BIG DATA: PRINCIPLES AND BEST PRACTICES OF SCALABLE REAL-TIME DATA SYSTEMS

Nathan Marz ET AL

ISBN 10: 1617290343 / ISBN 13: 9781617290343

Verlag: Manning, 2015

Beschreibung

Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.

Bestandsnummer des Verkäufers ABNR-7384

Bibliografische Details

• Titel: BIG DATA: PRINCIPLES AND BEST PRACTICES OF SCALABLE REAL-TIME DATA SYSTEMS
• Verlag: Manning
• Erscheinungsjahr: 2015
• Sprache: Englisch
• ISBN-10: 1617290343
• ISBN-13: 9781617290343
• Einband: Softcover
• Auflage: Internationale Ausgabe
• Zustand: New

Über diesen Titel

Inhaltsangabe

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

Über die Autorin bzw. den Autor

Nathan Marz is an engineer at Twitter. He was previously Lead Engineer at BackType, a marketing intelligence company that was acquired by Twitter in July of 2011. He is the author of two major open source projects: Storm, a distributed realtime computation system, and Cascalog, a tool for processing data on Hadoop. He is a frequent speaker and writes a blog at nathanmarz.com.

 

James Warren is an analytics architect at Storm8 with a background in big data processing, machine learning and scientific computing.