datagroup_trigger

Usage

view: my_view {
  derived_table: {
    datagroup_trigger: my_datagroup
    ...
  }
}

Hierarchy View File view derived_table datagroup_trigger

Default Value None Accepts The name of a datagroup defined in the model file

Definition

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.