Documentation

filter() function

filter() filters data based on conditions defined in a predicate function (fn).

Output tables have the same schema as the corresponding input tables.

Function type signature
(<-tables: stream[A], fn: (r: A) => bool, ?onEmpty: string) => stream[A] where A: Record
For more information, see Function type signatures.

Parameters

fn

(Required) Single argument predicate function that evaluates true or false.

Records representing each row are passed to the function as r. Records that evaluate to true are included in output tables. Records that evaluate to null or false are excluded from output tables.

onEmpty

Action to take with empty tables. Default is drop.

Supported values:

  • keep: Keep empty tables.
  • drop: Drop empty tables.

tables

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

Examples

Filter based on InfluxDB measurement, field, and tag

from(bucket: "example-bucket")
    |> range(start: -1h)
    |> filter(
        fn: (r) => r._measurement == "cpu" and r._field == "usage_system" and r.cpu == "cpu-total",
    )

Keep empty tables when filtering

import "sampledata"
import "experimental/table"

sampledata.int()
    |> filter(fn: (r) => r._value > 18, onEmpty: "keep")

View example input and output

Filter values based on thresholds

import "sampledata"

sampledata.int()
    |> filter(fn: (r) => r._value > 0 and r._value < 10)

View example input and output


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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.

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