GCP Professional Data Engineer Practice Question

Your analytics team normally runs cost-sensitive, exploratory queries using BigQuery's on-demand model. On the first business day of each month, finance must execute a close-of-month query that consistently consumes about 300 slots for roughly 40 minutes and must finish within the hour. You must guarantee that capacity while keeping overall monthly spend as low as possible. Which BigQuery capacity-pricing approach best meets these requirements?

Provision 300 flex slots only for the monthly job and keep other queries on the on-demand model.
Purchase a 300-slot one-year commitment in Standard Edition and run all queries on the reservation.
Move the project to Enterprise Edition capacity pricing with a permanent 300-slot baseline that auto-scales as needed.
Continue using on-demand pricing but submit the monthly job with batch priority to avoid concurrency limits.

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Answer Description

Buying long-term committed capacity for a workload that runs only 40 minutes per month would leave the slots idle for the rest of the period and be far more expensive than paying for capacity only when needed. Flex slots have a 60-second minimum and are billed per second thereafter, so provisioning 300 flex slots for the 40-minute window costs about 200 slot-hours (≈US$8) each month while still guaranteeing dedicated capacity. After the job finishes, you can script deletion or use a scheduled reservation end time so no further charges accrue. Continuing with on-demand alone risks longer runtimes during periods of high demand, and moving the whole project to a permanent 300-slot baseline would add unnecessary fixed cost. Submitting the job with batch priority affects scheduling but provides no completion-time guarantee.

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