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Big Data: Principles and best practices of scalable realtime data
systems
Nathan Marz with James Warren
Copyright
For online information and ordering of this and other Manning books, please visit www.manning.com. The publisher offers discounts on this book
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©2015 by Manning Publications Co. All rights reserved.
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appear in the book, and Manning Publications was aware of a trademark claim, the designations have been printed in initial caps or all caps.
Recognizing the importance of preserving what has been written, it is Manning’s policy to have the books we publish printed on acid-free
paper, and we exert our best efforts to that end. Recognizing also our responsibility to conserve the resources of our planet, Manning books are
printed on paper that is at least 15 percent recycled and processed without the use of elemental chlorine.
Manning Publications Co.
20 Baldwin Road
PO Box 761
Shelter Island, NY 11964
Development editors: Renae Gregoire, Jennifer Stout
Technical development editor: Jerry Gaines
Copyeditor: Andy Carroll
Proofreader: Katie Tennant
Technical proofreader: Jerry Kuch
Typesetter: Gordan Salinovic
Cover designer: Marija Tudor
ISBN 9781617290343
Printed in the United States of America
1 2 3 4 5 6 7 8 9 10 – EBM – 20 19 18 17 16 15
Brief Table of Contents
Copyright
Brief Table of Contents
Table of Contents
Preface
Acknowledgments
About this Book
Chapter 1. A new paradigm for Big Data
1. Batch layer
Chapter 2. Data model for Big Data
Chapter 3. Data model for Big Data: Illustration
Chapter 4. Data storage on the batch layer
Chapter 5. Data storage on the batch layer: Illustration
Chapter 6. Batch layer
Chapter 7. Batch layer: Illustration
Chapter 8. An example batch layer: Architecture and algorithms
Chapter 9. An example batch layer: Implementation
2. Serving layer
Chapter 10. Serving layer
Chapter 11. Serving layer: Illustration
3. Speed layer
Chapter 12. Realtime views
Chapter 13. Realtime views: Illustration
Chapter 14. Queuing and stream processing
Chapter 15. Queuing and stream processing: Illustration
Chapter 16. Micro-batch stream processing
Chapter 17. Micro-batch stream processing: Illustration
Chapter 18. Lambda Architecture in depth
Index
List of Figures
List of Tables
List of Listings
Table of Contents
Copyright
Brief Table of Contents
Table of Contents
Preface
Acknowledgments
About this Book
Chapter 1. A new paradigm for Big Data
1.1. How this book is structured
1.2. Scaling with a traditional database
1.2.1. Scaling with a queue
1.2.2. Scaling by sharding the database
1.2.3. Fault-tolerance issues begin
1.2.4. Corruption issues
1.2.5. What went wrong?
1.2.6. How will Big Data techniques help?
1.3. NoSQL is not a panacea
1.4. First principles
1.5. Desired properties of a Big Data system
1.5.1. Robustness and fault tolerance
1.5.2. Low latency reads and updates
1.5.3. Scalability
1.5.4. Generalization
1.5.5. Extensibility
1.5.6. Ad hoc queries
1.5.7. Minimal maintenance
1.5.8. Debuggability
1.6. The problems with fully incremental architectures
1.6.1. Operational complexity
1.6.2. Extreme complexity of achieving eventual consistency
1.6.3. Lack of human-fault tolerance
1.6.4. Fully incremental solution vs. Lambda Architecture solution
1.7. Lambda Architecture
1.7.1. Batch layer
1.7.2. Serving layer
1.7.3. Batch and serving layers satisfy almost all properties
1.7.4. Speed layer
1.8. Recent trends in technology
1.8.1. CPUs aren’t getting faster
1.8.2. Elastic clouds
1.8.3. Vibrant open source ecosystem for Big Data
1.9. Example application: SuperWebAnalytics.com
1.10. Summary
1. Batch layer
Chapter 2. Data model for Big Data
2.1. The properties of data
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- 江枫abalone2017-07-03看了第一章部分,就是排版比原来的差,内容基本一致。
- kofkyo2017-10-17清晰度不错,字有点小
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