Chapter 6: Performance and Cost Optimization
Snowflake has built-in capabilities to optimize queries and performance through various out-of-the-box features, such as caching, auto-scaling, and automatically clustering tables. However, there is always an opportunity to positively influence performance by tweaking table structures, introducing physicalization techniques, and optimizing your compute to the maximum. In this chapter, we will explore some of the techniques that can be used to make a Snowflake-based data warehouse run more efficiently and, therefore, at a lower cost. The chapter also explores optimization strategies for reducing unnecessary storage costs.
The following recipes are included in this chapter:
- Examining table schemas and deriving an optimal structure for a table
- Identifying query plans and bottlenecks
- Weeding out inefficient queries through analysis
- Identifying and reducing unnecessary Fail-safe and Time Travel storage usage
- Projections...
