Docker Execution Mode

The following tutorial illustrates how to run the Cosmos dbt Docker Operators and the required setup for them.

Requirements

1. Docker with docker daemon (Docker Desktop on MacOS). Follow the Docker installation guide.

2. Airflow

3. Astronomer-cosmos package containing the dbt Docker operators

4. Postgres docker container

5. Docker image built with required dbt project and dbt DAG

6. dbt DAG with dbt docker operators in the Airflow DAGs directory to run in Airflow

More information on how to achieve 2-6 is detailed below.

Step-by-step instructions

Install Airflow and Cosmos

Create a python virtualenv, activate it, upgrade pip to the latest version and install Apache Airflow® & astronomer-postgres

python -m venv venv
source venv/bin/activate
pip install --upgrade pip
pip install apache-airflow
pip install "astronomer-cosmos[dbt-postgres]"

Setup Postgres database

You will need a postgres database running to be used as the database for the dbt project. Run the following command to run and expose a postgres database

docker run --name some-postgres -e POSTGRES_PASSWORD="<postgres_password>" -e POSTGRES_USER=postgres -e POSTGRES_DB=postgres -p5432:5432 -d postgres

Build the dbt Docker image

For the Docker operators to work, you need to create a docker image that will be supplied as image parameter to the dbt docker operators used in the DAG.

Clone the cosmos-example repo

git clone https://github.com/astronomer/cosmos-example.git
cd cosmos-example

Create a docker image containing the dbt project files and dbt profile by using the Dockerfile, which will be supplied to the Docker operators.

docker build -t dbt-jaffle-shop:1.0.0 -f Dockerfile.postgres_profile_docker_k8s .

Note

If running on M1, you may need to set the following envvars for running the docker build command in case it fails

export DOCKER_BUILDKIT=0
export COMPOSE_DOCKER_CLI_BUILD=0
export DOCKER_DEFAULT_PLATFORM=linux/amd64

Take a read of the Dockerfile to understand what it does so that you could use it as a reference in your project.

• The dbt profile file is added to the image

• The dags directory containing the dbt project jaffle_shop is added to the image

• The dbt_project.yml is replaced with postgres_profile_dbt_project.yml which contains the profile key pointing to postgres_profile as profile creation is not handled at the moment for K8s operators like in local mode.

Setup and Trigger the DAG with Airflow

Copy the dags directory from cosmos-example repo to your Airflow home

cp -r dags $AIRFLOW_HOME/

Run Airflow

airflow standalone

Note

You might need to run airflow standalone with sudo if your Airflow user is not able to access the docker socket URL or pull the images in the Kind cluster.

Log in to Airflow through a web browser http://localhost:8080/, using the user airflow and the password described in the standalone_admin_password.txt file.

Enable and trigger a run of the jaffle_shop_docker DAG. You will be able to see the following successful DAG run.