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

The perils of SELECT *

SELECT * should be avoided in stored procedures, views, and Multi-Statement Table-Valued Functions (MSTVFs) because our T-SQL code might break if there are any changes to the underlying schema. For example, applications that reference SELECT * may rely on the ordinal position rather than column names and may encounter errors if the underlying table definition is changed. Instead, fully qualify the names of columns that are relevant to our result set.

This also has important performance implications. Some application patterns may rely on reading an entire dataset and applying filters in the client layer only. For example, imagine a web application where a sales supervisor can see a report of orders registered for a given month, with details per product. The application connects to the AdventureWorks sample database and runs a query:

Dim myConnection As New SqlConnection("Our Connection String")
Dim cmd As New SqlCommand
Dim reader As SqlDataReader...