Executing Ephemeral dbt Models
In this lab step, you will execute the dbt models you previously defined and check that the ephemeral model is leveraged by the full-refresh model but not stored in the database.
1. Open the terminal by clicking on Terminal -> New Terminal:
2. Move into the dbt project folder by entering the following command:
3. Execute the following command to build the dbt project:
# The export command is needed to let dbt know the profiles file is in the current directory export DBT_PROFILES_DIR='.' dbt run
After a few seconds, dbt will complete the execution with an output similar to the following:
As you can see, no model named int_more_two_orders has been created. That's because the ephemeral model has been included in models that leveraged it as a CTE and not stored in the database.
4. Execute the following command to log into the database:
psql -U postgres -d ca_dbt
5. Enter the following command to list out the available tables in the schema that dbt uses for the outputs:
As you can see, only the f_orders_avg_discount_yearly full-refresh model has been materialized.
6. Enter the following SQL query to make a query on the f_orders_avg_discount_yearly table:
select * from dbt_outputs.f_orders_avg_discount_yearly order by year;
In this lab step, you executed the dbt models you previously defined and checked that the ephemeral model is leveraged by the full-refresh model but not stored in the database.
Check whether the dbt models have been executed.