interpolated_rate()
Calculate the rate of change in a counter over a time period. Data points at the exact boundaries of the time period aren’t needed. The function linerally interpolates the counter values at the boundaries from adjacent CounterSummaries if they are unknown.
This is the same value as an interpolated_delta divided by the duration in seconds.
2. interpolated_rate(
4. summary CounterSummary,
6. start TIMESTAMPTZ,
8. interval INTERVAL,
10. prev CounterSummary,
12. next CounterSummary
14. ) RETURNS DOUBLE PRECISION
For more information about counter aggregation functions, see the hyperfunctions documentation.
Required arguments
| Name | Type | Description |
|---|---|---|
summary |
CounterSummary |
The input CounterSummary from a counter_agg call |
start |
TIMESTAMPTZ |
The start of the interval which the rate should be computed over (if there is a preceeding point) |
interval |
INTERVAL |
The length of the interval which the rate should cover |
Optional arguments
| Name | Type | Description |
|---|---|---|
prev |
CounterSummary |
The CounterSummary from the prior interval, used to interpolate the value at start. If NULL, the first timestamp in summary is used as the start of the interval. |
next |
CounterSummary |
The CounterSummary from the following interval, used to interpolate the value at start + interval. If NULL, the last timestamp in summary will be used as the end of the interval. |
Returns
| Name | Type | Description |
|---|---|---|
interpolated_rate |
DOUBLE PRECISION |
The per-second rate of change of the counter between the specified bounds. If the raw data contains no points calculated at those bounds, the bounding values are linearly interpolated from neighboring CounterSummaries. |
Sample usage
2. SELECT
4. id,
6. bucket,
8. interpolated_rate(
10. summary,
12. bucket,
14. '15 min',
16. LAG(summary) OVER (PARTITION BY id ORDER by bucket),
18. LEAD(summary) OVER (PARTITION BY id ORDER by bucket)
20. )
22. FROM (
24. SELECT
26. id,
28. time_bucket('15 min'::interval, ts) AS bucket,
30. counter_agg(ts, val) AS summary
32. FROM foo
34. GROUP BY id, time_bucket('15 min'::interval, ts)
36. ) t
