experimental.window() function

experimental.window() groups records based on time.

_start and _stop columns are updated to reflect the bounds of the window the row's time value is in. Input tables must have _start, _stop, and _time columns.

A single input record can be placed into zero or more output tables depending on the specific windowing function.

By default the start boundary of a window will align with the Unix epoch modified by the offset of the location option.

Calendar months and years

every, period, and offset support all valid duration units, including calendar months (1mo) and years (1y).

Function type signature

(
    <-tables: stream[{A with _time: time, _stop: time, _start: time}],
    ?createEmpty: bool,
    ?every: duration,
    ?location: {zone: string, offset: duration},
    ?offset: duration,
    ?period: duration,
) => stream[{A with _time: time, _stop: time, _start: time}]

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Parameters

every

Duration of time between windows. Default is the 0s.

period

Duration of the window. Default is 0s.

Period is the length of each interval. It can be negative, indicating the start and stop boundaries are reversed.

offset

Duration to shift the window boundaries by. Default is 0s.

offset can be negative, indicating that the offset goes backwards in time.

location

Location used to determine timezone. Default is the location option.

createEmpty

Create empty tables for empty windows. Default is false.

tables

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

Examples

• Window data into thirty second intervals
• Window by calendar month

Window data into thirty second intervals

import "experimental"

data
    |> experimental.window(every: 30s)

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Input data

Output data

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Window by calendar month

import "experimental"

data
    |> experimental.window(every: 1mo)

{{< expand-wrapper >}} {{% expand "View example input and output" %}}

Input data

Output data

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