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Answer: Increase the slot capacity of the project with baseline as 0 and maximum reservation size as 3000.
Increasing the slot capacity of the project with the baseline set to 0 and a maximum reservation size of 3000 directly addresses the concurrency issue by providing more capacity for simultaneous queries. Since the current peak usage is 1500 queries, this increase ensures sufficient headroom. Additionally, setting the baseline to 0 means you only pay for the slots actually used, optimizing costs by avoiding unnecessary expenses for idle capacity. This approach is ideal for non-time-sensitive workloads where flexibility is more crucial than guaranteed instant availability.
Author: LeetQuiz Editorial Team
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The data analyst team at your company utilizes BigQuery for both ad-hoc queries and scheduled SQL pipelines within a Google Cloud project that has a slot reservation of 2000 slots. Recently, the team has introduced hundreds of new, non time-sensitive SQL pipelines, leading to frequent quota errors. Upon examining the logs, you observe that around 1500 queries are being triggered simultaneously during peak times. You need to address the issue of query concurrency. What should you do?
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.
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