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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
Author Profile Icon Pam Lahoud
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

Tracking expensive queries

Query Store only collects plans for Data Manipulation Language (DML) statements such as SELECT, INSERT, UPDATE, DELETE, MERGE, and BULK INSERT, as these are the T-SQL statements that will be responsible for most of our SQL Database Engine’s resource usage. Most database administrators (DBAs) and database reliability engineers are constantly looking for ways to optimize resource usage; after all, if T-SQL queries are using just the resources they need (CPU, I/O, and memory), then the SQL Database Engine is operating at peak efficiency and allows for maximum concurrency with its current hardware resources.

This brings us to one of the main benefits of Query Store: tracking our workload heavy hitters – the most resource-consuming queries. With this exercise, we may be able to uncover tuning opportunities that, if successful, further improve the efficiency of the server’s resource usage.

To generate enough workload in our AdventureWorks...

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