We are integrating measurements with auto normalization (“all”). Measurements come in batch (ie. one canonical, multiple measurements). I’ve observed that the normalization queue (as shown in the InvalidationQueue.countAll() output) often gets bigger than the total number of different Timeseries we have (sometimes up to 4x times) and I am trying to understand why. When this happens we often have multiple measurements canonical uploads in status “PROCESSING”.
Therefore I am wondering if a normalization is triggered for each measurement (or each canonical) or if they are properly grouped together.
For instance, if I have measurements 1 & 2 for timeseries A in canonical C1, and measurement 3 for timeseries A in canonical C2:
- Will the integration of 1 then 2 (from C1) trigger a single normalization (at least if A has not been yet normalized when 2 is integrated to Cassandra)?
- Will the integration of 3 add another item to the normalization queue even when A has not been yet normalized (because the normalization of A due to 1 & 2 is still in the queue)?