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Learning .NET High-performance Programming
This book will help you understand what "programming for performance" means, and use effective coding patterns and techniques to optimize your .NET applications. You will begin by understanding what "high performance coding" means, and the different performance concerns. You will see how CLR works and get an understanding of concepts such as memory management, garbage collection, and thread life cycles. You will proceed to learn about the theoretical and practical concepts of PLINQ programming. You will also see what Big Data is, and how to architect a Big Data solution to manipulate large datasets. Finally, you will learn how to launch and analyze a profile session and execute tests against a code block or application for performance analysis.
By the end of this book, you will have a complete understanding of efficient programming using high-performance techniques, and will able to write highly optimized applications.
By the end of this book, you will have a complete understanding of efficient programming using high-performance techniques, and will able to write highly optimized applications.
306 pages, Kindle Edition
First published June 30, 2015
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September 5, 2015
Unfortunately the book didn't meet my expectations. I was expecting in-depth content, describing the good and bad practices in different scenarios supported by measurements, pitfalls to be aware of, options to consider. Instead I only got a high-level overview of several performance related aspects, at best.
The introductory chapters are very generic and subjective with very little to support the author's point of view. The remainder of the book covers a broad selection of topics, all of them related to performance in one way or another: Common Language Runtime internals, parallelism and asynchronicity, data access, distributed computing. As a consequence, the author only manages to mention what needs to be considered when thinking about performance, but gives very little guidance or useful advice. Occasional inaccuracies in text and errors in samples decrease the value even further. On top of that, the author's use of English language can make the book more difficult to read.
I really can't recommend the book to anyone, at least not for the full price. At a discount, it might be of limited use to someone, who's just starting to learn about performance, before moving on to more advanced resources. It should still be read with a grain of salt, though.
The introductory chapters are very generic and subjective with very little to support the author's point of view. The remainder of the book covers a broad selection of topics, all of them related to performance in one way or another: Common Language Runtime internals, parallelism and asynchronicity, data access, distributed computing. As a consequence, the author only manages to mention what needs to be considered when thinking about performance, but gives very little guidance or useful advice. Occasional inaccuracies in text and errors in samples decrease the value even further. On top of that, the author's use of English language can make the book more difficult to read.
I really can't recommend the book to anyone, at least not for the full price. At a discount, it might be of limited use to someone, who's just starting to learn about performance, before moving on to more advanced resources. It should still be read with a grain of salt, though.
Displaying 1 of 1 review