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Designing Data–Intensive Applications

Autor Martin Kleppmann
Notă:  5.00 · 3 note 
en Limba Engleză Paperback – 14 mar 2017
Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and mainteinability. In addition, we have an overwhelming variet of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive gjuide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications.
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Specificații

ISBN-13: 9781449373320
ISBN-10: 1449373321
Pagini: 614
Dimensiuni: 177 x 232 x 32 mm
Greutate: 0.98 kg
Editura: O'Reilly

Descriere

Want to know how the best software engineers and architects structure their applications to make them scalable, reliable, and maintainable in the long term? This book examines the key principles, algorithms, and trade-offs of data systems, using the internals of various popular software packages and frameworks as examples.

Tools at your disposal are evolving and demands on applications are increasing, but the principles behind them remain the same. You ll learn how to determine what kind of tool is appropriate for which purpose, and how certain tools can be combined to form the foundation of a good application architecture. You ll learn how to develop an intuition for what your systems are doing, so that you re better able to track down any problems that arise.

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Notă biografică

Martin is a researcher in distributed systems at the University of Cambridge. Previously he was a software engineer and entrepreneur at Internet companies including LinkedIn and Rapportive, where he worked on large-scale data infrastructure. In the process he learned a few things the hard way, and he hopes this book will save you from repeating the same mistakes.



Martin is a regular conference speaker, blogger, and open source contributor. He believes that profound technical ideas should be accessible to everyone, and that deeper understanding will help us develop better software.