Databricks Data Engineer Professional Question 138
Select 3A data engineering team is tasked with building a Lakehouse-based pipeline that processes transactional data from a financial system. The source system frequently updates and deletes records, which must be accurately reflected in downstream analytics and machine learning models. Historically, the team faced challenges tracking these changes due to the lack of efficient mechanisms for propagating updates and deletes. How does Databricks Change Data Feed (CDF) address this issue?
- A
CDF provides a mechanism to capture and query only the changed rows (inserts, updates, and deletes) in a Delta Table.
- B
CDF requires full table scans to identify changes, ensuring no missed updates or deletes.
- C
CDF generates metadata that tracks row-level changes, allowing downstream systems to consume only incremental changes.
- D
CDF automatically ensures schema enforcement and evolution when changes propagate to downstream systems.
- E
CDF helps reduce data duplication and processing overhead by eliminating the need to reprocess the entire dataset after updates or deletes.
Show answer and explanation
Correct answers: A, C, E
Explanation
Change Data Feed (CDF) in Databricks simplifies the propagation of updates and deletes in Lakehouse architecture by capturing and exposing only the incremental changes (inserts, updates, and deletes) in a Delta Table. This eliminates the need for full table scans or reprocessing the entire dataset, reducing processing overhead and ensuring efficient, accurate downstream consumption of changes. Additionally, the CDF metadata tracks row-level changes, enabling precise and scalable pipelines for analytics and machine learning workflows.
- A. Correct.
Correct. CDF is designed to efficiently capture and expose only the changed rows (inserts, updates, and deletes), which simplifies propagating updates and deletes within data pipelines.
- B. Incorrect.
Incorrect. CDF does not require full table scans. It optimizes the process by maintaining metadata about changes, avoiding the need for expensive operations like full scans.
- C. Correct.
Correct. CDF tracks and provides row-level changes via metadata, allowing downstream consumers to process only the incremental changes.
- D. Incorrect.
Incorrect. While Delta Lake supports schema enforcement and evolution, this feature is separate from CDF and not directly related to propagating updates and deletes.
- E. Correct.
Correct. CDF eliminates the need to reprocess the entire dataset by exposing only the modified data, reducing data duplication and computational overhead.