Skip to content

Latest commit

 

History

History

docker

Folders and files

NameName
Last commit message
Last commit date

parent directory

..
 
 
 
 
 
 

Docker for dbt

This docker file is suitable for building dbt Docker images locally or using with CI/CD to automate populating a container registry.

Building an image:

This Dockerfile can create images for the following targets, each named after the database they support:

  • dbt-core (no db-adapter support)
  • dbt-postgres
  • dbt-redshift
  • dbt-bigquery
  • dbt-snowflake
  • dbt-spark
  • dbt-third-party (requires additional build-arg)
  • dbt-all (installs all of the above in a single image)

In order to build a new image, run the following docker command.

docker build --tag <your_image_name>  --target <target_name> <path/to/dockerfile>

Note: Docker must be configured to use BuildKit in order for images to build properly!


By default the images will be populated with the most recent release of dbt-core and whatever database adapter you select. If you need to use a different version you can specify it by git ref using the --build-arg flag:

docker build --tag <your_image_name> \
  --target <target_name> \
  --build-arg <arg_name>=<git_ref> \
  <path/to/dockerfile>

valid arg names for versioning are:

  • dbt_core_ref
  • dbt_postgres_ref
  • dbt_redshift_ref
  • dbt_bigquery_ref
  • dbt_snowflake_ref
  • dbt_spark_ref

NOTE: Only override a single build arg for each build. Using multiple overrides may lead to a non-functioning image.


If you wish to build an image with a third-party adapter you can use the dbt-third-party target. This target requires you provide a path to the adapter that can be processed by pip by using the dbt_third_party build arg:

docker build --tag <your_image_name> \
  --target dbt-third-party \
  --build-arg dbt_third_party=<pip_parsable_install_string> \
  <path/to/dockerfile>

Examples:

To build an image named "my-dbt" that supports redshift using the latest releases:

cd dbt-core/docker
docker build --tag my-dbt  --target dbt-redshift .

To build an image named "my-other-dbt" that supports bigquery using dbt-core version 0.21.latest and the bigquery adapter version 1.0.0b1:

cd dbt-core/docker
docker build \
  --tag my-other-dbt  \
  --target dbt-bigquery \
  --build-arg [email protected] \
  --build-arg [email protected]  \
 .

To build an image named "my-third-party-dbt" that uses Materilize third party adapter and the latest release of dbt-core:

cd dbt-core/docker
docker build --tag my-third-party-dbt \
  --target dbt-third-party \
  --build-arg dbt_third_party=dbt-materialize \
  .

Special cases

There are a few special cases worth noting:

  • The dbt-spark database adapter comes in three different versions named PyHive, ODBC, and the default all. If you wish to overide this you can use the --build-arg flag with the value of dbt_spark_version=<version_name>. See the docs for more information.

  • The dbt-postgres database adapter is released as part of the dbt-core codebase. If you wish to overide the version used, make sure you use the gitref for dbt-core:

docker build --tag my_dbt \
  --target dbt-postgres \
  --build-arg [email protected] \
  <path/to/dockerfile> \
  • If you need to build against another architecture (linux/arm64 in this example) you can overide the build_for build arg:
docker build --tag my_dbt \
  --target dbt-postgres \
  --build-arg build_for=linux/arm64 \
  <path/to/dockerfile> \

Supported architectures can be found in the python docker dockerhub page.

Running an image in a container:

The ENTRYPOINT for this Dockerfile is the command dbt so you can bind-mount your project to /usr/app and use dbt as normal:

docker run \
--network=host
--mount type=bind,source=path/to/project,target=/usr/app \
--mount type=bind,source=path/to/profiles.yml,target=/root/.dbt/ \
my-dbt \
ls

Notes:

  • Bind-mount sources must be an absolute path
  • You may need to make adjustments to the docker networking setting depending on the specifics of your data warehouse/database host.