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Learn T-SQL Querying

You're reading from   Learn T-SQL Querying A guide to developing efficient and elegant T-SQL code

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Product type Paperback
Published in Feb 2024
Publisher Packt
ISBN-13 9781837638994
Length 456 pages
Edition 2nd Edition
Languages
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Authors (2):
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Pedro Lopes Pedro Lopes
Author Profile Icon Pedro Lopes
Pedro Lopes
Pam Lahoud Pam Lahoud
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Pam Lahoud
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Toc

Table of Contents (18) Chapters Close

Preface 1. Part 1: Query Processing Fundamentals
2. Chapter 1: Understanding Query Processing FREE CHAPTER 3. Chapter 2: Mechanics of the Query Optimizer 4. Part 2: Dos and Don’ts of T-SQL
5. Chapter 3: Exploring Query Execution Plans 6. Chapter 4: Indexing for T-SQL Performance 7. Chapter 5: Writing Elegant T-SQL Queries 8. Chapter 6: Discovering T-SQL Anti- Patterns in Depth 9. Part 3: Assembling Our Query Troubleshooting Toolbox
10. Chapter 7: Building Diagnostic Queries Using DMVs and DMFs 11. Chapter 8: Building XEvent Profiler Traces 12. Chapter 9: Comparative Analysis of Query Plans 13. Chapter 10: Tracking Performance History with Query Store 14. Chapter 11: Troubleshooting Live Queries 15. Chapter 12: Managing Optimizer Changes 16. Index 17. Other Books You May Enjoy

Fuzzy string matching

When searching for strings in the SQL Database Engine using =, the strings must match exactly for the expression to evaluate to true. If we want to match only part of the string, however, we must use a LIKE operator with wildcards. If we want to search for a pattern anywhere within a string, we need both leading and trailing wildcards. The problem with this is that it prevents us from being able to use an index or accurately estimate the cardinality. An index with a string key is sorted starting with the first character of the string, but if we are searching for a pattern that may appear in the middle of the string, the SQL Database Engine must scan every value and search for the matching pattern in each string in the column. A LIKE operator with a leading wildcard (%a value or %a value%) almost always causes a scan operation.

Consider an example from the AdventureWorks database where we want to find all the Flat Washers in the Product table. We know they all...

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