Connect to data sources from your Fabric User data functions item (Preview)

Fabric User data functions provides native data source connections by using the Manage connections feature in the Fabric portal. This feature allows you to connect to your Fabric data sources without having to create connection strings or manage access credentials.

In this article, you learn how to:

• Create a new connection for your user data functions item.
• Use your new connection in your function code.
• Modify or delete your data connection.

Supported data source connections in Fabric User data functions

The following data sources are currently supported for Fabric User data functions:

• Fabric SQL databases
• Fabric warehouses
• Fabric lakehouses
• Fabric mirrored databases

Create a new data connection for your user data functions item

Any data connections you add are associated with your user data functions item and can be referenced in the code of any of your functions. To follow this guide, you need an existing Fabric User data functions item and an existing Fabric data source.

1. Access the Manage connections feature from the Functions portal

Find and select Manage connections in the ribbon of the Functions portal editor.

The pane that opens contains any data connections you created. Select Add data connection to create a new connection.

2. Select your data connection from the OneLake catalog

When you select Add data connection, the OneLake catalog opens with a list of all the data sources your user account has access to. The list is filtered to include only supported data sources, some of which might be in other workspaces.

Choose your data source, then select Connect.

Once created, the new connection to the data source you selected is shown in the side pane on the Connections tab. When you see the connection, take note of the Alias field that was generated for it. You need this alias to reference the connection from any function in your user data functions item.

3. Use your connection alias in your function code

Once you're back in the portal editor, you need to add the alias of the connection you created in the Manage Connections tab to your code. In this case we will use a code sample called "Read data from a table in SQL Database". You can find this sample by clicking on the Edit tab, then clicking on the "Insert sample" button and navigating to "SQL Database".

This is the sample code that was inserted:

@udf.connection(argName="sqlDB",alias="<alias for sql database>")
@udf.function()
def read_from_sql_db(sqlDB: fn.FabricSqlConnection)-> list:
    # Replace with the query you want to run
    query = "SELECT * FROM (VALUES ('John Smith', 31), ('Kayla Jones', 33)) AS Employee(EmpName, DepID);"

    # Establish a connection to the SQL database
    connection = sqlDB.connect()
    cursor = connection.cursor()

    query.capitalize()

    # Execute the query
    cursor.execute(query)

    # Fetch all results
    results = []
    for row in cursor.fetchall():
        results.append(row)

    # Close the connection
    cursor.close()
    connection.close()
        
    return results

To use the data connection you created, modify the following line in this sample: @udf.connection(argName="sqlDB",alias="<alias for sql database>") by replacing the value of the alias with the one you obtained from the Manage Connections menu. The following code shows this example with the value ContosoSalesDat:

@udf.connection(argName="sqlDB",alias="ContosoSalesDat")
@udf.function()
def read_from_sql_db(sqlDB: fn.FabricSqlConnection)-> list:
    [...]

After modifying the code, publish your function using the Publish button in the toolbar. This operation may take a few minutes.

Once the publishing is completed, you can run your function by hovering on its name in the Functions Explorer list, and clicking on the "Run" button in the side panel. The bottom panel "Output" will show the outcome of running the function.

And that's all you need to connect to a data source from your Fabric User Data Functions.

Next steps

• Create a Fabric User data functions item from within Fabric or use the Visual Studio Code extension
• Learn about the User data functions programming model