A team's bundle defines a Lakeflow Spark Declarative Pipeline (formerly DLT) with one notebook library at the root, and the prod target overrides the `libraries` list: ```yaml bundle: name: etl_bundle resources: pipelines: sales_silver: name: sales_silver libraries: - notebook: path: ./src/dlt_silver.ipynb targets: prod: resources: pipelines: sales_silver: libraries: - notebook: path: ./prod/dlt_silver.ipynb ``` After running `databricks bundle deploy -t prod`, which notebook does the deployed pipeline use?

1. A. Both ./src/dlt_silver.ipynb and ./prod/dlt_silver.ipynb, because target-level lists are merged with root-level lists 💬 A
2. B. Only ./prod/dlt_silver.ipynb, because sequence (list) settings in a target replace the root-level list instead of merging with it ✓ B
3. C. Only ./src/dlt_silver.ipynb, because root-level resource definitions always take precedence over target overrides of any resource setting 💬 C
4. D. The deploy fails with a duplicate-resource error because sales_silver is defined in two places 💬 D

Reveal answer

Correct answer: Only ./prod/dlt_silver.ipynb, because sequence (list) settings in a target replace the root-level list instead of merging with it

Reference: https://docs.databricks.com/aws/en/dev-tools/bundles/overrides