When working with Databricks, you may often need to incorporate third-party dependencies to enhance your code's functionality. Whether you're using Databricks with Scala or Python, importing external jars or modules is essential for leveraging additional libraries
Steps to Add External Dependencies in Databricks
Navigate to the Cluster:
- Go to your Databricks workspace and select the cluster where you want to add the dependencies.
Access the Libraries Section:
- In the cluster configuration, find and select the 'Libraries' tab.
Install New Library:
- Click on the 'Install New' button. This will prompt you to provide the type and source of the library you wish to install.
Provide Library Details:
- Specify the details of the library, such as Maven coordinates for jars or the PyPI package name for Python modules.
Install the Library:
- After providing the necessary details, click on the 'Install' button to add the library to your cluster.
Example: Installing a Library in Azure Databricks Cluster
To illustrate, here’s a step-by-step guide to installing a library in an Azure Databricks cluster:
Go to the Cluster:
- Open your Azure Databricks workspace and navigate to the cluster you are using.
Select Libraries:
- Click on the 'Libraries' tab within the cluster configuration.
Install New Library:
- Click on the 'Install New' button.
Choose Library Source:
- Select the type of library (e.g., Maven, PyPI, etc.) and provide the source details.
Install:
Click 'Install' to add the library to your cluster.
By following these steps, you can easily manage and import third-party dependencies in your Databricks environment, ensuring your code has access to all the necessary libraries.
Conclusion
Managing dependencies at the cluster level in Databricks is a straightforward process that enhances your ability to use third-party libraries effectively. Whether you are working with Scala or Python, adding external jars or modules to your cluster ensures that your notebooks can leverage the full power of these libraries.