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When configuring your unit test, you can override the output of macros, project variables, or environment variables for a given unit test.
models/schema.yml
- name: test_my_model_overrides
model: my_model
given:
- input: ref('my_model_a')
rows:
- {id: 1, a: 1}
- input: ref('my_model_b')
rows:
- {id: 1, b: 2}
- {id: 2, b: 2}
overrides:
macros:
type_numeric: override
invocation_id: 123
vars:
my_test: var_override
env_vars:
MY_TEST: env_var_override
expect:
rows:
- {macro_call: override, var_call: var_override, env_var_call: env_var_override, invocation_id: 123}You can override the output of any macro in your unit test defition.
If the model you're unit testing uses these macros, you must override them:
is_incremental: If you're unit testing an incremental model, you must explicity set is_incremental to true or false.models/schema.yml
unit_tests:
- name: my_unit_test
model: my_incremental_model
overrides:
macros:
# unit test this model in "full refresh" mode
is_incremental: false
...dbt_utils.star: If you're unit testing a model that uses the star macro, you must explicity set star to a list of columns. This is because the star only accepts a relation for the from argument; the unit test mock input data is injected directly into the model SQL, replacing the ref() or source() function, causing the star macro to fail unless overidden.models/schema.yml
unit_tests:
- name: my_other_unit_test
model: my_model_that_uses_star
overrides:
macros:
# explicity set star to relevant list of columns
dbt_utils.star: col_a,col_b,col_c
...evals
skills
adding-dbt-unit-test
references
answering-natural-language-questions-with-dbt
building-dbt-semantic-layer
configuring-dbt-mcp-server
fetching-dbt-docs
scripts
migrating-dbt-core-to-fusion
running-dbt-commands
troubleshooting-dbt-job-errors
using-dbt-for-analytics-engineering