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Transform data by running a notebook

Use the Notebook activity to run notebooks you create in Microsoft Fabric as part of your Data Factory pipelines. Notebooks let you run Apache Spark jobs to bring in, clean up, or transform your data as part of your data workflows. It’s easy to add a Notebook activity to your pipelines in Fabric, and this guide walks you through each step.

Prerequisites

To get started, you must complete the following prerequisites:

Create a notebook activity

  1. Create a new pipeline in your workspace.

  2. Search for Notebook in the pipeline Activities pane, and select it to add it to the pipeline canvas.

    Screenshot of the Fabric UI with the Activities pane and Notebook activity highlighted.

  3. Select the new Notebook activity on the canvas if it isn't already selected.

    Screenshot showing the General settings tab of the Notebook activity.

    Refer to the General settings guidance to configure the General settings tab.

Configure notebook settings

Select the Settings tab.

Under Connection, select the authentication method for the notebook run and provide the required credentials or identity configuration based on your selection:

  • Service Principal (SPN) – Recommended for production scenarios to ensure secure, automated execution without relying on user credentials.
  • Workspace Identity (WI) – Ideal for managed environments where centralized identity governance is required.

Select an existing notebook from the Notebook dropdown, and optionally specify any parameters to pass to the notebook.

Screenshot showing the Notebook settings tab highlighting the tab, where to choose a notebook, and where to add parameters.

Using Fabric Workspace Identity (WI) in the Notebook activity

  1. Create the Workspace Identity

    You must enable WI in your workspace (this may take a moment to load). Create a Workspace Identity in your Fabric workspace. Note that the WI should be created in the same workspace as your Pipeline.

    Check out the docs on Workspace Identity.

  2. Enable tenant-level settings

    Enable the following tenant setting (it's disabled by default): Service principals can call Fabric public APIs.

    You can enable this setting in the Fabric admin portal. For more information about this setting, see the enable service principal authentication for admin APIs article.

  3. Grant workspace permissions to the Workspace Identity

    Open the workspace, select Manage access, and assign permissions to the Workspace Identity. Contributor access is sufficient for most scenarios. If your Notebook is not in the same workspace as your Pipeline, you'll need to assign the WI you created in your Pipeline's workspace at least Contributor access to your Notebook's workspace.

    Check out the docs on Give users access to workspaces.

Set session tag

In order to minimize the amount of time it takes to execute your notebook job, you could optionally set a session tag. Setting the session tag instructs Spark to reuse any existing Spark session, minimizing the startup time. Any arbitrary string value can be used for the session tag. If no session exists, a new one would be created using the tag value.

Screenshot showing the Notebook settings tab highlighting the tab, where to add session tag.

Note

To be able to use the session tag, High concurrency mode for pipeline running multiple notebooks option must be turned on. This option can be found under the High concurrency mode for Spark settings under the Workspace settings

Screenshot showing the Workspace settings tab highlighting the tab, where to enable high concurrency mode for pipelines running multiple notebooks.

Save and run or schedule the pipeline

Switch to the Home tab at the top of the pipeline editor, and select the save button to save your pipeline. Select Run to run it directly, or Schedule to schedule it. You can also view the run history here or configure other settings.

Screenshot showing the Home tab in the pipeline editor with the tab name, Save, Run, and Schedule buttons highlighted.

Known issues

  • The WI option in connections settings does not surface in some instances. This is a bug that a fix is being worked on at the moment.