Databricks Data Engineer Professional Question 133
Select 3A data engineering team is working on a Lakehouse architecture to manage a large dataset stored in Delta tables. They need to efficiently propagate updates and deletes downstream to analytical systems and data consumers without reprocessing the entire dataset. How does Databricks Change Data Feed (CDF) address this challenge?
- A
CDF provides a way to track row-level changes (inserts, updates, and deletes) in Delta tables.
- B
CDF automatically compacts small files into larger files, improving query performance.
- C
CDF eliminates the need for full table scans by providing access to only the changed data since a specified timestamp or version.
- D
CDF uses snapshots to capture the entire state of a Delta table at a specific point in time.
- E
CDF ensures that downstream consumers can process only the incremental changes instead of reprocessing the entire dataset.
Show answer and explanation
Correct answers: A, C, E
Explanation
Change Data Feed (CDF) in Delta Lake is designed to address the challenges of propagating updates and deletes in Lakehouse architectures by enabling incremental data processing. This eliminates the need for expensive full table scans and reprocessing of the entire dataset. CDF tracks row-level changes, provides access to modified data since a specified point in time, and ensures efficient consumption of incremental changes by downstream systems, making it an essential feature for modern data engineering workflows.
- A. Correct.
Correct - CDF enables tracking of row-level changes, which is key for identifying inserts, updates, and deletes within Delta tables.
- B. Incorrect.
Incorrect - While Delta Lake supports file compaction, this feature is unrelated to CDF. CDF focuses on tracking data changes, not file optimization.
- C. Correct.
Correct - CDF allows access to only the changed data since a specified timestamp or version, avoiding unnecessary full table scans.
- D. Incorrect.
Incorrect - While Delta Lake supports snapshots for capturing table states, this is not a feature of CDF. CDF is designed for tracking incremental changes.
- E. Correct.
Correct - CDF ensures efficient propagation of updates and deletes by allowing downstream systems to process only incremental changes.