tickscript.join() function

tickscript.join() is a user-contributed function maintained by the package author.

tickscript.join() merges two input streams into a single output stream based on specified columns with equal values and appends a new measurement name.

This function is comparable to Kapacitor JoinNode.

Function type signature
(measurement: A, tables: B, ?on: [string]) => stream[{C with _measurement: A}] where B: Record, C: Record

For more information, see Function type signatures.



(Required) Map of two streams to join.


List of columns to join on. Default is ["_time"].


(Required) Measurement name to use in results.


Join two streams of data

import "array"
import "contrib/bonitoo-io/tickscript"

metrics =
        rows: [
            {_time: 2021-01-01T00:00:00Z, host: "host1", _value: 1.2},
            {_time: 2021-01-01T01:00:00Z, host: "host1", _value: 0.8},
            {_time: 2021-01-01T02:00:00Z, host: "host1", _value: 3.2},
            {_time: 2021-01-01T00:00:00Z, host: "host2", _value: 8.4},
            {_time: 2021-01-01T01:00:00Z, host: "host2", _value: 7.3},
            {_time: 2021-01-01T02:00:00Z, host: "host2", _value: 7.9},
        |> group(columns: ["host"])

states =
        rows: [
            {_time: 2021-01-01T00:00:00Z, host: "host1", _value: "dead"},
            {_time: 2021-01-01T01:00:00Z, host: "host1", _value: "dead"},
            {_time: 2021-01-01T02:00:00Z, host: "host1", _value: "alive"},
            {_time: 2021-01-01T00:00:00Z, host: "host2", _value: "alive"},
            {_time: 2021-01-01T01:00:00Z, host: "host2", _value: "alive"},
            {_time: 2021-01-01T02:00:00Z, host: "host2", _value: "alive"},
        |> group(columns: ["host"])

    tables: {metric: metrics, state: states},
    on: ["_time", "host"],
    measurement: "example-m",

View example 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: