<ul data-eligibleForWebStory="true"><li>BigQuery lacks native support for fine-grained row-level security, but it can be simulated using views, SESSION_USER(), and join tables.</li><li>To implement row-level security in BigQuery, create a base table with sensitive data, a mapping table for user access, and a view that restricts data based on the logged-in user.</li><li>Create a base table with sensitive data using the CREATE TABLE statement.</li><li>Insert data into the customer_orders table using the INSERT INTO statement.</li><li>Create a table to manage row-level access and insert user emails into it.</li><li>Create a view that filters data based on the SESSION_USER() function.</li><li>The view joins the base table with the mapping table and filters rows based on the logged-in user's email.</li><li>Advantages of this approach include compatibility with standard BigQuery, scalability for multi-user scenarios, and centralized logic in the view.</li><li>This method provides a simple and powerful way to safeguard sensitive data in BigQuery by leveraging externalized access logic and SESSION_USER().</li></ul>

Row-Level Security in BigQuery Using Views and SESSION_USER()

Discover more