Goal
The path to "SQL Performance Explained"
Here is the reading path leading up to this book, derived from its dependencies and ordered from the fundamentals.
The path so far (6 books)
Why read this first: SQL Queries for Mere Mortals begins by checking that the database structure is sound, in its second chapter, before any query is written. Having worked through tables, keys and relationships as a design process first, you can read the join and subquery chapters knowing why the tables connect the way they do. Both books belong to the For Mere Mortals series and neither depends on a particular database product.
Why read this first: SQL Queries for Mere Mortals concentrates on how to express SELECT, joins, subqueries and grouping in standard SQL. Once writing a WHERE clause or a join no longer takes thought, SQL Performance Explained picks up the next question about those same clauses: how they use an index.
Why read this first: Once you have the basics of SELECT, the natural next step is set-oriented techniques—CASE expressions, window functions, set operations—that teach you to think in sets rather than procedurally. Both are Japanese SQL books by the same author (Mick), so the vocabulary carries over smoothly from introduction to application.
Why read this first: After learning to read execution plans in the practical intro, dig deeper into the internal structure of indexes themselves with Winand's 'SQL Performance Explained'. Understanding index structure clarifies why a plan chooses a given access path, raising the resolution of your tuning.
Why read this first: Grasping relational theory first makes the set operations and window functions in this advanced SQL guide land as the logical necessity of 'why think in sets'. Reading theory → implementation lets you derive each advanced SQL technique from first principles rather than memorizing it ad hoc.
Why read this first: Once you can write applied SQL, you want to understand why a query is fast or slow from the internal structure of indexes. Markus Winand's 'SQL Performance Explained' builds index design up from how B-Trees work, connecting the way you write SQL with how fast it runs.