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.