Documentation

Query fields and tags

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

Use the filter() function to query data based on fields, tags, or any other column value. filter() performs operations similar to the SELECT statement and the WHERE clause in InfluxQL and other SQL-like query languages.

The filter() function

filter() has an fn parameter that expects a predicate function, an anonymous function comprised of one or more predicate expressions. The predicate function evaluates each input row. Rows that evaluate to true are included in the output data. Rows that evaluate to false are excluded from the output data.

// ...
  |> filter(fn: (r) => r._measurement == "example-measurement" )

The fn predicate function requires an r argument, which represents each row as filter() iterates over input data. Key-value pairs in the row record represent columns and their values. Use dot notation or bracket notation to reference specific column values in the predicate function. Use logical operators to chain multiple predicate expressions together.

// Row record
r = {foo: "bar", baz: "quz"}

// Example predicate function
(r) => r.foo == "bar" and r["baz"] == "quz"

// Evaluation results
(r) => true and true

Filter by fields and tags

The combination of from(), range(), and filter() represent the most basic Flux query:

  1. Use from() to define your bucket.
  2. Use range() to limit query results by time.
  3. Use filter() to identify what rows of data to output.
from(bucket: "db/rp")
  |> range(start: -1h)
  |> filter(fn: (r) =>
      r._measurement == "example-measurement" and
      r._field == "example-field" and
      r.tag == "example-tag"
  )

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New in InfluxDB 3.5

Key enhancements in InfluxDB 3.5 and the InfluxDB 3 Explorer 1.3.

See the Blog Post

InfluxDB 3.5 is now available for both Core and Enterprise, introducing custom plugin repository support, enhanced operational visibility with queryable CLI parameters and manual node management, stronger security controls, and general performance improvements.

InfluxDB 3 Explorer 1.3 brings powerful new capabilities including Dashboards (beta) for saving and organizing your favorite queries, and cache querying for instant access to Last Value and Distinct Value caches—making Explorer a more comprehensive workspace for time series monitoring and analysis.

For more information, check out:

InfluxDB Docker latest tag changing to InfluxDB 3 Core

On November 3, 2025, 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