Big Data:Principles and best practices of scalable realtime data systems
Language: English
Published by Manning Publications, United States, New York, 2015
- Softcover
- Used
Seller: WorldofBooks, Goring-By-Sea, WS, United KingdomWorldofBooks
AbeBooks seller since March 16, 2007
Condition: Used - Very good
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Add to basketItem description from seller
Services like social networks, web analytics, and intelligent e-commerce often need to manage data at a scale too big for a traditional database. As scale and demand increase, so does Complexity. Fortunately, scalability and simplicity are not mutually exclusive rather than using some trendy technology, a different approach is needed. Big data systems use many machines working in parallel to store and process data, which introduces fundamental challenges unfamiliar to most developers. Big Data shows how to build these systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy to understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to use them in practice, and how to deploy and operate them once they're built. AUDIENCE This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful. ABOUT THE TECHNOLOGY To tackle the challenges of Big Data, a new breed of technologies has emerged. Many of which have been grouped under the term "NoSQL." In some ways these new technologies can be more complex than traditional databases and in other ways, simpler. Using them effectively requires a fundamentally new set of techniques . The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.…
Seller Inventory # GOR007665332
- Title
- Big Data:Principles and best practices of scalable realtime data systems
- Author
- Nathan Marz
- Publisher
- Manning Publications, United States, New York
- Publication year
- 2015
- Condition
- Very Good
- Binding
- Paperback
- Language
- English
- ISBN 10
- 1617290343
- ISBN 13
- 9781617290343
- Item weight
- 572 grams
- Dimensions
- 186.0 x 232.0
Services like social networks, web analytics, and intelligent e-commerce often need to manage data at a scale too big for a traditional database. As scale and demand increase, so does Complexity. Fortunately, scalability and simplicity are not mutually exclusive― rather than using some trendy technology, a different approach is needed. Big data systems use many machines working in parallel to store and process data, which introduces fundamental challenges unfamiliar to most developers.
Big Data shows how to build these systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy to understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to use them in practice, and how to deploy and operate them once they're built.
AUDIENCE
This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful.
ABOUT THE TECHNOLOGY
To tackle the challenges of Big Data, a new breed of technologies has emerged. Many of which have been grouped under the term "NoSQL." In some ways these new technologies can be more complex than traditional databases and in other ways, simpler. Using them effectively requires a fundamentally new set of techniques
"Synopsis" may belong to another edition of this title.
About the Author
"About the title" may belong to another edition of this title.
WorldofBooks
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