⏰ Run dbt models in Mage in under a minute.
docker compose
based.
dev.env
to .env
and run docker compose up
to start Mage and a Postgres database.
A simple dbt pipeline
simple_dbt_python_pipeline
by double-clicking the row from the list of pipelines this will take you directly to the editor. You can also single click,
then select the “code” icon from the side nav.Scroll to the bottom-most cell and click Execute with all upstream blocks.public.analytics.cur_customers
.customer_id | first_name | last_name | letters_first_name | is_alliterative |
---|---|---|---|---|
1 | Michael | P. | 7 | false |
2 | Shawn | M. | 5 | false |
3 | Kathleen | P. | 8 | false |
4 | Jimmy | C. | 5 | false |
5 | Katherine | R. | 9 | false |
6 | Sarah | R. | 5 | false |
7 | Martin | M. | 6 | true |
8 | Frank | R. | 5 | false |
9 | Jennifer | F. | 8 | false |
10 | Henry | W. | 5 | false |
Execute dbt from an external repo
dynamic_dbt_pipeline
by double-clicking the row from the list of pipelines— this will take you directly to the editor. You can also single click, then select the “code” icon from the side nav.Scroll to the bottom-most cell and click Execute and run all upstream blocks.profiles.yaml
file that interpolated environment variables from your instancedbt build
to write data to your local postgres database.dbt build
, which will: run models, test tests, snapshot snapshots, and seed seeds. 🥳To see the output, you can use a querying tool (like DataGrip or psql) to the locally hosted Postgres database. To learn more about the Jaffle Shop demo, check out the repo.