Databricks Data Engineer Associate Question 31
Single answerA data engineering team is setting up a Databricks cluster for an upcoming project. They want to ensure compatibility with specific libraries and features by selecting the correct version of the Databricks Runtime. How can the team identify the versioning scheme used by Databricks Runtime?
- A
Databricks Runtime versions are based on the release year and month (e.g., 2023.10).
- B
Databricks Runtime versions are represented as major and minor versions (e.g., 12.2).
- C
Databricks Runtime versions use semantic versioning (e.g., 2.1.0).
- D
Databricks Runtime versions are assigned unique alphanumeric identifiers (e.g., v12A).
Show answer and explanation
Correct answer: B
Explanation
Databricks Runtime versions are represented using a major.minor format (e.g., 12.2), where the major number indicates major functional updates or breaking changes, and the minor number indicates incremental updates or enhancements. This versioning scheme helps users select the appropriate runtime for compatibility with specific features or libraries.
- A. Incorrect.
Incorrect. Databricks Runtime does not use release year and month in its versioning scheme. This is not how the versions are represented.
- B. Correct.
Correct. Databricks Runtime versions are based on major and minor version numbers (e.g., 12.2), where the major version indicates significant changes and the minor version indicates incremental updates.
- C. Incorrect.
Incorrect. While semantic versioning (major.minor.patch) is common in software development, Databricks Runtime does not use this scheme.
- D. Incorrect.
Incorrect. Databricks Runtime does not use alphanumeric identifiers for versioning.