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

Query plan analyzer

So far, we have had to analyze query plans by correlating information in plan and operator properties to create working hypotheses on how to solve query performance issues. One constant throughout all these troubleshooting scenarios has to do with comparing estimated rows with actual rows flowing through the operators in a query plan. This is because significant differences between estimated and actual rows usually expose cardinality estimation issues, which speak to several possible causes, from outdated statistics to parameter sniffing or even out-of-model constructs such as User-Defined Functions (UDFs) or Multi-Statement Table-Valued Functions (MSTVFs).

Depending on the query performance problem, it may not be easy to even start troubleshooting, especially in complex plans. This is exactly why SSMS has a plan analysis tool, and this can jump-start our query performance troubleshooting efforts.

In the following example, we will examine a query that was...