Databricks Data Engineer Associate Question 32
Single answerYou are tasked with configuring a Databricks cluster to ensure compatibility with a specific library that requires Python 3.9. While setting up the cluster, you notice various Databricks Runtime versions listed. Which of the following statements accurately describes how Databricks Runtime versions are structured?
- A
Databricks Runtime versions follow a semantic versioning format: Major.Minor.Patch.
- B
Databricks Runtime versions indicate the Apache Spark version being used.
- C
Databricks Runtime versions only specify the Python version installed.
- D
Databricks Runtime versions are updated weekly and do not reflect specific dependencies.
Show answer and explanation
Correct answer: A
Explanation
Databricks Runtime versions follow a semantic versioning format: Major.Minor.Patch. This structure helps users understand the scope of changes in the runtime, such as major updates (e.g., breaking changes), minor updates (e.g., new features), or patches (e.g., bug fixes). By understanding this, data engineers can choose a runtime version that ensures compatibility with specific libraries, Python versions, or Apache Spark versions.
- A. Correct.
Correct: Databricks Runtime versions follow a semantic versioning format (Major.Minor.Patch). This helps users identify changes such as major updates, minor feature additions, or bug fixes.
- B. Incorrect.
Partially correct but misleading: While the Databricks Runtime version may indicate the Spark version, the runtime includes other components such as Python and libraries, making this statement incomplete.
- C. Incorrect.
Incorrect: Databricks Runtime versions do not solely specify the Python version. They also include Spark and additional libraries.
- D. Incorrect.
Incorrect: Databricks Runtime versions are not updated weekly; they follow a structured release schedule and reflect specific dependencies and updates.