Book Image

Learn T-SQL Querying - Second Edition

By : Pedro Lopes, Pam Lahoud
Book Image

Learn T-SQL Querying - Second Edition

By: Pedro Lopes, Pam Lahoud

Overview of this book

Data professionals seeking to excel in Transact-SQL (T-SQL) for Microsoft SQL Server and Azure SQL Database often lack comprehensive resources. This updated second edition of Learn T-SQL Querying focuses on indexing queries and crafting elegant T-SQL code, catering to all data professionals seeking mastery in modern SQL Server versions and Azure SQL Database. Starting with query processing fundamentals, this book lays a solid foundation for writing performant T-SQL queries. You’ll explore the mechanics of the Query Optimizer and Query Execution Plans, learning how to analyze execution plans for insights into current performance and scalability. Through dynamic management views (DMVs) and dynamic management functions (DMFs), you’ll build diagnostic queries. This book thoroughly covers indexing for T-SQL performance and provides insights into SQL Server’s built-in tools for expedited resolution of query performance and scalability issues. Further, hands-on examples will guide you through implementing features such as avoiding UDF pitfalls, understanding predicate SARGability, Query Store, and Query Tuning Assistant. By the end of this book, you‘ll have developed the ability to identify query performance bottlenecks, recognize anti-patterns, and skillfully avoid such pitfalls.
Table of Contents (18 chapters)
1
Part 1: Query Processing Fundamentals
4
Part 2: Dos and Don’ts of T-SQL
9
Part 3: Assembling Our Query Troubleshooting Toolbox

Understanding QTA fundamentals

While guiding us through the recommended process, QTA doesn’t follow it exactly. The very last step, step 5, will not have the same outcome we saw in the previous section; instead of providing options to revert to a last known good plan, QTA helps to find a new state that is not the pre-CE upgrade or post-CE upgrade plan but a new plan that will hopefully outperform both of the previous plans.

The following diagram summarizes the recommended steps to minimize risk with CE upgrades using QTA, which replaces the very last step of the process described in the previous Understanding where QTA and CE Feedback are needed section:

Figure 12.4: The recommended steps to minimize risk with CE upgrades using QTA

Figure 12.4: The recommended steps to minimize risk with CE upgrades using QTA

How does QTA find a better query plan for regressed queries? Starting with the same data that’s available in Query Store’s Regressed Queries report, QTA will look for query patterns that may be affected...