8 Optimizing query performance
This chapter covers
- Getting data from the Snowflake Marketplace
- Performing analysis of geographical data
- Viewing query performance using the query profile
- Understanding Snowflake micro-partitions
- Optimizing storage with clustering
- Improving query performance with search optimization
- General tips for improving query performance
Data engineers must ensure that their data pipelines perform well, especially when dealing with large amounts of data. They should write efficient SQL queries and be familiar with Snowflake optimization techniques to meet user performance requirements.
In this chapter, we will write queries using large amounts of data from the Snowflake Marketplace. We will use Snowflake’s query profile tool to understand the mechanics of query execution. We will learn about Snowflake’s units of storage, known as micro-partitions. We will apply clustering to underlying tables to improve query performance and identify queries that benefit from this type of optimization. We will also look at search optimization and describe the types of queries that benefit. Finally, we will learn how to identify queries that are candidates for optimization and share tips on improving query performance.