Documentation

keys() function

keys() returns the columns that are in the group key of each input table.

Each output table contains a row for each group key column label. A single group key column label is stored in the specified column for each row. All columns not in the group key are dropped.

Function type signature
(<-tables: stream[A], ?column: string) => stream[B] where A: Record, B: Record
  • Copy
  • Fill window

For more information, see Function type signatures.

Parameters

column

Column to store group key labels in. Default is _value.

tables

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

Examples

Return group key columns for each input table

data
    |> keys()
  • Copy
  • Fill window

View example input and output

Return all distinct group key columns in a single table

data
    |> keys()
    |> keep(columns: ["_value"])
    |> distinct()
  • Copy
  • Fill window

View example input and output

Return group key columns as an array

  1. Use keys() to replace the _value column with the group key labels.
  2. Use findColumn() to return the _value column as an array.
import "sampledata"

sampledata.int()
    |> keys()
    |> findColumn(fn: (key) => true, column: "_value")// Returns [tag]
  • Copy
  • Fill window

Was this page helpful?

Thank you for your feedback!


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.

Read more

InfluxDB 3 Core and Enterprise are now in Beta

InfluxDB 3 Core and Enterprise are now available for beta testing, available under MIT or Apache 2 license.

InfluxDB 3 Core is a high-speed, recent-data engine that collects and processes data in real-time, while persisting it to local disk or object storage. InfluxDB 3 Enterprise is a commercial product that builds on Core’s foundation, adding high availability, read replicas, enhanced security, and data compaction for faster queries. A free tier of InfluxDB 3 Enterprise will also be available for at-home, non-commercial use for hobbyists to get the full historical time series database set of capabilities.

For more information, check out: