Big Data: Principles and best practices of scalable realtime data systems (Paperback)
暫譯: 大數據:可擴展即時數據系統的原則與最佳實踐
Nathan Marz, James Warren
- 出版商: Manning
- 出版日期: 2015-05-10
- 售價: $1,700
- 貴賓價: 9.5 折 $1,615
- 語言: 英文
- 頁數: 328
- 裝訂: Paperback
- ISBN: 1617290343
- ISBN-13: 9781617290343
-
相關分類:
大數據 Big-data
-
相關翻譯:
大數據系統構建:可擴展實時數據系統構建原理與最佳實踐 (簡中版)
立即出貨 (庫存 < 3)
買這商品的人也買了...
-
$399R Cookbook (Paperback) -
Cracking the Coding Interview, 5/e : 150 Programming Questions and Solutions (Paperback)$1,500$1,425 -
王者歸來-資料存儲系統架構極限剖析$860$731 -
NoSQL Distilled: A Brief Guide to the Emerging World of Polyglot Persistence (Paperback)$1,685$1,651 -
amazon.com 的祕密$320$272 -
實戰 SEO-60 天讓網站流量增加 20 倍$580$458 -
$354BackTrack 4︰利用滲透測試保證系統安全 (BackTrack 4: Assuring Security by Penetration Testing) -
$948Single Page Web Applications: JavaScript end-to-end (Paperback) -
超圖解 Arduino 互動設計入門 (附 Arduino UNO R3 開發板)$1,130$961 -
巨型網站大師親自指導─建立極速的 Web 站台的祕密$620$527 -
$252安全的神話-電腦安全行業不想讓你知道的事 (The Myths of Security: What the Computer Security Industry Doesn't Want You to Know) -
提升程式設計的解題思考力-國際演算法程式設計競賽訓練指南$500$395 -
CI (Continuous integration) 關鍵技術—使用 Jenkins$420$332 -
Operating System Concepts, 9/e (IE-Paperback)$1,680$1,646 -
$825Practical Data Science with R (Paperback) -
The Java EE Architect's Handbook, 2/e: How to be a successful application architect for Java EE applications (Paperback)$1,400$1,330 -
$1,680An Introduction to Statistical Learning: With Applications in R (Hardcover) -
Write Modern Web Apps with the MEAN Stack: Mongo, Express, AngularJS, and Node.js (Paperback)$1,250$1,225 -
$800Python Data Analysis (Paperback) -
精實開發與看板方法$550$435 -
Storm Applied: Strategies for real-time event processing (Paperback)$1,650$1,568 -
Java SE 8 懶人包 (Java SE 8 for the Really Impatient)$360$281 -
完整學會 Git, GitHub, Git Server 的24堂課$360$284 -
Beginning Big Data with Power BI and Excel 2013: Big Data Processing and Analysis Using PowerBI in Excel 2013 (Paperback)$1,670$1,587 -
$352實用機器學習 (Real-world Machine Learning)
商品描述
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)
服務如社交網絡、網頁分析和智能電子商務通常需要管理超出傳統資料庫規模的數據。隨著規模和需求的增加,複雜性也隨之上升。幸運的是,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,而不是使用一些流行的技術。大數據系統使用多台機器並行工作來存儲和處理數據,這引入了對大多數開發者來說不熟悉的基本挑戰。
《Big Data》展示了如何使用一種架構來構建這些系統,該架構利用了集群硬體以及專門設計用於捕獲和分析網頁規模數據的新工具。它描述了一種可擴展、易於理解的大數據系統方法,這些系統可以由小型團隊構建和運行。通過一個現實的例子,本書指導讀者了解大數據系統的理論、如何在實踐中使用它們,以及一旦構建完成後如何部署和運行它們。
購買印刷版書籍可獲得Manning提供的免費PDF、ePub和Kindle電子書的優惠。此外,書中的所有代碼也可用。
