Connect Databricks and apotheo to Build Intelligent Automations
Choose a Trigger
When this happens...
- Request a new Trigger for Databricks
Choose an Action
Automatically do this!
- Request a new Action for apotheo
Enable Integrations or automations with these events of Databricks and apotheo
Enable Integrations or automations with these events of Databricks and apotheo
Actions
Create Cluster
Creates a new Databricks cluster for processing tasks.
Create a Directory
Create a directory by a path.
Delete a Job
This action deletes a job by ID.
Create a Repo
Creates a repo in the workspace and links it to the remote Git repo specified.
Delete Repo
Delete a Repo
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Frequently Asked Questions
To start, connect both your Databricks and apotheo accounts to viaSocket. Once connected, you can set up a workflow where an event in Databricks triggers actions in apotheo (or vice versa).
Absolutely. You can customize how Databricks data is recorded in apotheo. This includes choosing which data fields go into which fields of apotheo, setting up custom formats, and filtering out unwanted information.
The data sync between Databricks and apotheo typically happens in real-time through instant triggers. And a maximum of 15 minutes in case of a scheduled trigger.
Yes, viaSocket allows you to add custom logic or use built-in filters to modify data according to your needs.
Yes, you can set conditional logic to control the flow of data between Databricks and apotheo. For instance, you can specify that data should only be sent if certain conditions are met, or you can create if/else statements to manage different outcomes.
About Databricks
Databricks is a cloud-based data platform that provides a collaborative environment for data engineering, data science, and machine learning. It offers a unified analytics platform that simplifies data processing and enables organizations to build and deploy AI models at scale. With its powerful integration capabilities, Databricks allows teams to work together seamlessly, accelerating innovation and driving data-driven decision-making.
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