You are running your BigQuery project in the on-demand billing model and are executing a change data capture (CDC) process that ingests data. The CDC process loads 1 GB of data every 10 minutes into a

Question

Options

• ACreate a BigQuery reservation for the dataset.
• BCreate a BigQuery reservation for the job.
• CCreate a BigQuery reservation for the service account running the job.
• DCreate a BigQuery reservation for the project.

• A
  3% (1)
• B
  76% (29)
• C
  8% (3)
• D
  13% (5)

Explanation

Option B is correct because BigQuery allows you to assign a reservation directly to a specific job by specifying the reservation_id in the job's configuration. This lets you apply committed-slot capacity (predictable pricing) exclusively to the scan-intensive CDC merge job, while the rest of your project continues running on on-demand billing - giving you surgical cost control exactly where you need it.

Why the distractors are wrong:

• A (dataset): Datasets are not a valid reservation assignment target in BigQuery. Reservations attach to compute resources, not storage constructs.
• C (service account): BigQuery does not route reservation assignments by service account identity; this concept doesn't exist in the reservation model.
• D (project): While project-level reservation assignment is valid, it applies committed slots to all jobs in the project - not just the CDC process - which over-provisions and defeats the goal of targeted cost control.

Memory tip: Think of BigQuery reservation assignments as a targeting hierarchy: Org → Folder → Project → Job. Each level is more specific than the last. When you need to isolate cost for a single workload (like one CDC pipeline), go to the most specific valid target - the job - rather than blanketing the whole project.

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