Malloy

Malloy is an open source 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 supports every database connection registered by the core @malloydata/malloy library — at the time of writing that includes BigQuery, Postgres, MySQL, Snowflake, MotherDuck, DuckDB, Presto, and Trino. The list grows with each release; the live set is whatever shows up in the connection editor in your installed version.

We've built a Visual Studio Code extension to facilitate building Malloy data models, querying and transforming data, and creating simple visualizations and dashboards.

Click here to try Malloy in your browser!

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Install the Visual Studio Code Extension locally

To write your own Malloy models, use the VS Code Extension, currently available for Mac, Linux, and Windows machines.

1. Download Visual Studio Code: Download Visual Studio Code

2. Add the Malloy (pre-release) extension from the Visual Studio Code Marketplace: Open VS Code and click the Extensions button on the far left (it looks like 4 blocks with one flying away). This will open the Extension Marketplace. Search for "Malloy" and, once found, click "Install"

3. Download and unzip the Sample Models (models + data).

4. Open the samples folder in VS Code. In VS Code, go to File > Open Folder... select malloy-samples/duckdb > Open. DuckDB is built into the extension so you're ready to run these.

5. Start with 1_airports.malloy in the FAA dataset. This is a sub-sample of the NTSB Flights dataset. In the editor pane, above source: airports, click the word "Preview" to run a SELECT *, and click the word "Run" above any query object to run it (see gif below for example).

To get to know the Malloy language, follow the Quickstart guide and/or continue through the numbered models in the FAA directory.

Note: The Malloy VSCode Extension tracks a small amount of anonymous usage data. You can opt out in the extension settings. Learn more.

Join the Community

• Join our Malloy Slack Community! Use this community to ask questions, meet other Malloy users, and share ideas with one another.
• Use GitHub issues in this Repo to provide feedback, suggest improvements, report bugs, and start new discussions.

Resources

Documentation:

• Malloy Language - A quick introduction to the language
• eCommerce Example Analysis - a walkthrough of the basics on an ecommerce dataset (BigQuery public dataset)
• Modeling Walkthrough - introduction to modeling via the Iowa liquor sales public data set (BigQuery public dataset)

YouTube - Watch demos / walkthroughs of Malloy

Contributing

If you would like to work on the Malloy VS Code extension, take a look at the instructions for developing.

To report security issues please see our security policy.

Malloy is not an officially supported Google product.

Syntax Example

Here is a simple example of a Malloy query:

query: table('malloy-data.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.