Ok here is a problem we have. We are streaming data into influxdb. The data is sampled at 1s interval.
From time to time we need to query data over large time range. 5 years is a good example. We do not need 1s precision, but would like this query to be fast.
SELECT mean(value) as value FROM “values” WHERE ( id=$F_0 ) AND time >= 2016-07-22T00:00:00-07:00 AND time < 2021-07-21T00:00:00-07:00 GROUP BY time(86400s),id fill(none);
Query like this, will take > 20s
We tried down sampling data using continuous queries, but its a major challenge to keep down sampled data synchronized with actual data. Our ingestion is not constant, we could have outages and catch up, that results in gaps in down sampled data.
Is there a performant way to fill gaps in data produced by continuous queries?
is there a performant way to query data over large periods of time at 24h interval for example?