Documentation

aggregate.rate() function

aggregate.rate() is experimental and subject to change at any time.

aggregate.rate() calculates the average rate of increase per window of time for each input table.

aggregate.rate() requires that input data have _start and _stop columns to calculate windows of time to operate on. Use range() to assign _start and _stop values.

This function is designed to replicate the Prometheus rate() function and should only be used with counters.

Function type signature
(<-tables: stream[A], every: duration, ?groupColumns: [string], ?unit: duration) => stream[B] where A: Record, B: Record

For more information, see Function type signatures.

Parameters

every

(Required) Duration of time windows.

groupColumns

List of columns to group by. Default is [].

unit

Time duration to use when calculating the rate. Default is 1s.

tables

Input data. Default is piped-forward data (<-).

Examples

Calculate the average rate of change in data

import "experimental/aggregate"
import "sampledata"

data =
    sampledata.int()
        |> range(start: sampledata.start, stop: sampledata.stop)

data
    |> aggregate.rate(every: 30s, unit: 1s, groupColumns: ["tag"])

View example input and output


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The future of Flux

Flux is going into maintenance mode. You can continue using it as you currently are without any changes to your code.

Flux is going into maintenance mode and will not be supported in InfluxDB 3.0. This was a decision based on the broad demand for SQL and the continued growth and adoption of InfluxQL. We are continuing to support Flux for users in 1.x and 2.x so you can continue using it with no changes to your code. If you are interested in transitioning to InfluxDB 3.0 and want to future-proof your code, we suggest using InfluxQL.

For information about the future of Flux, see the following: