PDE Maintaining and Automating Data Workloads Practice Question
You manage a BigQuery reservation with 500 baseline slots and autoscaling up to 2000 slots. Your team runs a mix of interactive queries and batch load jobs. During peak hours, you notice that interactive queries are throttled when autoscaling slots are consumed by long-running batch loads. How can you ensure interactive queries get priority access to slots?
⚠ Common exam trap
Google often tests the misconception that autoscaling alone or reducing baseline slots can solve priority issues, but the key is that without separate reservations and explicit priority assignments, all jobs compete equally for the same pool of slots.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Create a separate reservation for interactive queries with a higher priority assignment.
BigQuery reservations allow you to create separate reservations for different workloads (e.g., interactive queries vs. batch loads) and assign them different priority levels. By creating a dedicated reservation for interactive queries with a higher priority, you ensure that interactive queries get preferential access to slots, even when autoscaling slots are consumed by long-running batch jobs. This directly addresses the contention issue without reducing overall capacity.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Create a separate reservation for interactive queries with a higher priority assignment.
Why this is correct
Separate reservations isolate slot pools, so batch load jobs cannot consume the interactive reservation's baseline or autoscaled slots. Assigning interactive queries higher priority within their own reservation guarantees they are scheduled ahead of batch work.
- ✗
Reduce the baseline slots to 200 and rely solely on autoscaling.
Why it's wrong here
Lowering baseline removes the guaranteed capacity that interactive queries draw on first, so they compete with batch jobs for autoscaled slots. Baseline reservations exist precisely to guarantee minimum throughput; reducing it suits cost-cutting on predictable workloads, not prioritising latency-sensitive queries.
- ✗
Switch to on-demand pricing to eliminate slot contention.
Why it's wrong here
On-demand pricing removes reservations entirely, so interactive queries join a shared pool with no priority over batch jobs and lose the slot guarantees a reservation provides. On-demand suits sporadic, unpredictable workloads; here it discards the baseline capacity that could shield interactive queries.
- ✗
Set the autoscaling max to 1000 slots for batch jobs.
Why it's wrong here
Capping autoscaling limits total slots but does not allocate any portion to interactive queries, so batch loads still consume whatever slots exist. Maximum-slot limits control cost and runaway scaling; they suit budgets, whereas priority requires separate reservations or assignment of batch jobs to a lower-priority reservation.
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