An enterprise data platform team manages workloads on BigQuery Enterprise edition in the us-central1 region across two separate reservations: batch_etl: Configured with a baseline of 600 slots, a maximum reservation size of 1,200 slots (allowing up to 600 autoscale slots), and idle slot sharing enabled (ignore_idle_slots = false). reporting_bi: Configured with a baseline of 400 slots, a maximum reservation size of 800 slots (allowing up to 400 autoscale slots), and idle slot sharing enabled (ignore_idle_slots = false). At 03:00 UTC, the reporting_bi reservation is completely idle with 0 active jobs. An unpredicted ETL job begins running in the batch_etl reservation, requiring 1,100 compute slots to process concurrently. In what order will BigQuery allocate compute capacity to satisfy the 1,100 slot demand, and how will this compute capacity be billed?

BigQuery first allocates the 600 baseline slots from `batch_etl`, then borrows 400 idle baseline slots from `reporting_bi`, and finally autoscales 100 slots; charges include the baseline rates for both reservations plus the autoscaling rate for the 100 scaled slots.: ### What BigQuery Reservation Priority and Autoscaling Is BigQuery Editions use a hierarchical slot provisioning mechanism that optimizes performance and cost efficiency across multi-tenant reservation architectures. When jobs demand more compute capacity than a single reservation's baseline, BigQuery allocates capacity according to a strict priority hierarchy: **Baseline slots**, followed by **Idle slot sharing** from sibling reservations in the same region and edition, and finally **Autoscaling slots** up to the reservation's configured maximum size. ### How It Meets the Requirements 1. **Step 1 (Own Baseline Allocation)**: BigQuery immediately utilizes all **600 baseline slots** configured in the `batch_etl` reservation. 2. **Step 2 (Idle Slot Sharing)**: Because `ignore_idle_slots` is set to `false` on both reservations within the same edition and region (`us-central1`), `batch_etl` borrows the **400 idle baseline slots** from the inactive `reporting_bi` reservation before spinning up autoscaling slots. This brings total available capacity to 1,000 slots. 3. **Step 3 (Autoscaling Activation)**: To meet the remaining 100 slot requirement (1,100 total needed - 1,000 available), BigQuery dynamically provisions **100 autoscale slots** in `batch_etl`. 4. **Billing Calculation**: The customer is billed for the fixed **600 baseline slots** (`batch_etl`) and **400 baseline slots** (`reporting_bi`) at standard baseline/commitment rates, plus the hourly **autoscaling rate** specifically for the 100 upscaled slots for the duration of the scaling event. ### Key Advantages * **Cost Optimization**: Prioritizing idle baseline borrowing avoids unnecessary autoscale compute costs when existing paid baseline capacity is sitting idle. * **Fast Provisioning**: Baseline and borrowed idle slots are immediately available without cold-start provisioning latency. * **Controlled Scale**: Autoscaling seamlessly covers remaining bursts up to the maximum reservation boundary. * **Fair-Share Return**: If jobs arrive in `reporting_bi`, borrowed idle slots are preemptively returned, prompting `batch_etl` to autoscale further if needed. ### Why This Is Optimal This allocation sequence minimizes operational expenditure by exhausting already-purchased baseline capacity across the organization before invoking dynamic autoscaling pricing.

Bigquery Reservation Autoscaling Idle Slot Priority | professional-cloud-data-engineer

Bigquery Reservation Autoscaling Idle Slot Priority

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An enterprise data platform team manages workloads on BigQuery Enterprise edition in the us-central1 region across two separate reservations:

batch_etl: Configured with a baseline of 600 slots, a maximum reservation size of 1,200 slots (allowing up to 600 autoscale slots), and idle slot sharing enabled (ignore_idle_slots = false).
reporting_bi: Configured with a baseline of 400 slots, a maximum reservation size of 800 slots (allowing up to 400 autoscale slots), and idle slot sharing enabled (ignore_idle_slots = false).

At 03:00 UTC, the reporting_bi reservation is completely idle with 0 active jobs. An unpredicted ETL job begins running in the batch_etl reservation, requiring 1,100 compute slots to process concurrently.

In what order will BigQuery allocate compute capacity to satisfy the 1,100 slot demand, and how will this compute capacity be billed?

BigQuery first allocates the 600 baseline slots from batch_etl, then borrows 400 idle baseline slots from reporting_bi, and finally autoscales 100 slots; charges include the baseline rates for both reservations plus the autoscaling rate for the 100 scaled slots.

BigQuery autoscales batch_etl up to its maximum ceiling of 1,200 slots before attempting any idle slot sharing; charges include baseline rates plus 600 autoscale slots.

BigQuery first borrows 400 idle slots from reporting_bi, then uses the 600 baseline slots from batch_etl, and autoscales 100 slots; charges include baseline rates for both reservations and on-demand per-TB pricing for the overflow.

BigQuery first allocates the 600 baseline slots from batch_etl, immediately autoscales 500 slots to reach the 1,100 slot demand, and leaves reporting_bi untouched; charges include baseline rates for both reservations plus the autoscaling rate for 500 slots.

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Bigquery Reservation Autoscaling Idle Slot Priority

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