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High-Performance Programming in C# and .NET

You're reading from   High-Performance Programming in C# and .NET Understand the nuts and bolts of developing robust, faster, and resilient applications in C# 10.0 and .NET 6

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Product type Paperback
Published in Jul 2022
Publisher Packt
ISBN-13 9781800564718
Length 660 pages
Edition 1st Edition
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Author (1):
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Jason Alls Jason Alls
Author Profile Icon Jason Alls
Jason Alls
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Table of Contents (22) Chapters Close

Preface 1. Part 1: High-Performance Code Foundation
2. Chapter 1: Introducing C# 10.0 and .NET 6 FREE CHAPTER 3. Chapter 2: Implementing C# Interoperability 4. Chapter 3: Predefined Data Types and Memory Allocations 5. Chapter 4: Memory Management 6. Chapter 5: Application Profiling and Tracing 7. Part 2: Writing High-Performance Code
8. Chapter 6: The .NET Collections 9. Chapter 7: LINQ Performance 10. Chapter 8: File and Stream I/O 11. Chapter 9: Enhancing the Performance of Networked Applications 12. Chapter 10: Setting Up Our Database Project 13. Chapter 11: Benchmarking Relational Data Access Frameworks 14. Chapter 12: Responsive User Interfaces 15. Chapter 13: Distributed Systems 16. Part 3: Threading and Concurrency
17. Chapter 14: Multi-Threaded Programming 18. Chapter 15: Parallel Programming 19. Chapter 16: Asynchronous Programming 20. Assessments 21. Other Books You May Enjoy

Chapter 10: Setting Up Our Database Project

In this and the following two chapters, we will be improving the performance of your database-based applications. In this chapter, we will be setting up our relational database and the code to access that database. In the next chapter, we will write benchmarks to test the performance of the different frameworks, which consist of Entity Framework, Dapper, and ADO.NET. Finally, in Chapter 12, Responsive User Interfaces, we will learn how to improve the performance of SQL Server and Cosmos DB.

Data is extensively used in all aspects of our daily lives. In today's world of big data, the volume of data being collected and stored for all kinds of analysis is phenomenal. When working with data, performance can slow down exponentially as the size of your data grows. And depending on how much data you have to process, time is often critical.

In this chapter, we will create a database and populate it, and we will write the code to access...

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