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When configuring your unit test, you can override the output of macros, vars, or environment variables. This enables you to unit test your incremental models in "full refresh" and "incremental" modes.
Incremental models need to exist in the database first before running unit tests. Use the --empty flag to build an empty version of the models to save warehouse spend. You can also optionally select only your incremental models using the --select flag.
dbt run --select "config.materialized:incremental" --emptyAfter running the command, you can then perform a regular dbt build for that model and then run your unit test.
When testing an incremental model, the expected output is the result of the materialization (what will be merged/inserted), not the resulting model itself (what the final table will look like after the merge/insert).
For example, say you have an incremental model in your project:
my_incremental_model.sql
{{
config(
materialized='incremental'
)
}}
select * from {{ ref('events') }}
{% if is_incremental() %}
where event_time > (select max(event_time) from {{ this }})
{% endif %}You can define unit tests on my_incremental_model to ensure your incremental logic is working as expected:
unit_tests:
- name: my_incremental_model_full_refresh_mode
model: my_incremental_model
overrides:
macros:
# unit test this model in "full refresh" mode
is_incremental: false
given:
- input: ref('events')
rows:
- {event_id: 1, event_time: 2020-01-01}
expect:
rows:
- {event_id: 1, event_time: 2020-01-01}
- name: my_incremental_model_incremental_mode
model: my_incremental_model
overrides:
macros:
# unit test this model in "incremental" mode
is_incremental: true
given:
- input: ref('events')
rows:
- {event_id: 1, event_time: 2020-01-01}
- {event_id: 2, event_time: 2020-01-02}
- {event_id: 3, event_time: 2020-01-03}
- input: this
# contents of current my_incremental_model
rows:
- {event_id: 1, event_time: 2020-01-01}
expect:
# what will be inserted/merged into my_incremental_model
rows:
- {event_id: 2, event_time: 2020-01-02}
- {event_id: 3, event_time: 2020-01-03}There is currently no way to unit test whether the dbt framework inserted/merged the records into your existing model correctly, but we're investigating support for this in the future in GitHub issue #8664.
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