1. Introduction:
This guide presents general best practices for leveraging virtual warehouses in Snowflake for efficient query processing. It refrains from absolute recommendations as optimal configurations depend on diverse factors, including:
- User/query concurrency
- Number of accessed tables
- Data size and structure
- Specific needs for availability, latency, and cost
Warehouse considerations for data loading are addressed in a separate topic (see sidebar).
2. Key Principles:
Experimentation: Execute diverse queries on various warehouse sizes to identify your ideal setups for specific workloads.
Size Flexibility: Prioritize efficient resource utilization over constant warehouse sizing. Snowflake's per-second billing allows suspending larger warehouses (Large, X-Large, etc.) during inactivity, minimizing cost.
3. Conclusion:
By implementing these principles, you can optimize warehouse usage and achieve cost-effective, high-performance query processing in Snowflake.
Note: These guidelines encompass both standard single-cluster warehouses and the advanced multi-cluster warehouses offered in Snowflake Enterprise edition.
