Getting started with DBT with Databricks

Let's start with the question what is dbt?

“dbt is a transformation workflow that helps you get more work done while producing higher quality results. You can use dbt to modularize and centralize your analytics code, while also providing your data team with guardrails typically found in software engineering workflows.” You can read more at Whatis dbt? | dbt Developer Hub (getdbt.com)

 

There are couple of options to get started, one is pip with virtual environment but I will use pip inside a docker container.

Let’s get started, first thing first start the docker container with below command:

$ docker run -p 8888:8888 -p 8000:8080 -v D:/projects/rnd2/:/home/jovyan/work jupyter/minimal-notebook

In above command, I am exposing two ports 1) 8888 and 2) 8080. The first port will be used to connect to jupyter notebook/terminal and the other port will be used to expose the dbt documentation.

Access your juypter notebook server with http://localhost:8888/lab/tree/work  like shown below:

Click on the terminal and execute the pip statement:

Note: For other target, you need to install other package. For instance dbt-snowflake for Snowflake.

Once installed, execute the below command to create a dbt project

Copy the /home/jovyan/.dbt/profiles.yml to your project folder like below:

Now everything is done, let’s open the Visual Studio code

You can explore the generated codes to understand the structure and codes etc.

I have generated the databricks token and supplied to profiles.yml file. Go to the terminal in your jupyter notbook server and execute dbt commands.

The first command is the dbt debug, which validates the configuration.

 

To apply your transformation, run dbt run command.

Points to remember:

Everytime you execute dbt run, a transformation is applied. With this concept you integrate this with orchestration tool like Apache Airflow or even with Databrick workflow or even with Docker container which will run your dbt command and destroy itself.

You can go in databricks to check the bronze schema which will have 1 table loaded.

Lets run dbt test

As we know that first model contains 1 null record.

Lets look at documentation part, run dbt docs generate and then serve. By default it exposes the documentation at port 8080 because we are running this doc server inside a container and we already mapped our 8000 port to 8080. So simply access localhost:8000 will take you to dbt generated documentation

Navigate to http://localhost:8000

View lineage as well

 

That’s for now, next I will share how we can use dbt to build data vault layer.