Frequently asked questions about the Databricks extension for Visual Studio Code
This article lists frequently asked questions about the Databricks extension for Visual Studio Code. See What is the Databricks extension for Visual Studio Code?.
What if I have the Databricks extension for Visual Studio Code installed already?
If you install a newer version of Databricks extension for Visual Studio Code, the extension makes a best effort to upgrade. You can always switch back to the pre-release version, or choose a specific version, as long as you have Visual Studio Code version 1.86.0 or above. See Install a different version of the extension.
What if I have the Databricks CLI already installed?
The Databricks extension for Visual Studio Code uses the currently installed version of the Databricks CLI.
What happens if I have a Databricks Asset Bundles project that I created before I installed the extension?
Simply open your project in version 2 of the extension. See Open an existing Databricks Asset Bundles project.
What happens if I have an existing project in Visual Studio Code that I want to migrate to Databricks Asset Bundles?
The extension makes it easy convert your Visual Studio Code project to a Databricks project. See Convert a project to a Databricks project.
I see that I can add a cluster to my configuration in the extension. What happens when I run my bundle with this configured?
For jobs, if the setting is toggled on, the configured cluster takes precedence in dev. For pipeline tasks, a new cluster is always created to run the pipeline.
What Databricks Runtime version is required to use Databricks extension for Visual Studio Code?
Databricks Runtime version 11.2 and above is required for basic extension functionality, such as deploying bundles and running notebooks. Databricks Runtime version 13.3 and above is required for features that rely on Databricks Connect, such as debugging notebook cells.
How does dbx by Databricks Labs relate to the Databricks extension for Visual Studio Code?
The main features of dbx by Databricks Labs include:
- Project scaffolding.
- Limited local development through the
dbx executecommand. - CI/CD for Databricks jobs.
The Databricks extension for Visual Studio Code enables local development and remotely running Python code files on Databricks clusters, and remotely running Python code files and notebooks in Databricks jobs. dbx can continue to be used for project scaffolding and CI/CD for Databricks jobs.
What happens if I already have an existing Databricks configuration profile that I created through the Databricks CLI?
You can select your existing configuration profile when you configure the Databricks extension for Visual Studio Code. With the extension and your project opened, do the following:
- In the Configuration view, click Auth Type, and then click the gear (Sign in to Databricks workspace) icon.
- In the Command Palette, select your existing configuration profile.
Can I use the Databricks extension for Visual Studio Code with a proxy?
Yes. See the recommended solution in Error when synchronizing through a proxy.