AQL Expression
What AQL expressions are, the two kinds (table and metric), how the pipe operator chains functions together, and the dataset context every expression needs.
An AQL expression is a structured combination of data types, operators, and functions, allowing you to query your database or define reusable metrics.
Types
There are two main types of AQL expressions:
- Table expressions: Expressions that represent a query that returns a table output, similar to SQL
- Metric expressions: Expressions that represent a reusable metric, which is basically some aggregation logic with added context
Structure
A typical AQL expression often is a combination of AQL functions combined together using the AQL pipe operator, like the followings:
A query that returns the sum of values of all orders from a order_items table:
order_items | select(value: quantity * price) | sum(value)A metric that returns the running total of number of orders in 2023:
count(orders.id)
| where(orders.created_at is @2023)
| running_total(run: orders.created_at | month())Dataset
An AQL expression only works within the context of a dataset as it requires knowledge of the models and relationships between them defined in the dataset.