Question 1

Explanation

Option B is CORRECT. BigQuery cost controls allow setting daily query usage limits at the project level to prevent budget overruns. These controls cap the amount of data that can be processed by on-demand queries each day, automatically disabling new queries when the limit is reached. This feature provides a direct mechanism to enforce budget constraints, protect against unexpected costs from runaway queries, and ensure predictable BigQuery expenses.

Option A is INCORRECT. While Google Cloud supports custom quotas for some services, BigQuery specifically uses cost controls rather than custom quotas to manage query spending. Custom quotas typically apply to API request limits rather than query data processing volumes.

Option C is INCORRECT. Custom IAM roles control permissions and access to resources but don't directly limit query costs or data processing volumes. While you could restrict who can run queries, this doesn't prevent authorized users from running expensive queries that exceed budget expectations.

Option D is INCORRECT. Query caching can reduce costs by returning cached results for identical queries at no charge, but it doesn't enforce budget limits. Caching only helps when running exact duplicate queries within the cache lifetime and doesn't protect against new or modified queries that could still exceed budget constraints.