Cowthulhu
02/23/2024, 6:10 PMScout
02/23/2024, 6:10 PMdagster-dbt
library installed in your environment. This library provides the necessary integrations to work with dbt in Dagster.
2. Define Your dbt Project: Ensure that your dbt project is set up correctly with the models you want to transform. Your dbt project should include your SQL transformation as a model.
3. Create a Dagster Asset: Use the @dbt_assets
decorator to create Dagster assets from your dbt project. You will need to provide the path to your dbt project's manifest file, which is generated by running dbt compile
or dbt run
.
Here is an example of how you might define a dbt asset in Dagster:
python
from dagster_dbt import dbt_assets
# Assuming you have a manifest.json file in your dbt project directory
dbt_manifest_path = "/path/to/your/dbt/project/manifest.json"
@dbt_assets(manifest=dbt_manifest_path)
def my_dbt_assets(context, dbt):
yield from dbt.cli(["run"], context=context).stream()
4. Materialize the Asset: Once you have defined your dbt asset, you can materialize it using Dagster's tooling. This can be done through the Dagster UI or by invoking the asset within a Dagster job.
By following these steps, you can integrate your dbt transform into Dagster as an asset. This approach is beneficial because it allows you to manage your dbt models within the broader context of your Dagster data pipelines, providing you with a unified view of your data workflows and dependencies. Using Dagster with dbt, part 4: Add a do... button Using Dagster with dbt, part 3: Define a... button SqlTypeHandler - Proposing an additional... button Using Dagster with Fivetran button Thank you for your feedback!