datagroup_trigger lets you specify the datagroup to use as a caching policy for the derived table. The datagroup itself is defined in the model file using the datagroup parameter.

Adding the datagroup_trigger parameter to a derived table makes the derived table a persistent derived table (PDT). The table is written into a scratch schema on your database and regenerated as specified by the datagroup parameter.

If you use datagroup_trigger for your PDT, you don’t need to use the sql_trigger_value or persist_for parameters. If you do, you will get a warning in the Looker IDE, and only the datagroup_trigger will be used.

Examples

Create a persistent native derived table called customer_orders that is rebuilt when triggered by the datagroup named order_datagroup:

view: customer_orders { derived_table: { explore_source: order { column: customer_id { field: order.customer_id } column: lifetime_orders { field: order.lifetime_orders } } datagroup_trigger: order_datagroup } }

Create a customer_orders persistent derived table based on a SQL query that is rebuilt when triggered by the datagroup called etl_datagroup:

view: customer_orders { derived_table: { sql: SELECT customer_id, COUNT(*) AS lifetime_orders FROM order GROUP BY 1 ;; datagroup_trigger: etl_datagroup } }

Common challenges

If you have PDTs that are dependent on other PDTs, be careful not to specify incompatible datagroup caching policies.