Ems

Ems creates an EMS (exponential moving sum) for an updateBy table operation. The formula for an EMS is:

$a = e^{\frac{-1}{\tau}}$

$\epsilon_{n} = a * \epsilon_{n-1} + x$

Where:

$\tau$ is the window size, an input parameter to the method.
$\epsilon$ is the EMS.
$x$ is the current value.
$n$ denotes the step. The current step is $n$ , and the previous step is $n - 1$ .

Syntax

Ems(tickDecay, pairs...)
Ems(control, tickDecay, pairs...)
Ems(control, timestampColumn, timeDecay, pairs...)
Ems(control, timestampColumn, durationDecay, pairs...)
Ems(timestampColumn, timeDecay, pairs...)
Ems(timestampColumn, durationDecay, pairs...)

Parameters

Parameter	Type	Description
tickDecay	long	The decay rate in ticks (rows).
pairs	String...	The input/output column name pairs.
control	OperationControl	Defines how special cases should behave. If not given, default `OperationControl` settings are used.
timestampColumn	String	The column in the source table to use for timestamps.
timeDecay	long	The decay rate in nanoseconds.
durationDecay	Duration	The decay rate in a Duration object.

Returns

An UpdateByOperation to be used in an updateBy table operation.

Examples

One column, no groups

The following example calculates the tick-based and time-based EMS of the X column, renaming the resulting column to EmsX. The tick decay rate is set to 5 rows, and the time decay rate is set to 5 seconds. No grouping columns are specified, so the EMS is calculated for all rows.

baseTime = parseInstant("2023-01-01T00:00:00 ET")

source = emptyTable(10).update("Timestamp = baseTime + i *  SECOND", "Letter = (i % 2 == 0) ? `A` : `B`", "X = i")

result = source.updateBy([Ems(5, "EmsTickX = X"), Ems("Timestamp", 5 * SECOND, "EmsTimeX = X")])

One EMS column, one grouping column

The following example builds on the previous by specifying Letter as the key column. Thus, the EMA is calculated on a per-letter basis.

baseTime = parseInstant("2023-01-01T00:00:00 ET")

source = emptyTable(10).update("Timestamp = baseTime + i *  SECOND", "Letter = (i % 2 == 0) ? `A` : `B`", "X = i")

result = source.updateBy([Ems(5, "EmsTickX = X"), Ems("Timestamp", 5 * SECOND, "EmsTimeX = X")], "Letter")

Multiple EMS columns, multiple grouping columns

The following example builds on the previous by calculating the EMS of multiple columns with each UpdateByOperation. Also, the groups are defined by unique combinations of letter and boolean in the Letter and Truth columns, respectively.

baseTime = parseInstant("2023-01-01T00:00:00 ET")

source = emptyTable(20).update("Timestamp = baseTime + i *  SECOND", "Letter = (i % 2 == 0) ? `A` : `B`", "Truth = randomBool()", "X = i", "Y = randomInt(5, 10)")

result = source.updateBy([Ems(2, "EmsTickX = X", "EmsTickY = Y"), Ems("Timestamp", 3 * SECOND, "EmsTimeX = X", "EmsTimeY = Y")], "Letter", "Truth")

Multiple `UpdateByOperations`, multiple grouping columns

The following example builds on the previous by calculating the tick- and time-based EMS of the X and Y columns using different EMS UpdateByOperations. This allows each EMS to have its own decay rate. The decay rates are reflected in the renamed resultant columns.

baseTime = parseInstant("2023-01-01T00:00:00 ET")

source = emptyTable(20).update("Timestamp = baseTime + i *  SECOND", "Letter = (i % 2 == 0) ? `A` : `B`", "Truth = randomBool()", "X = i", "Y = randomInt(5, 10)")

emsTickX = Ems(1, "EmsTickX_1row = X")
emsTickY = Ems(5, "EmsTickY_5rows = Y")
emsTimeX = Ems("Timestamp", 2 * SECOND, "EmsTimeX_2sec = X")
emsTimeY = Ems("Timestamp", 4 * SECOND, "EmsTimeY_4sec = Y")

result = source.updateBy([emsTickX, emsTickY, emsTimeX, emsTimeY], "Letter", "Truth")

Ems