Pro SQL Server Internals
Article Index
Pro SQL Server Internals
Chapters 5 -11
Chapters 12 -17
Chapters 18 - 24
Chapter 25 - 29
Chapters 30 - 35
Conclusion

 

Author: Dmitri Korotkevitch
Publisher: Apress
Pages: 804
ISBN: 978-1430259626
Audience: DBAs, Database developers
Rating: 4.9
Reviewer: Ian Stirk

Conclusion

This book provides an in-depth look at a wide range of SQL Server topics from an internals and performance related perspective.

 

 

It assumes some background knowledge of SQL Server, perhaps a few years SQL development. It is relatively easy to read, with excellent explanations, good use of screenshots, and detailed example code throughout to back up the assertions made. There are good links between the chapters, and to further information available on the web. Most chapters end with a very useful, and relatively long, summary. Having a single author undoubtedly contributed to a more consistent quality of explanations, and prevented duplication.

The book is wide-ranging, with coverage from User-Defined Functions to High Availability options. This is matched by its great detail, including examination of execution plans and physical database page/row content. There is no filler in this book, it is all useful detail. Throughout there are useful incidental tips provided. The author provides a balanced approach in his discussions, giving both the pros and cons to each problem’s solutions. There were few errors, mostly relating to editing, but nothing too distracting.

This book will take your level of SQL Server internals/performance understanding from say level 4 to level 9 (out of 10). I learned something new in almost every chapter, and there are lots of chapters! I started this review wondering if we needed another SQL Server internals book, I’ll finish it by saying this is the best SQL Server internals/performance book I’ve read, I congratulate the author on his industry.

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Python All-in-One, 2nd Ed (For Dummies)

Authors: John Shovic and Alan Simpson
Publisher: For Dummies
Date: April 2021
Pages: 720
ISBN: 978-1119787600
Print: 1119787602
Kindle: B091DGDLK8
Audience: People wanting to learn Python
Rating: 2
Reviewer: Mike James
All-in-one refers to the fact that this is seven books put together - why?



Artificial Intelligence, Machine Learning, and Deep Learning (Mercury Learning)

Author: Oswald Campesato
Publisher: Mercury Learning
Date: February 2020
Pages: 300
ISBN: 978-1683924678
Print: 1683924673
Kindle: B084P1K9YP
Audience: Developers interested in machine learning
Rating: 4
Reviewer: Mike James

Another AI/ML book - is there room for another one?


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Last Updated ( Tuesday, 01 May 2018 )