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

Nathan Marz, James Warren

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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

商品描述(中文翻譯)

社交網絡、網絡分析和智能電子商務等服務通常需要處理傳統數據庫無法應對的大規模數據。隨著規模和需求的增加,複雜性也隨之增加。幸運的是,可擴展性和簡單性並不是互相排斥的,而是需要一種不同的方法,而不是使用一些時髦的技術。大數據系統使用多台機器並行存儲和處理數據,這引入了對大多數開發人員來說不熟悉的基本挑戰。

《大數據》展示了如何使用一種利用集群硬件和專門設計用於捕獲和分析網絡規模數據的新工具的架構來構建這些系統。它描述了一種可擴展且易於理解的大數據系統方法,可以由一個小團隊構建和運行。通過一個實際的例子,本書引導讀者了解大數據系統的理論,如何在實踐中使用它們,以及在構建完成後如何部署和運營它們。

購買印刷版書籍可獲得免費的PDF、ePub和Kindle電子書,還提供書中的所有代碼。