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Applying Row-Level Security to Regional Customer Data

I recently had the task of implementing row-level security for customer data in a regional sales table. The goal was to ensure that only analysts in the ‘regional_analysts’ account group could access data for regions other than ‘EU’, while also allowing access to EU data for all users. I decided to use Databricks Unity Catalog’s row-level security features to achieve this.

Creating a Security Function for Region Filtering

To start, I needed to define a function that would determine whether a user is allowed to access a specific row based on the region. I created a function called region_filter in the production.security schema. This function checks if the user is part of the ‘regional_analysts’ group or if the region is ‘EU’. This way, all users can access EU data, and only those in the ‘regional_analysts’ group can access other regions.

CREATE OR REPLACE FUNCTION production.security.region_filter(region STRING) 
RETURN is_account_group_member('regional_analysts') OR region = 'EU';

I noticed that the function was created successfully, which meant I could proceed with applying it to the table.

Applying the Filter to the Customers Table

Next, I applied the row-level filter to the production.sales.customers table. I used the ALTER TABLE command with the SET ROW FILTER clause, specifying the region_filter function and the region column as the filter condition. This ensures that only rows matching the filter criteria are accessible to users.

ALTER TABLE production.sales.customers SET ROW FILTER production.security.region_filter ON (region);

I verified that the filter was applied successfully. This means that any future queries on the customers table will automatically respect the row-level security rules I defined.

Querying the Filtered Customers Table

To confirm that the row-level filter was working as expected, I ran a SELECT query on the production.sales.customers table. I wanted to see what data was being returned based on the filter. The results showed that only rows where the region was ‘EU’ or the user was part of the ‘regional_analysts’ group were accessible.

SELECT * FROM production.sales.customers;

customer_id	customer_name	region	status
1001	Maria Keller	EU	ACTIVE
1002	Daniel Smith	US	ACTIVE
1003	Sofia Rossi	EU	INACTIVE

I noticed that the query returned rows for both EU and US regions, which made sense because the function allowed access to EU data for all users and only regional analysts could access US data. This confirmed that the row-level security was working as intended.

Overall, this process helped me understand how to use Databricks Unity Catalog’s row-level security to control data access based on user roles and data attributes. It’s a powerful feature that ensures data is only accessible to the right people, which is critical for compliance and security in a multi-regional environment.