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

Pitfalls of complex views

Views are often used with the same intent as User-Defined Functions (UDFs) – to allow easy re-use of what could otherwise be a complex expression to inline in our T-SQL query. Often developers build a view that will serve multiple queries, and then just select from that view with different SELECT statements and different filters, be those joins or search predicates. However, what may look like a seemingly harmless T-SQL construct may be detrimental for query performance if the underlying view is complex.

Imagine that in the AdventureWorks sample database, a developer built an all-encompassing view that gets data on all company employees, as in the following example:

CREATE OR ALTER VIEW [HumanResources].[vEmployeeNew]
AS
SELECT e.[BusinessEntityID], p.[Title], p.[FirstName], p.[MiddleName],
     p.[LastName], p.[Suffix], e.[JobTitle], pp.[PhoneNumber],
     pnt.[Name] AS [PhoneNumberType], ea....