2.10 Windowed Aggregates

2.10 Windowed Aggregates

This calculation is an optimized SLIDINGAGG variant that uses historian-provided aggregates to speed up data retrieval time. Instead of calculating over a sliding window, it calculates the aggregates over consecutive fixed windows within the time period.

The syntax of the WINDOWAGG function is:

calc/WINDOWAGG(input, operation, window)

input — an integer or any valid timeseries source

operation — the short name for one of the operators listed below (AVG, COUNT, , NUMBAD, STDDEV, VAR, MIN, MAX, SUM, DIFF)

window — any valid time input — see section 2.2

The available operations for WINDOWAGG are AVG, MIN, MAX, COUNT, STDDEV, VAR. The functions as the same as for the SLIDINGAG calculation.

Important Notes on WindowAGG

• To achieve best performance, this calc should be used on historian tags, not on other calculations.

• Windows are anchored to closest midnight UTC before requested range.

• When using not “round” window size, windows since day 2 of request will be placed after previous, not after midnight UTC.

• Aggregates like MIN, MAX and COUNT are stepped (step-after), raw points are generated at beginning of each window.

• Aggregates like AVG, STDDEV, VAR are linearly interpolated, raw points are generated in the middle of each window.

• When requesting interpolated points, window size is increased to match interpolated point interval, when requested window count would be at least twice more than requested interpolated point count. This changes slightly how this calc works, but makes sure that all values in requested area are used, so effectively we query for a continuous time range.