SQL Server 2025 Query Performance Tuning, 7th Edition Troubleshoot and Optimize Query Performance (Grant Fritchey)（Z-Library）
SQL
A new era of SQL Server is here, and this latest edition of Grant Fritchey’s best-selling dive into SQL Server query performance can ensure your queries keep up. The fundamentals are still here: You’ll learn how statistics and indexes impact performance, how to identify poorly performing queries, and how to discover effective solutions. But this new edition also includes advanced features unique to SQL Server 2025, such as AI integration for automatic tuning, insights on using extended events, automatic execution plan correction, and more. It’s a must-have resource designed to empower you to troubleshoot slow-performing queries and make them run faster than ever. The book is a treasure trove of instruction, insight, and advice. As you dive in, you’ll encounter key fundamentals, from statistics and data distribution to cardinality and parameter sniffing, and learn to analyze and design your indexes and queries using best practices that prevent performance problems before they occur. You’ll also explore advanced features like Query Store for managing and controlling execution plans, automated performance tuning, and memory-optimized OLTP tables and procedures—and learn how SQL Server 2025 makes it all more powerful and automatable than ever. Who This Book Is For Developers and database administrators with responsibility for query performance in SQL Server environments, and anyone responsible for writing or creating T-SQL queries and in need of insight into bottlenecks—including how to identify them, understand them, and eliminate them
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SQL Server 2025 Query Performance Tuning Troubleshoot and Optimize Query Performance — Seventh Edition — Grant Fritchey
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SQL Server 2025 Query Performance Tuning Troubleshoot and Optimize Query Performance Seventh Edition Grant Fritchey
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SQL Server 2025 Query Performance Tuning: Troubleshoot and Optimize Query Performance, Seventh Edition ISBN-13 (pbk): 979-8-8688-1864-6 ISBN-13 (electronic): 979-8-8688-1865-3 https://doi.org/10.1007/979-8-8688-1865-3 Copyright © 2026 by Grant Fritchey This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Trademarked names, logos, and images may appear in this book. Rather than use a trademark symbol with every occurrence of a trademarked name, logo, or image we use the names, logos, and images only in an editorial fashion and to the benefit of the trademark owner, with no intention of infringement of the trademark. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Managing Director, Apress Media LLC: Welmoed Spahr Acquisitions Editor: Shaul Elson Development Editor: Laura Berendson Coordinating Editor: Gryffin Winkler Cover image designed by wrenchk on Freepik (www.freepik.com) Distributed to the book trade worldwide by Springer Science+Business Media New York, 1 New York Plaza, New York, NY 10004. Phone 1-800-SPRINGER, fax (201) 348-4505, e-mail orders-ny@springer-sbm.com, or visit www.springeronline.com. Apress Media, LLC is a Delaware LLC and the sole member (owner) is Springer Science + Business Media Finance Inc (SSBM Finance Inc). SSBM Finance Inc is a Delaware corporation. For information on translations, please e-mail booktranslations@springernature.com; for reprint, paperback, or audio rights, please e-mail bookpermissions@springernature.com. Apress titles may be purchased in bulk for academic, corporate, or promotional use. eBook versions and licenses are also available for most titles. For more information, reference our Print and eBook Bulk Sales web page at http://www.apress.com/bulk-sales. Any source code or other supplementary material referenced by the author in this book is available to readers on GitHub. For more detailed information, please visit www.apress.com/gp/services/source-code. If disposing of this product, please recycle the paper Grant Fritchey Sapulpa, OK, USA
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Mom, you received a copy of the first of these I wrote. Now you’re gone, but this one is for you as well.
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xxi About the Author Grant Fritchey is a Microsoft Data Platform MVP and AWS Community Builder. He has more than 30 years of experience in IT technical support, development, and database administration. He currently works as a Product Advocate at Redgate Software. Grant writes articles for publication at SQL Server Central and SimpleTalk. He has published books, including Introduction to PostgreSQL for the Data Professional, SQL Server Execution Plans, and SQL Server 2022 Query Performance Tuning (Apress). Grant presents live sessions, virtual sessions, and recorded content online and in person, around the world.
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AI Reading Assistant
Whole-book reading guide from stratified index samples; jump to passages in the text
AI guide
【One-Line Pitch】
A practical, end-to-end guide to making T-SQL queries fast on SQL Server 2025, covering both the enduring fundamentals (statistics, indexes, execution plans) and the new automation features. Best for developers and DBAs who own query performance and need to find, understand, and eliminate bottlenecks.
【Book Arc】
- **Opening (~0%–20%)**: Establishes why query performance matters and how SQL Server decides what to do with your query — the performance-tuning mindset and the diagnostic groundwork before touching indexes or code.
- **Early (~20%–40%)**: Core fundamentals of data distribution and statistics, including cardinality estimation and parameter sniffing — the root causes behind most "the plan went bad" problems.
- **Middle (~40%–60%)**: Index analysis and design plus query design best practices, aimed at preventing performance problems before they occur rather than reacting to them.
- **Late (~60%–80%)**: Execution plan management and control via Query Store, plus automated performance tuning and automatic execution plan correction — turning manual firefighting into managed, repeatable process.
- **Ending (~80%–100%)**: Advanced and specialized territory: extended events for deeper insight, memory-optimized OLTP tables and procedures, and how SQL Server 2025's AI-assisted automation changes the tuning workflow.
【Key Takeaways】
- **Statistics and data distribution drive plan quality** (Early): Cardinality estimation and parameter sniffing explain why the same query can be fast for one parameter value and disastrous for another — understand this before blaming the query text.
- **Index design is a preventive discipline, not a rescue operation** (Middle): Analyzing and designing indexes against real workload patterns stops many performance problems from ever appearing.
- **Query design and indexing go together** (Middle): Best practices for writing T-SQL and for structuring indexes reinforce each other; tuning one while ignoring the other leaves gains on the table.
- **Query Store gives you control over execution plans** (Late): Managing and controlling plans through Query Store is the mechanism that makes plan regressions visible and fixable rather than mysterious.
- **Automation is now part of the tuner's toolkit** (Late): Automated performance tuning and automatic execution plan correction reduce the manual burden of catching and reverting bad plans.
- **Extended events provide the diagnostic depth** (Ending): They are the route to observing what the server is actually doing when surface-level metrics aren't enough.
- **Memory-optimized OLTP is a distinct performance path** (Ending): Memory-optimized tables and procedures address workloads where conventional disk-based structures are the limiting factor.
- **SQL Server 2025 pushes tuning toward AI-assisted automation** (Ending): AI integration for automatic tuning is presented as the headline shift in this edition, making the platform "more powerful and automatable than ever."
【Reading Tips】
- Read the fundamentals (statistics, cardinality, parameter sniffing) slowly and with a real workload open in front of you — these chapters are the diagnostic vocabulary for everything later.
- Treat the index and query-design chapters as a working checklist: apply them to one slow query in your own environment as you go, rather than reading passively.
- If you already manage plans manually, deep-read the Query Store and automated-tuning material — that is where this edition's practical leverage is concentrated.
- Skim the memory-optimized OLTP material unless you actually run such workloads; note it exists and return when relevant.
- Keep the extended events content as a reference section to revisit when you need to investigate a specific problem.
【Coverage Limits】
The source excerpts consist only of the book's front matter and description; they do not cover specific chapter titles, code examples, benchmark figures, or detailed technical procedures. This guide therefore maps the book's stated scope and progression rather than its internal chapter structure.
Passage locations
Excerpt 1
书名: SQL Server 2025 Query Performance Tuning, 7th Edition Troubleshoot and Optimize Query Performance (Grant Fritchey) (z-library.sk, 1lib.sk, z-lib.sk) 作者:...
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