1. Shared Data Science Workspaces Using Databricks Repos

    Python

    In Data Science projects, it's common to manage and collaborate on code using version control systems like Git. Databricks offers an integration with Git through the Databricks Repos API, which allows you to synchronize your notebooks and code with a Git repository. This feature promotes collaboration among data scientists by enabling them to share, review, and manage code within a project workspace easily.

    Here's how you can create a shared Data Science workspace by setting up a Databricks Repo resource:

    1. Databricks Repo: We will use the databricks.Repo resource which enables us to link a Git repository to a Databricks workspace path. You can specify various settings like the repository URL, branch, and commit hash.

    2. GitProvider: GitProvider is necessary to configure the integration with the Git repository. This might be something like 'github', 'bitbucket', etc.

    3. Access Token: To authenticate with your Git provider, you may require a personal access token or similar credentials, which should be handled securely, for example by using Pulumi's secret management.

    Let's write the Pulumi program in Python to create a Databricks Repo:

    import pulumi import pulumi_databricks as databricks # Create a Databricks Repo resource that points to your GitHub repository # Replace the placeholders with actual values for your 'url', 'branch', and 'path' where the repo is to be checked out. databricks_repo = databricks.Repo("shared-data-science-repo", url="https://github.com/your-org/your-repo.git", branch="main", # The branch to sync with path="/Repos/your-path" # The workspace directory where the repo will be checked out ) # Export the ID of the Databricks repo which can be used to reference it in other API calls pulumi.export('repo_id', databricks_repo.id)

    This program performs the following:

    • It imports the required Pulumi and Databricks modules.
    • It instantiates the databricks.Repo resource with necessary properties:
      • url: This is the URL to your Git repository.
      • branch: The branch you want to synchronize with. Typically this might be main or master.
      • path: The path within your Databricks workspace where you want your Repo to be synced. This will typically be within the /Repos directory of your Databricks workspace.

    Replace the placeholders for url, branch, and path with the actual values that correspond to the Git repository you want to work with.

    To apply the above, ensure you have the Pulumi CLI installed and configured to work with your Databricks workspace. Typically, this means you need to log in to your Databricks workspace and generate a token that you can then use with Pulumi.

    After that, to run the Pulumi program, navigate to the directory containing your Pulumi Python program, and execute:

    pulumi up

    This command will provision the resources declared in your Pulumi program. Once completed, the output will give you the 'repo_id' which is an identifier for the created Databricks Repo in your workspace. You can now visit your Databricks workspace and should find your Repo synced and ready for collaboration.

    It is important to note that the program does not cover things like user permissions within Databricks, conflict resolution, or continuous integration/deployment strategies, which are also important considerations when setting up a collaborative workspace.


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