Big Data: Principles and Best Practices of Scalable Realtime Data Systems
Nathan Marz; James Warren
ISBN 10: 1617290343 ISBN 13: 9781617290343
Editorial: Manning Publications, 2015
Usado
Paperback
Librería:
ThriftBooks-Dallas, Dallas, TX, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Vendedor de AbeBooks desde 2 de julio de 2009
Este artículo en concreto ya no está disponible.
Descripción
Descripción:
May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less. N° de ref. del artículo G1617290343I4N00
Sinopsis:
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
Acerca del 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.
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Detalles bibliográficos
Título: Big Data: Principles and Best Practices of ...
Editorial: Manning Publications
Año de publicación: 2015
Encuadernación: Paperback
Condición: Very Good
Condición de la sobrecubierta: No Jacket