Documentation

map() function

map() iterates over and applies a function to input rows.

Each input row is passed to the fn as a record, r. Each r property represents a column key-value pair. Output values must be of the following supported column types:

  • float
  • integer
  • unsigned integer
  • string
  • boolean
  • time

Output data

Output tables are the result of applying the map function (fn) to each record of the input tables. Output records are assigned to new tables based on the group key of the input stream. If the output record contains a different value for a group key column, the record is regrouped into the appropriate table. If the output record drops a group key column, that column is removed from the group key.

Preserve columns

map() drops any columns that are not mapped explicitly by column label or implicitly using the with operator in the fn function. The with operator updates a record property if it already exists, creates a new record property if it doesn’t exist, and includes all existing properties in the output record.

data
    |> map(fn: (r) => ({ r with newColumn: r._value * 2 }))
Function type signature
(<-tables: stream[A], fn: (r: A) => B, ?mergeKey: bool) => stream[B]

For more information, see Function type signatures.

Parameters

fn

(Required) Single argument function to apply to each record. The return value must be a record.

mergeKey

(Deprecated) Merge group keys of mapped records. Default is false.

tables

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

Examples

Square the value in each row

import "sampledata"

sampledata.int()
    |> map(fn: (r) => ({r with _value: r._value * r._value}))

View example input and output

Create a new table with new columns

import "sampledata"

sampledata.int()
    |> map(
        fn: (r) => ({time: r._time, source: r.tag, alert: if r._value > 10 then true else false}),
    )

View example input and output

Add new columns and preserve existing columns

Use the with operator on the r record to preserve columns not directly operated on by the map operation.

import "sampledata"

sampledata.int()
    |> map(fn: (r) => ({r with server: "server-${r.tag}", valueFloat: float(v: r._value)}))

View example input and output


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InfluxDB OSS 2.9.0: API tokens are hashed by default

Stronger token security in InfluxDB OSS 2.9.0 — tokens are hashed on disk by default. Existing tokens are hashed on first startup and can’t be recovered afterward. Capture any plaintext tokens you still need before you upgrade.

View InfluxDB OSS 2.9.0 release notes

Hashed tokens authenticate exactly like unhashed tokens — clients and integrations keep working.

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View Explorer 1.9 release notes

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InfluxDB 3.10 is now available

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InfluxDB Docker latest tag changing to InfluxDB 3 Core

On September 15, 2026, the latest tag for InfluxDB Docker images will point to InfluxDB 3 Core. To avoid unexpected upgrades, use specific version tags in your Docker deployments.

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docker pull influxdb:2