ES|QL time series aggregation functions

The first STATS under a TS source command supports aggregation functions per time series. These functions accept up to two arguments. The first argument is required and denotes the metric name of the time series. The second argument is optional and allows specifying a sliding time window for aggregating metric values. Note that this is orthogonal to time bucketing of output results, as specified in the BY clause (e.g. through TBUCKET). For example, the following query calculates the average rate of requests per host for every minute, using values over a sliding window of 10 minutes:

		TS metrics
  | WHERE TRANGE(1h)
  | STATS AVG(RATE(requests, 10m)) BY TBUCKET(1m), host
		
	

Accepted window values are currently limited to multiples of the time bucket interval in the BY clause. If no window is specified, the time bucket interval is implicitly used as a window.

All window values are accepted, though there are performance optimizations for the cases where the window is a multiple of the time bucket interval.

It's currently not allowed to mix windows that are smaller than the time bucket for one metrics and larger than the time bucket for another metrics, in the same query.

When a time series aggregation function is used directly in STATS (that is, not wrapped in an outer aggregation such as AVG() or SUM()), results are implicitly grouped by every time series dimension and include a _timeseries column. You can narrow or make this grouping explicit with the WITHOUT grouping function ( ). Refer to Grouping time series for details and examples.

The following time series aggregation functions are supported: