Databricks Data Engineer Professional Question 256
Select 3You are tasked with deploying a data pipeline in a Databricks environment. To ensure a smooth deployment, your team decides to implement automated testing as part of the CI/CD process. Which of the following are best practices to follow for testing and deploying your Databricks pipeline?
- A
Write unit tests for your pipeline using a framework like pytest to validate the logic of individual transformations.
- B
Manually test your pipeline in the production environment before deployment to ensure it works as expected.
- C
Use a staging environment to test the pipeline with production-like data before deploying it to production.
- D
Set up a jobs cluster specifically for running automated tests to isolate testing environments.
- E
Deploy directly to production after confirming the pipeline works in your development environment.
Show answer and explanation
Correct answers: A, C, D
Explanation
Testing and deploying a Databricks pipeline requires a structured approach to avoid introducing errors into production. Best practices include writing unit tests to validate individual transformations, using a staging environment for testing with production-like data, and setting up dedicated infrastructure for automated testing to ensure isolation. These steps help ensure a smooth deployment process and minimize risks.
- A. Correct.
Writing unit tests for individual transformations ensures that the logic of each step in the pipeline is correct and can catch errors early in the development process.
- B. Incorrect.
Manually testing in the production environment is not a best practice because it risks introducing issues directly into production, which can affect end users.
- C. Correct.
Testing in a staging environment with production-like data minimizes the risk of issues when deploying to production, as it simulates real-world scenarios.
- D. Correct.
Using a dedicated jobs cluster for automated tests ensures that the testing environment is isolated, preventing interference with other workloads and ensuring consistent test results.
- E. Incorrect.
Deploying directly to production without proper testing in staging or running automated tests is risky and not recommended, as it can lead to undetected issues affecting the production environment.