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Ever wondered what actually happens between typing a SQL query and seeing your results appear? Behind every database lies a hidden engineering marvel: the query engine. It parses your text, reasons about the fastest way to answer it, and executes that plan across anything from a single laptop to a cluster spanning continents. Most engineers use this machinery every single day without ever understanding how it works. This book changes that. Building Query Engines takes you on a complete journey through the internals of modern data systems, from the first character of a SQL string to the final row returned from a distributed cluster. Rather than treating parsing, optimization, and execution as separate, disconnected topics, this book weaves them into a single coherent narrative, showing you exactly how real systems like PostgreSQL, Apache Spark, Trino, and DuckDB solve the same fundamental problems you'll solve yourself. Inside, you'll learn how to: This is not a book of abstract theory. Every concept is grounded in working code and real engineering trade-offs, so you build genuine intuition instead of memorizing definitions. Whether you're a backend engineer curious about what happens after you hit execute, a data engineer who wants to move beyond tuning by folklore, or a systems programmer looking for a serious project to sharpen your skills, this book gives you a clear, honest path from first principles to a working query engine of your own. By the end, you won't just write SQL. You'll understand it, from the inside out.
• Validate queries and translate them into relational algebra
• Build a cost-based optimizer that chooses efficient execution plans
• Implement core operators including joins, aggregations, and sorts
• Manage memory when working sets exceed available RAM
• Take advantage of modern hardware through vectorized execution
• Scale query processing across distributed clusters
• Handle the failures, network delays, and coordination challenges unique to distributed systems
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