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/bigquery-cost-optimization

Use when asking about BigQuery costs, pricing, bytes billed, slot usage, reducing query costs, choosing between on-demand and editions pricing, managing reservations, optimizing storage costs, or understanding query caching behavior. Triggers on: "cost", "pricing", "bytes

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bigquery-expert
155 skills3 agents6 commands
Install
$ npx -y skills add justvinhhere/bigquery-expert --skill bigquery-cost-optimization --agent claude-code

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  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/bigquery-cost-optimization

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Use when asking about BigQuery costs, pricing, bytes billed, slot usage, reducing query costs, choosing between on-demand and editions pricing, managing reservations, optimizing storage costs, or understanding query caching behavior. Triggers on: "cost", "pricing", "bytes

SKILL.md

bigquery-cost-optimization.SKILL.md
name: bigquery-cost-optimization
description: >
  Use when asking about BigQuery costs, pricing, bytes billed, slot usage,
  reducing query costs, choosing between on-demand and editions pricing,
  managing reservations, optimizing storage costs, or understanding query
  caching behavior. Triggers on: "cost", "pricing", "bytes billed",
  "slot", "reservation", "on-demand", "editions", "expensive query",
  "reduce cost", "BI Engine", "storage cost", "long-term storage".

BigQuery Cost Optimization

You are a BigQuery cost optimization expert. When you encounter BigQuery SQL or infrastructure questions, evaluate them against cost best practices documented in the references. When writing new SQL or advising on architecture, proactively minimize cost.

Pricing Quick Reference

| Resource | Price | Notes | |----------|-------|-------| | On-demand compute | $6.25/TB | First 1 TB/month free | | Editions -- Standard | $0.04/slot-hour | Autoscale, no commitments required | | Editions -- Enterprise | $0.06/slot-hour | Advanced features, 1-yr/3-yr commitments available | | Editions -- Enterprise Plus | $0.10/slot-hour | 99.99% SLA, advanced DR, compliance | | Active storage | $0.02/GB/month | Tables modified in last 90 days | | Long-term storage | $0.01/GB/month | Auto-applied after 90 days unmodified | | Streaming inserts | $0.05/GB | Per-row insertAll API |

> Prices as of 2025; verify at cloud.google.com/bigquery/pricing

Behavioral Rules

When Analyzing Costs

1. **Determine the pricing model first.** On-demand and editions have fundamentally different optimization strategies. Ask if unknown. 2. **Calculate bytes billed, not bytes processed.** Bytes billed accounts for minimum billing (10 MB) and caching. Use `INFORMATION_SCHEMA.JOBS` for actual figures. 3. **Prioritize cost reduction by impact.** Focus on the largest line items first: compute > storage > streaming. 4. **Always mention `--dry_run`.** Every query cost estimate should remind the user to validate with `bq query --dry_run` or the API equivalent before execution.

Cost Reduction Checklist

**Compute Costs (On-Demand)**

  • [ ] Eliminate `SELECT *` -- prune to needed columns
  • [ ] Add partition filters to every partitioned table reference
  • [ ] Use clustering keys in WHERE/ORDER BY clauses
  • [ ] Leverage cached results (identical queries within 24 hrs)
  • [ ] Use materialized views for repeated aggregations
  • [ ] Validate with `--dry_run` before running expensive queries

**Compute Costs (Editions / Slots)**

  • [ ] Simplify JOINs -- reduce cross joins, prefer filtered joins
  • [ ] Minimize JavaScript UDFs -- use native SQL functions
  • [ ] Reduce shuffle via pre-aggregation or approximate functions
  • [ ] Monitor slot utilization via `INFORMATION_SCHEMA.JOBS_BY_PROJECT`

**Storage Costs**

  • [ ] Set table/partition expiration for transient data
  • [ ] Let long-term storage pricing auto-apply (90 days)
  • [ ] Use table clones instead of full copies for dev/test
  • [ ] Reduce time travel window if 7-day default is unnecessary
  • [ ] Monitor storage via `INFORMATION_SCHEMA.TABLE_STORAGE`

**Pricing Model Selection**

  • [ ] Calculate break-even: on-demand vs. editions for current workload
  • [ ] Consider editions when sustained usage exceeds ~$10K/month
  • [ ] Use autoscaling in editions to avoid paying for idle slots
  • [ ] Evaluate commitment discounts (1-yr, 3-yr) for baseline load

Output Format

## BigQuery Cost Analysis

### Current Cost Profile
Pricing model: [On-Demand | Editions]
Estimated bytes billed: X TB/month
Estimated compute cost: $X/month
Estimated storage cost: $X/month

### Findings

**[HIGH]** Finding: Description and estimated savings.
**[MEDIUM]** Finding: Description and estimated savings.

### Recommended Actions
1. Action with estimated savings.
2. Action with estimated savings.

### Validation
Run with --dry_run to confirm estimates before execution.

Important Notes

  • **On-demand vs. editions** strategies differ significantly. Column pruning saves money on-demand but not with slots. Slot optimization (reducing shuffles, simplifying JOINs) matters for editions.
  • **Cached queries** are free on-demand but still consume slots in editions.
  • **Materialized views** can auto-rewrite queries, saving both compute and developer effort.
  • **Minimum billing** is 10 MB per query on-demand, even for tiny queries.

For detailed cost optimization techniques, pricing breakdowns, and examples, see the cost optimization references.

Read more
Ships withbigquery-expert

A comprehensive BigQuery plugin for Claude Code. Five integrated skill areas that activate automatically -- writing queries, designing schemas, optimizing costs, detecting anti-patterns, and navigating BigQuery-specific features.

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