Accept and mount the shared assets
Learn how to accept the Delta Share from Reltio and mount the shared ML models in your Databricks workspace so that you can run the entity resolution pipeline.
After you Provide your Delta Sharing identifier to Reltio, Reltio shares the required models with your workspace. Accept and mount the share to make the assets available in your workspace.
Prerequisites
Before you begin, ensure that you have completed the following steps:
Steps to accept and mount the shared assets
To accept and mount the shared assets, follow these steps:
- In the Databricks workspace, click Catalog in the left sidebar to open Catalog Explorer.
- In Catalog Explorer, navigate to the top-right toolbar, click the gear icon, and select Delta Sharing.
- In the Delta Sharing page, select the Shared with me tab.
- Locate the incoming share from the provider named Reltio and click on it to view its details.
- On the reltio provider page, look for "embedded-er-models-prd" and click Mount to catalog next to it.
- In the mounting dialog:
- Create a new catalog
- Select all the shared schemas
- Confirm the mount
After you accept the share, a new read-only shared catalog appears in Catalog Explorer. This catalog contains the models and supporting resources required for the pipeline. When you run the pipeline, select this catalog as the location of the models.
Grant the following permissions on the shared catalog to the user or service principal that runs the pipeline:
| Resource type | Name or details | Required permissions |
|---|---|---|
| Shared models catalog | Mounted Delta Share from Reltio | USE CATALOG, USE SCHEMA, READ VOLUME, SELECT |
Verification
Verify that the shared assets are available in your workspace:
- A new read-only catalog appears in Catalog Explorer.
- The catalog contains the shared schemas, models, and related resources.
- You can open the catalog and browse the available files.
Result
The shared models and assets are available in your Databricks workspace. When you run the pipeline, select this catalog as the location of the models.
Proceed to Install the required library on the cluster to enable pipeline execution .