Documentation

to() function

to() writes data to an InfluxDB Cloud or 2.x bucket and returns the written data.

Output data requirements

to() writes data structured using the standard InfluxDB Cloud and v2.x data structure that includes, at a minimum, the following columns:

  • _time
  • _measurement
  • _field
  • _value

All other columns are written to InfluxDB as tags.

Note: to() drops rows with null _time values and does not write them to InfluxDB.

to() does not require a package import

to() is part of the influxdata/influxdb package, but is part of the Flux prelude and does not require an import statement or package namespace.

Function type signature
(
    <-tables: stream[A],
    ?bucket: string,
    ?bucketID: string,
    ?fieldFn: (r: A) => B,
    ?host: string,
    ?measurementColumn: string,
    ?org: string,
    ?orgID: string,
    ?tagColumns: [string],
    ?timeColumn: string,
    ?token: string,
) => stream[A] where A: Record, B: Record
For more information, see Function type signatures.

Parameters

bucket

Name of the bucket to write to. bucket and bucketID are mutually exclusive.

bucketID

String-encoded bucket ID to to write to. bucket and bucketID are mutually exclusive.

host

URL of the InfluxDB instance to write to.

See InfluxDB Cloud regions or InfluxDB OSS URLs. host is required when writing to a remote InfluxDB instance. If specified, token is also required.

org

Organization name. org and orgID are mutually exclusive.

orgID

String-encoded organization ID to query. org and orgID are mutually exclusive.

token

InfluxDB API token.

InfluxDB 1.x or Enterprise: If authentication is disabled, provide an empty string (""). If authentication is enabled, provide your InfluxDB username and password using the <username>:<password> syntax. token is required when writing to another organization or when host is specified.

timeColumn

Time column of the output. Default is "_time".

measurementColumn

Measurement column of the output. Default is "_measurement".

tagColumns

Tag columns in the output. Defaults to all columns with type string, excluding all value columns and columns identified by fieldFn.

fieldFn

Function that maps a field key to a field value and returns a record. Default is (r) => ({ [r._field]: r._value }).

tables

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

Examples

Write data to InfluxDB

data =
    array.from(
        rows: [
            {
                _time: 2021-01-01T00:00:00Z,
                _measurement: "m",
                tag1: "a",
                _field: "temp",
                _value: 100.1,
            },
            {
                _time: 2021-01-01T00:01:00Z,
                _measurement: "m",
                tag1: "a",
                _field: "temp",
                _value: 99.8,
            },
            {
                _time: 2021-01-01T00:02:00Z,
                _measurement: "m",
                tag1: "a",
                _field: "temp",
                _value: 99.1,
            },
            {
                _time: 2021-01-01T00:03:00Z,
                _measurement: "m",
                tag1: "a",
                _field: "temp",
                _value: 98.6,
            },
        ],
    )

data
    |> to(
        bucket: "example-bucket",
        org: "example-org",
        token: "mYSuP3rSecR37t0k3N",
        host: "http://localhost:8086",
    )

The example above produces the following line protocol and sends it to the InfluxDB /api/v2/write endpoint:

m,tag1=a temp=100.1 1609459200000000000
m,tag1=a temp=99.8 1609459260000000000
m,tag1=a temp=99.1 1609459320000000000
m,tag1=a temp=98.6 1609459380000000000

Customize measurement, tag, and field columns in the to() operation

data =
    array.from(
        rows: [
            {
                _time: 2021-01-01T00:00:00Z,
                tag1: "a",
                tag2: "b",
                hum: 53.3,
                temp: 100.1,
            },
            {
                _time: 2021-01-01T00:01:00Z,
                tag1: "a",
                tag2: "b",
                hum: 53.4,
                temp: 99.8,
            },
            {
                _time: 2021-01-01T00:02:00Z,
                tag1: "a",
                tag2: "b",
                hum: 53.6,
                temp: 99.1,
            },
            {
                _time: 2021-01-01T00:03:00Z,
                tag1: "a",
                tag2: "b",
                hum: 53.5,
                temp: 98.6,
            },
        ],
    )

data
    |> to(
        bucket: "example-bucket",
        measurementColumn: "tag1",
        tagColumns: ["tag2"],
        fieldFn: (r) => ({"hum": r.hum, "temp": r.temp}),
    )

The example above produces the following line protocol and sends it to the InfluxDB /api/v2/write endpoint:

a,tag2=b hum=53.3,temp=100.1 1609459200000000000
a,tag2=b hum=53.4,temp=99.8 1609459260000000000
a,tag2=b hum=53.6,temp=99.1 1609459320000000000
a,tag2=b hum=53.5,temp=98.6 1609459380000000000

Write to multiple InfluxDB buckets

The example below does the following:

  1. Writes data to bucket1 and returns the data as it is written.
  2. Applies an empty group key to group all rows into a single table.
  3. Counts the number of rows.
  4. Maps columns required to write to InfluxDB.
  5. Writes the modified data to bucket2.
data
    |> to(bucket: "bucket1")
    |> group()
    |> count()
    |> map(
        fn: (r) => ({r with _time: now(), _measurement: "writeStats", _field: "numPointsWritten"}),
    )
    |> to(bucket: "bucket2")

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InfluxDB Clustered is a highly available InfluxDB 3.0 cluster built for high write and query workloads on your own infrastructure.

InfluxDB Clustered is currently in limited availability and is only available to a limited group of InfluxData customers. If interested in being part of the limited access group, please contact the InfluxData Sales team.

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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: