dbt-testing

To write unit tests for dbt models, create a YAML file next to your model using a top-level unit_tests key with given and expect blocks to validate transformation logic and verify expected outputs.

dbt unit tests validate transformation logic and edge-case handling using input refs and expected outputs, whereas schema tests validate data properties and constraints without checking the model's internal processing logic.

You test edge cases in dbt transformations by defining specific input conditions and failure modes within the given block of your unit_tests YAML and asserting the expected output in the expect block.

The unit_tests YAML file should be placed next to the dbt model it validates, using a top-level unit_tests key rather than nesting the configuration inside the models directory block.

Yes, you can validate dbt model logic without rewriting SQL by using a non-invasive unit_tests YAML workflow that mocks inputs in the given block and checks results in the expect block.

You verify multiple inputs in a dbt unit test by defining multiple input refs within the given block of the unit_tests YAML structure and asserting their combined transformation output in the expect block.