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Version: Java (Groovy)

OperationControl

OperationControl is a Java class that defines the control parameters of some UpdateByOperations used in an updateBy table operation. The UpdateByOperations that can use OperationControl to handle erroneous data are:

Syntax​

opControl = OperationControl.builder().onNullValue(BadDataBehavior.SKIP).onNanValue(BadDataBehavior.SKIP).bigValueContext(MathContext.DECIMAL128).build()

Construction​

OperationControl is constructed using a builder pattern. The builder can set parameters on how to handle nulls, NaNs, and large values, respectively, with the following methods:

The first two take an enum value from BadDataBehavior, whereas the third takes a value from MathContext.

BadDataBehavior has four enum values:

  • POISON: Allow bad data to poison the result.
  • RESET: Reset the state of the bucket to null when any bad data is encountered.
  • SKIP: Skip and do not process invalid data without changing state.
  • THROW: Throw an exception and abort processing when bad data is encountered.

The default value is SKIP.

MathContext has four values:

  • DECIMAL128: Precision matching IEEE 754R Decimal128 format. Has 34 digits and rounding mode of HALF_EVEN.
  • DECIMAL32: Precision matching the IEEE 754R Decimal32 format. Has 7 digits and rounding mode of HALF_EVEN.
  • DECIMAL64: Precision matching the IEEE 754R Decimal64 format. Has 16 digits and a rounding mode of HALF_EVEN.
  • UNLIMITED: Unlimited precision arithmetic.

Returns​

An instance of an OperationControl class that can be used in an updateBy operation.

Examples​

The following example does not set control. It uses the default settings of BadDataBehavior.SKIP and MathContext.DECIMAL128. Null values in the source table are skipped.

source = emptyTable(25).update("Letter = (i % 2 == 0) ? `A` : `B`", "X = (i % 5 == 0) ? NULL_INT : randomInt(0, 100)")

result = source.updateBy(Ema(5, "EmaX = X"), "Letter")

The following example sets control to use BadDataBehavior.RESET when null values occur, so that the EMA is reset when null values are encountered.

ctrl = OperationControl.builder().onNullValue(BadDataBehavior.RESET).build()

source = emptyTable(25).update("Letter = (i % 2 == 0) ? `A` : `B`", "X = (i % 5 == 0) ? NULL_INT : randomInt(0, 100)")

result = source.updateBy(Ema(ctrl, 5, "EmaX = X"), "Letter")

The following example sets op_control to use BadDataBehavior.RESET when NaN values occur, so that the EMA is reset when NaN values are encountered.

ctrl = OperationControl.builder().onNanValue(BadDataBehavior.RESET).build()

source = emptyTable(25).update("Letter = (i % 2 == 0) ? `A` : `B`", "X = (i % 5 == 0) ? (0/0) : randomInt(0, 100)")

result = source.updateBy(Ema(ctrl, 5, "EmaX = X"), "Letter")

The following example sets op_control to use BadDataBehavior.POISON when NaN values occur. This results in the EMA being poisoned with NaN values.

ctrl = OperationControl.builder().onNanValue(BadDataBehavior.POISON).build()

source = emptyTable(25).update("Letter = (i % 2 == 0) ? `A` : `B`", "X = (i % 5 == 0) ? (0/0) : randomInt(0, 100)")

result = source.updateBy(Ema(ctrl, 5, "EmaX = X"), "Letter")

The following example sets op_control to BadDataBehavior.THROW when null values occur. The query throws an error when it encounters a null value in the first row.

ctrl = OperationControl.builder().onNullValue(BadDataBehavior.THROW).build()

source = emptyTable(25).update("Letter = (i % 2 == 0) ? `A` : `B`", "X = (i % 5 == 0) ? NULL_INT : randomInt(0, 100)")

result = source.updateBy(Ema(ctrl, 5, "EmaX = X"), "Letter")