Get started with Flux

Flux is a functional data scripting language designed to unify querying, processing, analyzing, and acting on data into a single syntax.

Flux overview

To understand how Flux works conceptually, consider the process of treating water. Water is pulled from a source, limited by demand, piped through a series of stations to modify (remove sediment, purify, and so on), and delivered in a consumable state.

Basic Flux query

Like treating water, a Flux query does the following:

1. Retrieves a specified amount of data from a source.
2. Filters data based on time or column values.
3. Processes and shapes data into expected results.
4. Returns the result.

To see how to retrieve data from a source, select the data source: InfluxDB, CSV, or PostgreSQL.

from(bucket: "example-bucket")
    |> range(start: -1d)
    |> filter(fn: (r) => r._measurement == "example-measurement")
    |> mean()
    |> yield(name: "_results")

import "csv"

csv.from(file: "path/to/example/data.csv")
    |> range(start: -1d)
    |> filter(fn: (r) => r._measurement == "example-measurement")
    |> mean()
    |> yield(name: "_results")

import "sql"

sql.from(
    driverName: "postgres",
    dataSourceName: "postgresql://user:password@localhost",
    query: "SELECT * FROM TestTable",
)
    |> filter(fn: (r) => r.UserID == "123ABC456DEF")
    |> mean(column: "purchase_total")
    |> yield(name: "_results")

Each example includes the following functions (in the order listed):

• from() to retrieve data from the data source.
• Pipe-forward operator (|>) to send the output of each function to the next function as input.
• range(), filter(), or both to filter data based on column values.
• mean() to calculate the average of values returned from the data source.
• yield() to yield results to the user.

For detailed information about basic Flux queries, see Flux query basics.

For an introduction to Flux and how it works with time series data, watch the following video: