filter() filters data based on conditions defined in a predicate function (
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
Single argument predicate function that evaluates
Records representing each row are passed to the function as
Records that evaluate to
true are included in output tables.
Records that evaluate to null or
false are excluded from output tables.
Action to take with empty tables. Default is
- keep: Keep empty tables.
- drop: Drop empty tables.
Input data. Default is piped-forward data (
- Filter based on InfluxDB measurement, field, and tag
- Keep empty tables when filtering
- Filter values based on thresholds
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")
Filter values based on thresholds
import "sampledata" sampledata.int() |> filter(fn: (r) => r._value > 0 and r._value < 10)
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