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docs/stream-aggregation.md: use 5m
instead of 300
in the example query for rate() calculation from "increase" results
This makes the query easier to read and understand
Follow-up for 0df506de54
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@ -448,15 +448,15 @@ For example, see below time series produced by config with aggregation interval
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<img alt="increase aggregation" src="stream-aggregation-check-increase.png">
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Aggregating irregular and sporadic metrics (received from [Lambdas](https://aws.amazon.com/lambda/)
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or [Cloud Functions](https://cloud.google.com/functions)) can be controlled via [staleness_inteval](#stream-aggregation-config).
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`increase` can be used as an alternative for [rate](https://docs.victoriametrics.com/MetricsQL.html#rate) function.
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For example, if we have `increase` with `interval` of `5m` for a counter `some_counter`, then to get `rate` we should divide
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the resulting aggregation by the `interval` in seconds: `some_counter:5m_increase / 300` is similar to `rate(some_counter[5m])`.
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the resulting aggregation by the `interval` in seconds: `some_counter:5m_increase / 5m` is similar to `rate(some_counter[5m])`.
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Please note, opposite to [rate](https://docs.victoriametrics.com/MetricsQL.html#rate), `increase` aggregations can be
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combined safely afterwards. This is helpful when the aggregation is calculated by more than one vmagent.
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Aggregating irregular and sporadic metrics (received from [Lambdas](https://aws.amazon.com/lambda/)
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or [Cloud Functions](https://cloud.google.com/functions)) can be controlled via [staleness_inteval](#stream-aggregation-config).
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### count_series
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`count_series` counts the number of unique [time series](https://docs.victoriametrics.com/keyConcepts.html#time-series).
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