diff --git a/docs/stream-aggregation.md b/docs/stream-aggregation.md index 5970c5ce2..2f53ad59e 100644 --- a/docs/stream-aggregation.md +++ b/docs/stream-aggregation.md @@ -448,15 +448,15 @@ For example, see below time series produced by config with aggregation interval increase aggregation -Aggregating irregular and sporadic metrics (received from [Lambdas](https://aws.amazon.com/lambda/) -or [Cloud Functions](https://cloud.google.com/functions)) can be controlled via [staleness_inteval](#stream-aggregation-config). - `increase` can be used as an alternative for [rate](https://docs.victoriametrics.com/MetricsQL.html#rate) function. For example, if we have `increase` with `interval` of `5m` for a counter `some_counter`, then to get `rate` we should divide -the resulting aggregation by the `interval` in seconds: `some_counter:5m_increase / 300` is similar to `rate(some_counter[5m])`. +the resulting aggregation by the `interval` in seconds: `some_counter:5m_increase / 5m` is similar to `rate(some_counter[5m])`. Please note, opposite to [rate](https://docs.victoriametrics.com/MetricsQL.html#rate), `increase` aggregations can be combined safely afterwards. This is helpful when the aggregation is calculated by more than one vmagent. +Aggregating irregular and sporadic metrics (received from [Lambdas](https://aws.amazon.com/lambda/) +or [Cloud Functions](https://cloud.google.com/functions)) can be controlled via [staleness_inteval](#stream-aggregation-config). + ### count_series `count_series` counts the number of unique [time series](https://docs.victoriametrics.com/keyConcepts.html#time-series).