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

Indexing strategy using rowstore indexes

Now that we’ve covered the basics of how rowstore indexes are structured and how they are used to access data, let’s move on to where and when they should be used, along with some best practices for efficient index design.

The goal of an indexing strategy is to minimize the amount of I/O required to satisfy the queries being generated against the database. This translates into a few simple guidelines:

  • Keep indexes as small as possible. The more rows that fit on a page, the fewer page reads that are required to access the data.
  • Avoid lookups – they add unnecessary I/O and can sometimes lead to suboptimal query plans.
  • Choose index keys that support query predicates so that indexes can be used for seeks rather than scans.
  • When creating indexes with multiple key columns, columns used for equality comparisons should be first, followed by columns used for inequality comparisons. The leading column should...