Executing Ephemeral dbt Models

Introduction

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.

Instructions

1. Open the terminal by clicking on Terminal -> New Terminal:

2. Move into the dbt project folder by entering the following command:

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cd ca_dbt_project

3. Execute the following command to build the dbt project:

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# 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:

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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:

Copy code\dt dbt_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:

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select * from dbt_outputs.f_orders_avg_discount_yearly order by year;

Summary

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.