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

Query execution essentials

Query execution is driven by the relational engine in SQL Server. This means executing the plan that resulted from the optimization process. In this section, we will focus on the highlighted sections of the following diagram, which handle query execution:

Before execution starts, the relational engine needs to initialize the estimated amount of memory necessary to run the query, known as a memory grant. Along with the actual execution, the relational engine schedules the worker threads (also known as threads, or workers) for the processes to run on and provides inter-thread communication. The number of worker threads spawned depends on the following two key aspects:

  • Whether the plan was eligible for parallelism as determined by the Query Optimizer.
  • The actual available Degree of Parallelism (DOP) in the system, based on current load. This may differ...