Google Cloud Professional Data Engineer — Question 172

The data analyst team at your company uses BigQuery for ad-hoc queries and scheduled SQL pipelines in a Google Cloud project with a slot reservation of 2000 slots. However, with the recent introduction of hundreds of new non time-sensitive SQL pipelines, the team is encountering frequent quota errors. You examine the logs and notice that approximately 1500 queries are being triggered concurrently during peak time. You need to resolve the concurrency issue. What should you do?

Answer options

• A. Increase the slot capacity of the project with baseline as 0 and maximum reservation size as 3000.
• B. Update SQL pipelines to run as a batch query, and run ad-hoc queries as interactive query jobs.
• C. Increase the slot capacity of the project with baseline as 2000 and maximum reservation size as 3000.
• D. Update SQL pipelines and ad-hoc queries to run as interactive query jobs.

Correct answer: B

Explanation

The correct option is B because running SQL pipelines as batch queries will help to manage the load more effectively, reducing the number of concurrent queries during peak times. Options A and C do not address the concurrency issue effectively since simply increasing slot capacity may not resolve the underlying problem of too many concurrent jobs. Option D would not differentiate the job types and could lead to further congestion in query execution.