Book Image

Learn T-SQL Querying

By : Pedro Lopes, Pam Lahoud
Book Image

Learn T-SQL Querying

By: Pedro Lopes, Pam Lahoud

Overview of this book

Transact-SQL (T-SQL) is Microsoft's proprietary extension to the SQL language used with Microsoft SQL Server and Azure SQL Database. This book will be a usefu to learning the art of writing efficient T-SQL code in modern SQL Server versions as well as the Azure SQL Database. The book will get you started with query processing fundamentals to help you write powerful, performant T-SQL queries. You will then focus on query execution plans and leverage them for troubleshooting. In later chapters, you will explain how to identify various T-SQL patterns and anti-patterns. This will help you analyze execution plans to gain insights into current performance, and determine whether or not a query is scalable. You will also build diagnostic queries using dynamic management views (DMVs) and dynamic management functions (DMFs) to address various challenges in T-SQL execution. Next, you will work with the built-in tools of SQL Server to shorten the time taken to address query performance and scalability issues. In the concluding chapters, this will guide you through implementing various features, such as Extended Events, Query Store, and Query Tuning Assistant, using hands-on examples. By the end of the book, you will have developed the skills to determine query performance bottlenecks, avoid pitfalls, and discover the anti-patterns in use.
Table of Contents (18 chapters)
Free Chapter
1
Section 1: Query Processing Fundamentals
5
Section 2: Dos and Donts of T-SQL
10
Section 3: Assemble Your Query Troubleshooting Toolbox

Mechanics of the Query Optimizer

The next step in our journey toward writing efficient T-SQL queries is understanding how the SQL Server database engine optimizes a query; we will do so by exploring T-SQL query optimization internals and architecture, starting with the infamous cardinality estimation process and its building blocks. From there, we will understand how the Query Optimizer uses that information to produce a just-in-time, good-enough execution plan. This chapter will be referenced throughout this book, as we apply architectural topics to real-world uses.

Before we get started, it's important to have a common frame of reference about the following terms:

  • Cardinality: Cardinality in a database is defined as the number of records, also called tuples, in each table or view.
  • Frequency: This term represents the average number of occurrences of a given value in a...