window() function

The window() function groups records based on a time value. The function calculates time windows and stores window bounds in the _start and _stop columns. _start and _stop values are assigned to rows based on the _time value.

A single input row may be placed into zero or more output tables depending on the parameters passed into the window() function.

window(
  every: 5m,
  period: 5m,
  offset: 12h,
  timeColumn: "_time",
  startColumn: "_start",
  stopColumn: "_stop",
  location: "UTC",
  createEmpty: false
)

Parameters

every

Duration of time between windows. Defaults to period value.

period

Duration of the window. Period is the length of each interval. It can be negative, indicating the start and stop boundaries are reversed. Defaults to every value.

offset

Offset is the duration by which to shift the window boundaries. It can be negative, indicating that the offset goes backwards in time. Defaults to 0, which will align window end boundaries with the every duration.

timeColumn

The column containing time. Defaults to "_time".

startColumn

The column containing the window start time. Defaults to "_start".

stopColumn

The column containing the window stop time. Defaults to "_stop".

location

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

Flux uses the timezone database (commonly referred to as “tz” or “zoneinfo”) provided by the operating system.

createEmpty

Specifies whether empty tables should be created. Defaults to false.

tables

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

Examples

The following examples use data provided by the sampledata package to show how window() transforms data.

• Window data into 30 second intervals
• Window every 20 seconds covering 40 second periods
• Window by calendar month

Window data into 30 second intervals

import "sampledata"

data = sampledata.int()
  |> range(start: sampledata.start, stop: sampledata.stop)
 
data 
  |> window(every: 30s)

Window every 20 seconds covering 40 second periods

import "sampledata"

data = sampledata.int()
  |> range(start: sampledata.start, stop: sampledata.stop)
 
data 
  |> window(every: 20s, period: 40s)

Window by calendar month

The following example uses generate.from to illustrate windowing by calendar month.

import "generate"

timeRange = {start: 2021-01-01T00:00:00Z, stop: 2021-04-01T00:00:00Z}

data = generate.from(
    count: 6,
    fn: (n) => n + n,
    start: timeRange.start,
    stop: timeRange.stop
  )
  |> range(start: timeRange.start, stop: timeRange.stop)

data
  |> window(every: 1mo)