Databricks

Workspace Commands

Interact with Databricks workspace objects including notebooks, folders, and libraries. Import, export, and organize your data engineering and ML assets.

6 commands

Pro Tips

Use 'databricks workspace export-dir' to backup entire directory trees for disaster recovery.

Export notebooks as SOURCE format to maintain version control compatibility with Git.

Use workspace ACLs to control access to sensitive notebooks and folders.

Common Mistakes

Workspace import with overwrite flag replaces existing content without backup. Export first.

Notebook execution results and state are not preserved during export - only source code.

Commands

List workspace contents

$ databricks workspace list /path/to/folder

List contents of a workspace folder.

Export notebook

$ databricks workspace export /path/to/notebook local-file.py

Export a notebook to a local file.

Import notebook

$ databricks workspace import local-file.py /path/to/notebook

Import a local file as a notebook.

Export directory

$ databricks workspace export-dir /remote/path ./local/path

Export entire workspace directory recursively.

Create directory

$ databricks workspace mkdirs /path/to/new/folder

Create a new folder in the workspace.

Delete item

$ databricks workspace rm /path/to/item --recursive

Delete a workspace item (add --recursive for folders).