Advancing Spark - Row-Level Security and Dynamic Masking with Unity Catalog

[@prasad8195]

Hello @Simon I require your assistance with a specific use case. Suppose I create a view using the `%sql` declaration with the `CREATE OR REPLACE VIEW` statement and grant the Databricks group 'X' usage access to the schema and catalog, along with select access to the view. Consequently, a user who is a member of the Databricks group 'X' will gain visibility of the object and the ability to retrieve data from the view. However, a challenge arises when I execute the `CREATE OR REPLACE VIEW` statement again. It appears that the previously granted permissions for Databricks group 'X' vanish, subsequently restricting users in that group from accessing the object. Could you please provide guidance /feedback on this ? Your assistance is greatly appreciated.

[@bharathchunchu]

How about performance if we use column level masking on huge tables ?

[@DucNguyen-pw6hc]

how can it mask other datatype like timestamp or map? It's a very very simple example so I think it can not apply for data governance comprehensively

[@ruchitasurve835]

Does it work nested columns!

[@rajkumarv5791]

Currently, Would it even be possible to a bit of both, .i.e. Row based masking a column. Ex: Hide the phone number/email if the person is not an admin.

[@agasti2007]

That is not bit of both. It is called column level security.

[@theamazingworldofsonicandd2637]

Will RLS and column masking be available on Delta Live Materialized Views?

[@AdvancingAnalytics]

Goooood question. Don't know yet, will dig into it!

[@lodbrockcraft1369]

Does this configuration also work for synapse sql pool?

[@AdvancingAnalytics]

Nope, this is a Databricks Unity Catalog feature