In this post, we are going to understand the Databricks Workspace. It will help to get familiar with the Databricks platform.
Overview
Databricks workspace is a kind of organizer which keeps notebooks, library, folder, MLFlow experiment.
Notebook: It is a web-based interface document that keeps all commands, visualizations in a cell.
Library: It is a collection of code available for the notebook or job to use.
Folder: It is a storage to keep all the notebooks for better organize.
MLExperiment: It is a collection of MLFlow for training a model.
Default Databricks Workspace
By default, there are two workspaces already available in Databricks – Shared and Users.
Shared: It is basically a shared location across the team to keep all the notebooks and others stuffs.
Users: It is an individual user’s work directory to use and create a notebook.
If you right-click on the workspace, you will see multiple options like
Create: Notebook, Library, Folder, Experiment
Clone: To copy an existing notebook with a diff name
Import: To upload any existing notebook from local
Export: Export the notebook in Archive and HTML format
Copy to link address: Get the absolute path with link
Wrapping Up
In this post, we have learned about the Workspace available in Databricks and how it organizes the notebooks, library, etc. You can check the next post to get familiar with Databricks Notebook.