Malloy is an experimental language for describing data relationships and transformations. It is both a semantic modeling language and a querying language that runs queries against a relational database. Malloy currently supports BigQuery and Postgres, as well as querying Parquet and CSV files via DuckDB.
The easiest way to try Malloy is with our VS Code Extension, which provides a place to create Malloy models, execute queries, get help, and more. VS Code is a text editor and IDE (integrated development environment) that runs on your desktop or in your browser. A few ways to install the extension:
.csv
or .parquet
file in a repository.To get to know the Malloy language, follow our Quickstart.
Note: The Malloy VSCode Extension tracks a small amount of anonymous usage data. You can opt out in the extension settings. Learn more.
Documentation:
YouTube - Watch demos / walkthroughs of Malloy
If you would like to work on Malloy, take a look at the instructions for developing Malloy.
Here is a simple example of a Malloy query:
run: bigquery.table('malloydata-org.faa.flights') -> {
where: origin ? 'SFO'
group_by: carrier
aggregate:
flight_count is count()
average_flight_time is flight_time.avg()
}
In SQL this would be expressed:
SELECT
carrier,
COUNT(*) as flight_count,
AVG(flight_time) as average_flight_time
FROM `malloy-data.faa.flights`
WHERE origin = 'SFO'
GROUP BY carrier
ORDER BY flight_count desc -- malloy automatically orders by the first aggregate
Learn more about the syntax and language features of Malloy in the Quickstart.