[PDF/Kindle] Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems by Martin Kleppmann
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Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems by Martin Kleppmann
- Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems
- Martin Kleppmann
- Page: 500
- Format: pdf, ePub, mobi, fb2
- ISBN: 9781449373320
- Publisher: O'Reilly Media, Incorporated
Public domain free ebooks download Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems
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.
Designing Data-Intensive Applications: The Big Ideas Behind
Download Designing Data-Intensive Applications: The Big Ideas Behind Reliable , Scalable, and Maintainable Systems eBook PDF File.
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Big Data AnalyticseBook Resources in Resources | Pentaho | Page 1
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems. Type: eBook. Product: Data Integration, Big Data
Designing Data-Intensive Applications: The Big Ideas Behind
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and The Big Ideas Behind Reliable, Scalable, and Maintainable Systems Big Data: Principles and best practices of scalable realtime data systems.
Data Intensive | Big Data Intensive Architectures
A systematic way of approaching Big Data complex projects. This framework is a template for design data pipelines with different requirements: such as Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems by Martin Kleppmann (Apache Samza).
Designing DataIntensive Applications The Big Ideas Behind
Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems by Martin Kleppmann. (Paperback
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