Databricks and Peekalink integration
How to connect Databricks and Peekalink
Create a new workflow and add the first step
In n8n, click the "Add workflow" button in the Workflows tab to create a new workflow. Add the starting point – a trigger on when your workflow should run: an app event, a schedule, a webhook call, another workflow, an AI chat, or a manual trigger. Sometimes, the HTTP Request node might already serve as your starting point.
Build your own Databricks and Peekalink integration
Create custom Databricks and Peekalink workflows by choosing triggers and actions. Nodes come with global operations and settings, as well as app-specific parameters that can be configured. You can also use the HTTP Request node to query data from any app or service with a REST API.
Supported API Endpoints for Databricks
List clusters
Retrieve a list of all the clusters in your Databricks workspace.
Create cluster
Creates a cluster with the specified Databricks Runtime version and cluster node type.
Delete cluster
Permanently deletes a cluster from your Databricks workspace.
Delete cluster
Permanently deletes the cluster with the specified cluster ID from the workspace.
Create cluster
Creates a new cluster in the Databricks workspace.
Create job
Creates a Databricks job that runs the specified notebook on the specified cluster.
Create directory
Creates an empty folder in a volume.
Upload file
Uploads a file to a volume.
List directory contents
Lists the contents of a volume.
Delete file
Deletes a file from a volume.
Delete directory
Deletes a folder from a volume.
List groups
Lists the display names for all of the available groups within the Databricks account.
To set up Databricks integration, add the HTTP Request node to your workflow canvas and authenticate it using a generic authentication method. The HTTP Request node makes custom API calls to Databricks to query the data you need using the API endpoint URLs you provide.
These API endpoints were generated using n8n
n8n AI workflow transforms web scraping into an intelligent, AI-powered knowledge extraction system that uses vector embeddings to semantically analyze, chunk, store, and retrieve the most relevant API documentation from web pages. Remember to check the Databricks official documentation to get a full list of all API endpoints and verify the scraped ones!
Databricks and Peekalink integration details
Other integrations with Peekalink
FAQ
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