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Big data: principles and best practices of scalable real-time data systems

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 techno...

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Detalles Bibliográficos
Autores principales: Marz, Nathan, Warren, James
Lenguaje:eng
Publicado: Manning 2013
Materias:
Acceso en línea:http://cds.cern.ch/record/1530819
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author Marz, Nathan
Warren, James
author_facet Marz, Nathan
Warren, James
author_sort Marz, Nathan
collection CERN
description 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. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.
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spelling cern-15308192021-04-21T22:50:17Zhttp://cds.cern.ch/record/1530819engMarz, NathanWarren, JamesBig data: principles and best practices of scalable real-time data systemsComputing and ComputersServices 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. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.Manningoai:cds.cern.ch:15308192013-04-28
spellingShingle Computing and Computers
Marz, Nathan
Warren, James
Big data: principles and best practices of scalable real-time data systems
title Big data: principles and best practices of scalable real-time data systems
title_full Big data: principles and best practices of scalable real-time data systems
title_fullStr Big data: principles and best practices of scalable real-time data systems
title_full_unstemmed Big data: principles and best practices of scalable real-time data systems
title_short Big data: principles and best practices of scalable real-time data systems
title_sort big data: principles and best practices of scalable real-time data systems
topic Computing and Computers
url http://cds.cern.ch/record/1530819
work_keys_str_mv AT marznathan bigdataprinciplesandbestpracticesofscalablerealtimedatasystems
AT warrenjames bigdataprinciplesandbestpracticesofscalablerealtimedatasystems