最新大數(shù)據(jù)電子書(shū)：Big Data Analytics Beyond Hadoop: Real-Time Applications with

相似文件 換一批

是 否 +2 論壇幣

k人 參與回答

經(jīng)管之家送您一份

應(yīng)屆畢業(yè)生專(zhuān)屬福利!

求職就業(yè)群

趙安豆老師微信：zhaoandou666

經(jīng)管之家聯(lián)合CDA

送您一個(gè)全額獎(jiǎng)學(xué)金名額~ !

立即領(lǐng)取

感謝您參與論壇問(wèn)題回答

經(jīng)管之家送您兩個(gè)論壇幣！

+2 論壇幣

簡(jiǎn)介

[size=14.399999618530273px]Master alternative Big Data technologies that can do what Hadoop can’t: real-time analytics and iterative machine learning.

[size=14.399999618530273px]When most technical professionals think of Big Data analytics today, they think of Hadoop. But there are many cutting-edge applications that Hadoop isn’t well suited for, especially real-time analytics and contexts requiring the use of iterative machine learning algorithms. Fortunately, several powerful new technologies have been developed specifically for use cases such as these. Big Data Analytics Beyond Hadoop is the first guide specifically designed to help you take the next steps beyond Hadoop. Dr. Vijay Srinivas Agneeswaran introduces the breakthrough Berkeley Data Analysis Stack (BDAS) in detail, including its motivation, design, architecture, Mesos cluster management, performance, and more. He presents realistic use cases and up-to-date example code for:

• Spark, the next generation in-memory computing technology from UC Berkeley
• Storm, the parallel real-time Big Data analytics technology from Twitter
• GraphLab, the next-generation graph processing paradigm from CMU and the University of Washington (with comparisons to alternatives such as Pregel and Piccolo)
  

[size=14.399999618530273px]Halo also offers architectural and design guidance and code sketches for scaling machine learning algorithms to Big Data, and then realizing them in real-time. He concludes by previewing emerging trends, including real-time video analytics, SDNs, and even Big Data governance, security, and privacy issues. He identifies intriguing startups and new research possibilities, including BDAS extensions and cutting-edge model-driven analytics.

[size=14.399999618530273px]Big Data Analytics Beyond Hadoop is an indispensable resource for everyone who wants to reach the cutting edge of Big Data analytics, and stay there: practitioners, architects, programmers, data scientists, researchers, startup entrepreneurs, and advanced students

[size=14.399999618530273px] Big Data Analytics Beyond Hadoop_ Real-Time Applications with Storm, Spark, and .pdf (398.32 KB, 需要: 10 個(gè)論壇幣)

2014-7-27 21:43:15 上傳

需要: 10 個(gè)論壇幣  [購(gòu)買(mǎi)]

掃碼加我 拉你入群

請(qǐng)注明：姓名-公司-職位

以便審核進(jìn)群資格，未注明則拒絕

分享2 收藏6 回帖

關(guān)鍵詞：Applications Application Analytics Real-time Big data 電子書(shū) Beyond

多謝樓主分享

分享啦

多謝樓主分享

貴---，值好得留意一下，感謝樓主的告知，我先研究一下。。。

只有48頁(yè)，也不說(shuō)清楚!欺騙!大家別上當(dāng)！

謝謝分享�。。。。。�！

I really need some practical books

我看靠幾個(gè)論壇幣過(guò)日子的人，不可能做成什么大事�。�！注定的�。�！