Install Databricks CLI: A Step-by-Step Guide

Nov 7, 2025 by Admin 45 views

Hey data enthusiasts! Are you ready to supercharge your Databricks experience? The Databricks CLI (Command Line Interface) is your trusty sidekick for managing Databricks workspaces, clusters, jobs, and more, all from the comfort of your terminal. In this comprehensive guide, we'll walk you through installing the Databricks CLI, ensuring a smooth setup and empowering you to automate tasks, streamline workflows, and become a Databricks power user. Let's dive in and get your CLI up and running!

Prerequisites: Before You Begin

Before we jump into the Databricks CLI installation process, let's make sure you've got the essentials covered. Think of these as the ingredients you need to bake the perfect CLI cake:

Python: The Databricks CLI is built using Python, so you'll need Python installed on your system. Make sure you have Python 3.6 or later. You can usually check your Python version by opening your terminal or command prompt and typing python --version or python3 --version. If Python isn't installed, head over to the official Python website (https://www.python.org/downloads/) and download the appropriate installer for your operating system.
Pip: Pip is Python's package installer, and it's what we'll use to install the Databricks CLI. Pip usually comes bundled with Python installations, but if it's missing, you can install it easily. Check if pip is already installed by typing pip --version or pip3 --version in your terminal. If it's not there, you can typically install it using your system's package manager (e.g., apt-get install python3-pip on Debian/Ubuntu, or brew install python3 on macOS with Homebrew). For Windows, the Python installer often includes an option to install pip.
A Databricks Workspace: You'll obviously need access to a Databricks workspace to interact with using the CLI. If you don't have one, sign up for a Databricks account. You can sign up for a free trial or choose a paid plan, depending on your needs. Once you have a workspace, make a note of your Databricks instance URL; you'll need it later.
Authentication Credentials: You'll need a way to authenticate with your Databricks workspace. There are several methods, including personal access tokens (PATs), OAuth, and service principals. The easiest method is usually to create a personal access token (PAT) in your Databricks workspace. Go to User Settings in your Databricks workspace, and generate a new token. Save this token securely; you'll use it to configure the CLI.

Once you've confirmed that you have these prerequisites set up, we're ready to proceed to install the Databricks CLI!

Installing the Databricks CLI: A Detailed Guide

Alright, let's get down to the nitty-gritty and install the Databricks CLI. The installation process is pretty straightforward, but the exact steps may vary slightly depending on your operating system. Don't worry, we'll cover the most common scenarios.

Installation via Pip (Recommended)

The easiest and most recommended way to install the Databricks CLI is using pip. This method works well on most operating systems and ensures you get the latest version of the CLI.

Open your terminal or command prompt.
Run the installation command: Type pip install databricks-cli and press Enter. If you have both Python 2 and Python 3 installed, you might need to use pip3 install databricks-cli to ensure you're installing the package for Python 3.
Wait for the installation to complete. Pip will download and install the necessary packages. You should see a progress bar and some output indicating the installation's progress. If everything goes well, you'll see a message confirming the successful installation.
Verify the installation: To make sure the CLI is installed correctly, type databricks --version in your terminal and press Enter. You should see the version number of the Databricks CLI displayed. If you do, congratulations! You've successfully installed the CLI!

Installing with Homebrew (macOS)

If you're a macOS user and have Homebrew installed (a popular package manager for macOS), you can install the Databricks CLI using Homebrew. This is another convenient way to manage your CLI installation.

Open your terminal.
Run the installation command: Type brew install databricks-cli and press Enter. Homebrew will handle the installation process.
Wait for the installation to complete. Homebrew will download and install the CLI and its dependencies.
Verify the installation: Similar to the pip installation, type databricks --version in your terminal to check the CLI version.

Installing from Source (Advanced)

If you need a specific version of the CLI, want to contribute to the project, or simply like to get your hands dirty, you can install the CLI from source. This is a bit more involved, but it gives you more control.

Clone the Databricks CLI repository: Clone the repository from GitHub using git clone https://github.com/databricks/databricks-cli.git.
Navigate to the CLI directory: Change your directory to the cloned repository using cd databricks-cli.
Install the CLI: Use pip install . to install the CLI from the source code. You might need to use pip3 install . if you have multiple Python versions.
Verify the installation: Again, type databricks --version in your terminal to verify the installation.

Configuring the Databricks CLI: Connecting to Your Workspace

Now that you've got the Databricks CLI installed, it's time to configure it to connect to your Databricks workspace. This is where you'll provide the CLI with your workspace details and authentication credentials. Don't worry, it's easy!

Configuring Authentication Using PAT

Open your terminal.
Run the configure command: Type databricks configure and press Enter. This command will start the configuration process.
Enter your Databricks instance URL: The CLI will prompt you to enter the Databricks instance URL. This is the URL of your Databricks workspace (e.g., https://<your-workspace-id>.cloud.databricks.com). Copy and paste it in, then press Enter.
Enter your personal access token (PAT): The CLI will then ask for your personal access token. Paste your PAT here and press Enter. Remember, keep your PAT safe! Don't share it, and treat it like a password.
Verify the configuration: To verify that the configuration is working, you can try listing the clusters in your workspace using the command databricks clusters list. If you see a list of your clusters, the configuration was successful!

Configuring Authentication using OAuth (Advanced)

For more secure authentication, you can use OAuth. This involves using a web browser to log in to your Databricks workspace.

Open your terminal.
Run the configure command: Type databricks configure --oauth and press Enter.
Follow the on-screen prompts: The CLI will open a browser window and prompt you to log in to your Databricks workspace using your credentials.
Authorize the CLI: You will then be asked to authorize the CLI to access your Databricks workspace.
Verify the configuration: Similar to the PAT method, try listing your clusters using databricks clusters list to verify.

Basic Databricks CLI Commands: Getting Started

Alright, your Databricks CLI is installed and configured! Now, let's explore some basic commands to get you started. The CLI offers a wide range of functionalities, but let's start with the essentials:

databricks clusters list: Lists all the clusters in your Databricks workspace. This is a great way to verify your configuration.
databricks jobs list: Lists all the jobs in your Databricks workspace.
databricks runs list --job-id <job-id>: Lists the runs for a specific job. Replace <job-id> with the actual ID of your job.
databricks workspace ls <path>: Lists the contents of a workspace directory. For example, databricks workspace ls /Users/<your-username>/.
databricks workspace cp <local-file> <dbfs-path>: Copies a local file to DBFS. Replace <local-file> with the path to your local file and <dbfs-path> with the DBFS path (e.g., dbfs:/FileStore/).
databricks workspace mkdirs <path>: Creates a directory in the workspace. For example, databricks workspace mkdirs /Users/<your-username>/new_directory/.

These are just a few examples. The CLI has many more commands for managing your Databricks resources. To get a complete list of commands and options, type databricks --help in your terminal.

Troubleshooting Common Issues

Even though the Databricks CLI installation is usually straightforward, sometimes you might run into issues. Here are some common problems and how to solve them:

Command Not Found: If you get an error like "databricks: command not found," it usually means the CLI isn't installed correctly or isn't in your system's PATH. Double-check your installation steps, and make sure you can find the databricks executable in your system. You might need to restart your terminal or shell.
Authentication Errors: If you're getting authentication errors, the most common cause is an incorrect instance URL or personal access token (PAT). Double-check these details and make sure they are correct. Also, verify that your PAT is still valid and hasn't expired. If you are using OAuth, ensure that you have authorized the CLI.
Python Version Conflicts: If you have multiple Python versions installed, make sure you're using the correct one for the CLI. Try specifying pip3 instead of pip when installing or using the CLI.
Proxy Issues: If you're behind a proxy, you might need to configure your proxy settings for pip. You can do this by setting environment variables like http_proxy and https_proxy.
Permissions Issues: Ensure you have the necessary permissions to access your Databricks workspace and the resources you're trying to manage.

If you're still stuck, check the official Databricks documentation for detailed troubleshooting guides or search online for solutions. The Databricks community is also a great resource for help.

Conclusion: You're Now a Databricks CLI Master!

Congratulations! You've successfully installed and configured the Databricks CLI and learned some essential commands. Now, you're ready to automate tasks, manage your Databricks resources efficiently, and become a true Databricks power user. Remember to explore the CLI's extensive documentation and experiment with different commands to unlock its full potential.

This is just the beginning. The Databricks CLI can be a game-changer for your data engineering and data science workflows. Happy coding, and have fun using the Databricks CLI, guys!