I have the same exact need in my company's IoT project.
Sensors send values at irregular times, only when their reading change.
The last stored value is to be considered "the" value until the next one.
For simplicity, let's say the value is a boolean status ("presence"/"absence"
in our case) encoded as "1" or "0".
I need to count the number of devices that are in state "1" for fixed time
intervals. Using
SELECT COUNT(value) ... GROUP BY TIME (1h) FILL(previous)
the filling is done _after_ the GROUPing, so the count doesn't reflect the
number of devices that are _simultaneously_ in state "1". Using SUM() instead
of COUNT() makes no difference.
The fact that Influx doesn't accept arithmetic expression as arguments of
aggregate functions makes it difficult to work around this limitation.
Another thing that would help immensely would be a working INTEGRAL function:
if it were possible to do something like:
SELECT INTEGRAL("value" != 0 ? 1 : 0) ... GROUP BY TIME (1h) FILL(previous)
one could easily extract the fraction of time inside every fixed interval when
the value satisfied a given condition (value<>0 in my example, but could be
anything).
At the moment I am querying all the raw data in the time interval and sending
it to AWS Lambda for processing, but it would be much better if this kind of
time-based manipulations were possible directly inside InfluxDB.
Thank you for any suggestion.
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