Indexing and Performance Tuning
SQL Indexing: Transform Your Database Performance,Improve database performance with strategic SQL indexing and query optimization.
Slow SQL is expensive. Whether you’re fighting timeouts in production or planning a resilient data layer, this practical guide shows you how to turn performance pain into predictable, measurable speedups across MySQL, PostgreSQL, and SQL Server.
Move beyond guesswork with a repeatable workflow for diagnosing bottlenecks, designing the right indexes, and reading execution plans like a pro.
Optimize SQL Queries with Indexes, Execution Plans, and Database Tuning Techniques
Overview
This definitive IT book delivers a clear, hands-on path to Indexing and Performance Tuning for modern systems. You’ll learn how to Optimize SQL Queries with Indexes, Execution Plans, and Database Tuning Techniques through real-world walkthroughs that apply core SQL principles across multiple engines. As a programming guide and technical book, it covers SQL indexing strategies, query execution plans, performance optimization, database tuning, index maintenance, JOIN optimization, query analysis, database architecture, performance monitoring, execution plan interpretation, index design patterns, and query debugging techniques—so you can diagnose issues quickly and ship faster, more reliable applications.
Who This Book Is For
- Application developers who want to ship features without regressions—learn how to design queries and indexes that scale as data and traffic grow.
- DBAs and data engineers seeking repeatable tuning playbooks—gain a deep understanding of execution plans, statistics, and storage internals to achieve predictable outcomes.
- Engineering leaders and architects responsible for uptime—build an optimization culture with measurable KPIs, performance monitoring, and capacity planning that keeps costs in check.
Key Lessons and Takeaways
- Design high-impact indexes that match access patterns. You’ll map predicates, sort orders, and JOINs to composite keys, covering indexes, and filtered/partial indexes to reduce I/O and CPU.
- Master execution plan interpretation to find the real bottleneck. Learn to spot table scans, key lookups, hash vs. merge joins, cardinality misestimates, and spilled sorts so fixes are targeted, not guesswork.
- Implement a systematic tuning workflow from query analysis to validation. Profile, hypothesize, test, and verify with baselines, ensuring every change improves throughput and latency in production.
Why You’ll Love This Book
It’s relentlessly practical. Each chapter translates complex internals into plain language, then backs it up with step-by-step checklists, annotated plan examples, and platform-specific notes for MySQL, PostgreSQL, and SQL Server. You’ll find battle-tested guidance on index design patterns, JOIN optimization, and index maintenance that you can apply the same day. No fluff—just actionable strategies, diagnostic techniques, and tooling recommendations that shorten time-to-fix and raise performance confidence.
How to Get the Most Out of It
- Start with the fundamentals, then iterate. Read the indexing core concepts, move into query execution plans, and finish with advanced database tuning. Use the appendices as quick-reference for syntax and plan operators.
- Apply concepts in your real workload. Capture slow queries from your production logs, analyze actual execution plans, and align indexes to the most expensive predicates and JOIN paths. Track improvements with before/after metrics.
- Build mini-projects to reinforce learning. For example: create a composite index to eliminate a key lookup; refactor a multi-join report to reduce sort spills; implement a maintenance window for statistics refresh and index defragmentation, then measure impact.
What You’ll Learn in Practice
You’ll learn how to map business questions to efficient SQL, choose the right access method, and validate improvements with hard data. By practicing execution plan interpretation, you’ll stop treating the optimizer as a black box and start bending it to your goals.
Expect concrete coverage of clustered vs. nonclustered structures, partial and filtered indexes, covering strategies, and when to lean on include columns. You’ll also see how statistics, histograms, and correlation affect cardinality estimates and why parameter sniffing can tank otherwise “good” queries.
Platform-Specific Wisdom
Across engines, the principles remain steady, but the knobs differ. For MySQL, explore InnoDB nuances, composite key ordering, and the pitfalls of functions on indexed columns. In PostgreSQL, leverage partial indexes, BRIN/GiST/GiN where appropriate, and avoid plan instability with careful statistics targets.
In SQL Server, learn to decode actual vs. estimated plans, identify residual predicates, and mitigate key lookups with covering indexes or rowstore/columnstore trade-offs. Each section highlights tooling—from EXPLAIN and auto_explain to Query Store and DMVs—to streamline query analysis and performance monitoring.
Production-Ready Checklists
The book includes concise checklists for index maintenance, from rebuild vs. reorganize decisions to fill factor and fragmentation thresholds. You’ll adopt a cadence for statistics updates, dead-index review, and regression detection that fits CI/CD workflows.
You also get lightweight runbooks for throttling long-running migrations, validating plan stability after version upgrades, and establishing SLO-aligned alerting that prioritizes user-facing latency.
Common Pitfalls—and How to Avoid Them
Stop over-indexing by tying every index to a real query pattern and measuring write overhead. Prevent plan thrashing with stable parameterization and carefully chosen hints only when evidence supports them.
Avoid premature denormalization by first tightening predicates, fixing join order, and ensuring selective filtering happens early. When denormalization is warranted, the book shows how to measure the trade-off with storage and update costs.
Your Roadmap to Consistent Wins
By the end, you’ll have a repeatable toolkit: identify the top offenders, read the plan, choose a minimal, high-leverage change, and verify with controlled tests. This is performance optimization you can trust—transparent, measurable, and portable across stacks.
Get Your Copy
Ready to crush slow queries and scale with confidence? Equip yourself with a proven, engine-agnostic methodology and start delivering faster features, happier users, and lower infrastructure costs.
