How to run DBT in airflow without copying our repo

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We use DBT with GCP and BigQuery for transformations in BigQuery, and the simplest approach to scheduling our daily run dbt seems to be a BashOperator in Airflow. Currently we have two separate directories / github projects, one for DBT and another for Airflow. To schedule DBT to run with Airflow, it seems like our entire DBT project would need to be nested inside of our Airflow project, that way we can point to it for our dbt run bash command?

Is it possible to trigger our dbt run and dbt test without moving our DBT directory inside of our Airflow directory? With the airflow-dbt package, for the dir in the default_args, maybe it is possible to point to the gibhub link for the DBT project here?

dbt airflow
3 Answers

My advice would be to leave your dbt and airflow codebases separated. There is indeed a better way:

  1. dockerise your dbt project in a simple python-based image where you COPY the codebase
  2. push that to DockerHub or ECR or any other docker repository that you are using
  3. use the DockerOperator in your airflow DAG to run that docker image with your dbt code

I'm assuming that you use the airflow LocalExecutor here and that you want to execute your dbt run workload on the server where airflow is running. If that's not the case and that you have access to a Kubernetes cluster, I would suggest instead to use the KubernetesPodOperator.

user_38238150

Accepted the other answer based on the consensus via upvotes and the supporting comment, however I'd like to post a 2nd solution that I'm currently using:

  • dbt and airflow repos / directories are next to each other.
  • in our airflow's docker-compose.yml, we've added our DBT directory as a volume so that airflow has access to it.
  • in our airflow's Dockerfile, install DBT and copy our dbt code.
  • use BashOperator to run dbt and test dbt.
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