Databricks Data Engineer Associate Question 421
Select 3You are designing a production pipeline in Databricks to process large volumes of streaming data from IoT sensors. The pipeline must ensure data integrity, fault-tolerance, and scalability. Which of the following steps should be included in your pipeline design to meet these requirements?
- A
Use Delta Lake for streaming data storage and enable schema enforcement.
- B
Configure checkpointing for the streaming query to maintain fault-tolerance during failures.
- C
Avoid using partitioning in your data storage to simplify the data model.
- D
Leverage Auto Scaling clusters to handle variable streaming data loads.
- E
Disable write-ahead logs (WAL) to improve write performance.
Show answer and explanation
Correct answers: A, B, D
Explanation
To design a robust production pipeline for streaming data, you must ensure data integrity, fault-tolerance, and scalability. Using Delta Lake with schema enforcement, enabling checkpointing, and leveraging Auto Scaling clusters are key steps for meeting these requirements. Avoid practices like disabling WAL or skipping partitioning as they can negatively impact fault-tolerance and scalability.
- A. Correct.
Using Delta Lake with schema enforcement ensures data integrity by preventing schema mismatches during streaming ingestion. This is a best practice for production pipelines.
- B. Correct.
Checkpointing is essential for fault-tolerance in streaming applications as it allows the pipeline to recover from failures without data loss.
- C. Incorrect.
Avoiding partitioning may lead to significant performance issues in large-scale data processing. Partitioning is crucial for scalability and efficient querying in production pipelines.
- D. Correct.
Auto Scaling clusters dynamically adjust resources based on workload, ensuring scalability for pipelines handling variable streaming data loads.
- E. Incorrect.
Disabling write-ahead logs (WAL) compromises fault-tolerance as WAL ensures data durability in case of system failures. This is not recommended in production pipelines.