Documentation

Operate on columns

This page documents an earlier version of InfluxDB OSS. InfluxDB 3 Core is the latest stable version.

API token hashing is enabled by default in InfluxDB OSS 2.9.0

Stronger token security: tokens are stored as hashes on disk, so a copy of the database file doesn’t expose usable tokens. Existing tokens are hashed on first startup and the original strings can’t be recovered afterward — capture any plaintext tokens you still need before you upgrade.

For more information, see Token hashing.

Use the following common queries to operate on columns:

These examples use NOAA water sample data.

Find and count unique values in a column

Find and count the number of unique values in a specified column. The following examples find and count unique locations where data was collected.

Find unique values

This query:

  • Uses group() to ungroup data and return results in a single table.
  • Uses keep() and unique() to return unique values in the specified column.
from(bucket: "noaa")
    |> range(start: -30d)
    |> group()
    |> keep(columns: ["location"])
    |> unique(column: "location")

Example results

location
coyote_creek
santa_monica

Count unique values

This query:

  • Uses group() to ungroup data and return results in a single table.
  • Uses keep(), unique(), and then count() to count the number of unique values.
from(bucket: "noaa")
    |> group()
    |> unique(column: "location")
    |> count(column: "location")

Example results

location
2

Recalculate the _values column

To recalculate the _value column, use the with operator in map() to overwrite the existing _value column.

The following query:

  • Uses filter() to filter the average_temperature measurement.
  • Uses map() to convert Fahrenheit temperature values into Celsius.

from(bucket: "noaa")
    |> filter(fn: (r) => r._measurement == "average_temperature")
    |> range(start: -30d)
    |> map(fn: (r) => ({r with _value: (float(v: r._value) - 32.0) * 5.0 / 9.0} ))
_field_measurement_start_stop_timelocation_value
degreesaverage_temperature1920-03-05T22:10:01Z2020-03-05T22:10:01Z2019-08-17T00:00:00Zcoyote_creek27.77777777777778
degreesaverage_temperature1920-03-05T22:10:01Z2020-03-05T22:10:01Z2019-08-17T00:06:00Zcoyote_creek22.77777777777778
degreesaverage_temperature1920-03-05T22:10:01Z2020-03-05T22:10:01Z2019-08-17T00:12:00Zcoyote_creek30
degreesaverage_temperature1920-03-05T22:10:01Z2020-03-05T22:10:01Z2019-08-17T00:18:00Zcoyote_creek31.666666666666668
degreesaverage_temperature1920-03-05T22:10:01Z2020-03-05T22:10:01Z2019-08-17T00:24:00Zcoyote_creek25
degreesaverage_temperature1920-03-05T22:10:01Z2020-03-05T22:10:01Z2019-08-17T00:30:00Zcoyote_creek21.11111111111111
degreesaverage_temperature1920-03-05T22:10:01Z2020-03-05T22:10:01Z2019-08-17T00:36:00Zcoyote_creek28.88888888888889
degreesaverage_temperature1920-03-05T22:10:01Z2020-03-05T22:10:01Z2019-08-17T00:42:00Zcoyote_creek24.444444444444443
degreesaverage_temperature1920-03-05T22:10:01Z2020-03-05T22:10:01Z2019-08-17T00:48:00Zcoyote_creek29.444444444444443
degreesaverage_temperature1920-03-05T22:10:01Z2020-03-05T22:10:01Z2019-08-17T00:54:00Zcoyote_creek26.666666666666668
degreesaverage_temperature1920-03-05T22:10:01Z2020-03-05T22:10:01Z2019-08-17T01:00:00Zcoyote_creek21.11111111111111
•••••••••••••••••••••

Calculate a new column

To use values in a row to calculate and add a new column, use map(). This example below converts temperature from Fahrenheit to Celsius and maps the Celsius value to a new celsius column.

The following query:

  • Uses filter() to filter the average_temperature measurement.
  • Uses map() to create a new column calculated from existing values in each row.
from(bucket: "noaa")
    |> filter(fn: (r) => r._measurement == "average_temperature")
    |> range(start: -30d)
    |> map(fn: (r) => ({r with celsius: (r._value - 32.0) * 5.0 / 9.0}))

Example results

_start_stop_field_measurementlocation_time_valuecelsius
1920-03-05T22:10:01Z2020-03-05T22:10:01Zdegreesaverage_temperaturecoyote_creek2019-08-17T00:00:00Z8227.78
1920-03-05T22:10:01Z2020-03-05T22:10:01Zdegreesaverage_temperaturecoyote_creek2019-08-17T00:06:00Z7322.78
1920-03-05T22:10:01Z2020-03-05T22:10:01Zdegreesaverage_temperaturecoyote_creek2019-08-17T00:12:00Z8630.00
1920-03-05T22:10:01Z2020-03-05T22:10:01Zdegreesaverage_temperaturecoyote_creek2019-08-17T00:18:00Z8931.67
1920-03-05T22:10:01Z2020-03-05T22:10:01Zdegreesaverage_temperaturecoyote_creek2019-08-17T00:24:00Z7725.00
1920-03-05T22:10:01Z2020-03-05T22:10:01Zdegreesaverage_temperaturecoyote_creek2019-08-17T00:30:00Z7021.11
1920-03-05T22:10:01Z2020-03-05T22:10:01Zdegreesaverage_temperaturecoyote_creek2019-08-17T00:36:00Z8428.89
1920-03-05T22:10:01Z2020-03-05T22:10:01Zdegreesaverage_temperaturecoyote_creek2019-08-17T00:42:00Z7624.44
1920-03-05T22:10:01Z2020-03-05T22:10:01Zdegreesaverage_temperaturecoyote_creek2019-08-17T00:48:00Z8529.44
1920-03-05T22:10:01Z2020-03-05T22:10:01Zdegreesaverage_temperaturecoyote_creek2019-08-17T00:54:00Z8026.67
••••••••••••••••••••••••

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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.

Also new in 2.9.0:

  • Configurable backup compression
  • Restore support for backups containing hashed tokens
  • Tighter Edge Data Replication queue validation
  • Flux upgrade
  • Compaction reliability improvements

Key enhancements in Explorer 1.9

Explorer 1.9 is now available with InfluxQL support, an AI-assisted Flux to SQL converter (beta), and new live sample data simulators.

View Explorer 1.9 release notes

Explorer 1.9 includes new features and improvements that make it easier to query, visualize, and manage data.

Highlights:

  • Flux to SQL converter (beta): Convert Flux queries to SQL with an AI-assisted converter.
  • InfluxQL support: Query data with InfluxQL in the Data Explorer and dashboards, and save and load InfluxQL queries.
  • InfluxQL visualizations: Render line and bar charts from InfluxQL results with per-tag series grouping.
  • Query error history: Review a history of query errors in the query tool.
  • Live sample data simulators: Generate continuous live sample data with new bird data and signal generator simulators.

For more details, see Explorer 1.9 release notes

InfluxDB 3.10 is now available

InfluxDB 3 Core 3.10 adds an automatic catalog format upgrade, a configurable query-concurrency limit, and processing engine improvements.

Key updates in InfluxDB 3 Core 3.10:

  • Catalog format upgrade: the on-disk catalog automatically upgrades from format v2 to v3 on first 3.10 startup. Migration is one-way—back up your catalog before upgrading.
  • --max-concurrent-queries: limit concurrent queries (adjustable at runtime).
  • GET /ready endpoint for readiness probes.
  • Processing engine: cross-database queries and trigger lockdown flags.

For more information, see the InfluxDB 3 Core release notes.

InfluxDB 3.10 is now available

InfluxDB 3 Enterprise 3.10 adds automated backup and restore, row-level deletions, and user management, with an automatic catalog format upgrade and performance preview improvements.

Key updates in InfluxDB 3 Enterprise 3.10:

  • Catalog format upgrade: the on-disk catalog automatically upgrades from format v2 to v3 on first 3.10 startup. Migration is one-way—back up your catalog before upgrading.
  • Automated backup and restore (beta)
  • Row-level deletions
  • User management (authentication and RBAC) — preview
  • Performance preview improvements

Backup and restore, row-level deletions, and the performance preview require the Enterprise storage engine upgrade (opt-in beta). Beta and preview features are subject to breaking changes and aren’t recommended for production use.

For more information, see the InfluxDB 3 Enterprise release notes

Telegraf Enterprise is now generally available

Telegraf Enterprise is now generally available, along with Telegraf Controller v1.0.

Telegraf Enterprise combines Telegraf Controller, a centralized management console for Telegraf, with official support from InfluxData. Manage configurations, monitor fleet health, and operate tens of thousands of Telegraf agents from a single system.

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.

If using Docker to install and run InfluxDB, the latest tag will point to InfluxDB 3 Core. To avoid unexpected upgrades, use specific version tags in your Docker deployments. For example, if using Docker to run InfluxDB v2, replace the latest version tag with a specific version tag in your Docker pull command–for example:

docker pull influxdb:2