Advanced SQL

Chapter 2. Advanced SQL Techniques

In Chapter 1, we explored SQL’s evolution and modern breadth across traditional databases and cloud data platforms. We saw how SQL has grown far beyond simple SELECT statements into a rich ecosystem of analytical capabilities. Chapter 2 builds on that foundation by diving into advanced SQL query techniques and practical performance optimization strategies. We will discuss several SQL features like recursive common table expressions (CTEs) and window functions that enable complex data manipulations within SQL. We’ll then explore techniques to refactor and optimize queries for better performance. These include indexing in PostgreSQL, understanding how query planners make execution decisions, caching results, and leveraging materialized views in both on-premise and cloud environments. Throughout, we’ll compare approaches in PostgreSQL (representative of many traditional RDBMSs) with modern cloud data warehouses like Snowflake and BigQuery, highlighting best practices and real-world scenarios that intermediate and advanced SQL practitioners can apply.

Recursive Queries, Window Functions, and CTEs

Advanced SQL enables you to express complex logic within queries by using CTEs (including recursive CTEs) and window functions. These features let you handle hierarchical or sequential data and perform analytics directly in SQL, capabilities that earlier SQL dialects lacked or made overly difficult. In this section, we explore the syntax and natural usage ...