Where to find comprehensive docs on databricks.yaml / DAB settings options
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
07-12-2024 10:50 AM
Where can I find documentation on how to set cluster settings (e.g., AWS instance type, spot vs on-demand, number of machines) in Databricks Asset Bundle databicks.yaml files? The only documentation I've come across mentions these things indirectly, for example this link.
Here is an example part my DAB that I'm hoping to complete:
resources:
jobs:
clicks:
job_clusters:
- job_cluster_key: job_cluster
new_cluster:
node_type_id: i3.xlarge
spark_version: 13.3.x-scala2.12
But I'm not sure the names of fields to specify spot vs on demand, number of machines, etc. I'm having a really hard time finding comprehensive documentation on DABs and their options on Google and on this site.
- Labels:
-
Workflows
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
07-14-2024 01:01 AM
I have faced similar problem while developing CI/CD using DABs for ML Jobs. There is no straight forward documentation listing all the options for DABs(As far as I know). As a workaround you can look at the REST API documentation which has all the options which are available for creating a job. Similar options are available in DABs as well.
https://docs.databricks.com/api/workspace/jobs/create
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
07-14-2024 04:53 AM
You're right, wasn't able to find much either.
What I did was create an all purpose compute and looked at the yaml/json config from the UI and then copied the attributes to my DAB config.
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
07-19-2024 05:52 AM
Hi @spicysheep ,
Thank you for reaching out to our community! We're here to help you.
To ensure we provide you with the best support, could you please take a moment to review the response and choose the one that best answers your question? Your feedback not only helps us assist you better but also benefits other community members who may have similar questions in the future.
If you found the answer helpful, consider giving it a kudo. If the response fully addresses your question, please mark it as the accepted solution. This will help us close the thread and ensure your question is resolved.
We appreciate your participation and are here to assist you further if you need it!
Thanks,
Rishabh

