I've used WINDOW functions before but only when working with data that has a fixed cadence/interval. I am likely missing something simple in aggregation but I've never had a scenario where I'm not working with fixed intervals.
I have a table the records samples at arbitrary timestamps. A sample is only recorded when it is a delta from the previous sample and the sample rate is completely irregular due to a large number of conditions. The table is very simple:
id (int)
happened_at (timestamp)
sensor_id (int)
new_value (float)
I'm trying to construct a query that will include a count of all of the samples before the happened_at of a given result row. So given an ultra simple 2 row sample data set:
id|happened_at |sensor_id| new_value
1 |2019-06-07:21:41|134679 | 123.331
2 |2019-06-07:19:00|134679 | 100.009
I'd like the result set to look like this:
happened_at |sensor_id | new_value | sample_count
2019-06-07:21:41|134679 |123.331 |2
2019-06-07:19:00|134679 |123.331 |1
I've tried:
SELECT *,
(SELECT count(sample_history.id) OVER (PARTITION BY score_history.sensor_id
ORDER BY sample_history.happened_at DESC))
FROM sensor_history
ORDER by happened_at DESC
and the duh not going to work.
(SELECT count(*)
FROM sample_history
WHERE sample_history.happened_at <= sample_timestamp)
Insights greatly appreciated.
