-
def
errorMessage: String
Metric error message for cases when some of column value cannot be cast to number.
Metric error message for cases when some of column value cannot be cast to number.
- returns
Metric increment failure message.
- Definition Classes
- StdNumberDFMetricCalculator → DFMetricCalculator
-
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
-
val
errorsCol: String
Name of the column that will store metric errors
Name of the column that will store metric errors
- Definition Classes
- DFMetricCalculator
-
def
finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws( classOf[java.lang.Throwable] )
-
final
def
getClass(): Class[_]
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
-
final
def
isInstanceOf[T0]: Boolean
- Definition Classes
- Any
-
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
- StdNumberDFMetricCalculator → DFMetricCalculator
-
val
metricName: MetricName
- Definition Classes
- StdNumberDFMetricCalculator → DFMetricCalculator
-
final
def
ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
-
final
def
notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
-
final
def
notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
-
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
-
val
resultAggregateFunction: (Column) ⇒ Column
Aggregation function to find standard deviation is just
stddev_popAggregation function to find standard deviation is just
stddev_pop- Attributes
- protected
- Definition Classes
- StdNumberDFMetricCalculator → DFMetricCalculator
-
val
resultCol: String
Name of the column that will store metric result
Name of the column that will store metric result
- Definition Classes
- DFMetricCalculator
-
def
resultExpr(implicit colTypes: Map[String, DataType]): Column
Retrieves number from requested column of row.
Retrieves number from requested column of row.
- colTypes
Map of column names to their datatype.
- returns
Spark row-level expression yielding numeric result.
- Attributes
- protected
- Definition Classes
- StdNumberDFMetricCalculator → DFMetricCalculator
-
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
-
final
def
synchronized[T0](arg0: ⇒ T0): T0
- Definition Classes
- AnyRef
-
final
def
wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
-
final
def
wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... )
-
final
def
wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws( ... ) @native()