Google Professional Data Engineer Question 262
Single answerGoogle Cloud PlatformYou are managing a BigQuery project where multiple teams run queries on shared datasets. One team has reported that their critical workloads are being delayed due to resource contention caused by non-critical ad hoc queries from another team. How can you ensure that the critical workloads from the affected team are prioritized while maintaining resource allocation fairness?
- A
Create a separate BigQuery project for the critical team and migrate their datasets there.
- B
Set up BigQuery Reservations and allocate a dedicated slot pool for the critical team.
- C
Use the BigQuery Query Scheduler to assign higher priority to the critical team's queries.
- D
Enable BigQuery flat-rate pricing to ensure all teams have equal access to resources.
Show answer and explanation
Correct answer: B
Explanation
BigQuery Reservations is the correct approach to solve resource contention issues. By allocating a dedicated slot pool to the critical team, you ensure their critical workloads have guaranteed compute capacity without interference from other teams' queries. This solution maintains fairness and prevents delays for high-priority workloads.
- A. Incorrect.
Creating a separate BigQuery project would isolate the datasets but does not directly address resource contention or prioritize workloads. It also adds complexity in managing multiple projects.
- B. Correct.
Setting up BigQuery Reservations allows you to allocate a dedicated slot pool for the critical team, ensuring their queries are prioritized and preventing delays caused by resource contention.
- C. Incorrect.
BigQuery Query Scheduler does not exist. This option is invalid.
- D. Incorrect.
Enabling BigQuery flat-rate pricing changes the billing model but does not solve the issue of resource contention or workload prioritization.