Big Data: Principles and best practices of scalable realtime data systems (Paperback)

Nathan Marz, James Warren

  • 出版商: Manning Publications
  • 出版日期: 2015-05-10
  • 售價: $1,650
  • 貴賓價: 9.5$1,568
  • 語言: 英文
  • 頁數: 328
  • 裝訂: Paperback
  • ISBN: 1617290343
  • ISBN-13: 9781617290343
  • 相關分類: JVM 語言大數據

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content<div><p>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.</p> <p><i>Big Data</i> 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.</p> <p> 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. </p></div>sourceProduct Description