电子书:《Druid实时大数据分析 原理与实践》

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《Druid实时大数据分析 原理与实践》_2

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内容简介:

小米商业产品部研发总监,负责广告
架构和数据分析平台,擅长数据挖掘,大
数据分析和广告搜索架构。之前,在微软
工作10年,任微软公司高级开发经理
负责 Contextual Ads产品研发,开发
Bing Index Serve的核心模块。持有多
项关于互联网广告及搜索的美guo专利。创
办“互联居”公众号,致力于互联网
告技术的繁荣。毕业于北京大学计算机
系,获硕士学历
刘麒赟
现任 Testin?云测公司技术总监,全面
负责领导团队完成数据分析产品的研发。
作为资深数据技术专家,曾为多个著名开
源项目( Hadoop/ Scoop/ Oozie/
Druid)贡献源代码,在互联网大数据分
析、机器学习和统计学应用等方面拥有丰
富的实战经验和相关专利。在企业级产品
研发和客户支持方面也有着丰富的经验
并曾为中guo多地(包括香港和台湾地区)
的龙头企业成功进行实地支持,为美guo与
新加坡等地客户进行.远.程.支持。之前,曾
任 OneAPM公司大数据架构师,以及在
BM公司工作七年并任BM全球大数据平
台产品 BigInsights的 Advisory Software
Engineer

Druid
实时大数据分析
原理与实践
欧阳辰刘麒赟张海雷高振源许哲著
電子工業出版社
Publishing House of Electronics Industr
北京 BELJINg

内容简介
Druid作为一款开源的实时大数据分析软件,最近几年快速风靡全球互联网公司,特别
是对于海量数据和实时性要求高的场景,包括广告数据分析、用户行为分析、数据统计分析
维监控分析等,在腾 讯、_阿.里_、优酷、小米等公司都有大量成功应用的案例。本书的目的
就是帮助技术人员更好地深入理解 Druid技术、大数据分析技术选型、 Druid的安装和使用
高级特性的使用,也包括一些源代码的解析,以及一些常见问题的快速回答
Drud的生态系统正在不断扩大和成熟, Druid也正在解决越来越多的业务场景。希望
本书能帮助技术人员做出更好的技术选型,深度了解Duid的功能和原理,更好地解决大数
据分析问题。本书适合大数据分析的从业人员、IT人员、互联网从业者阅读。
未经许可,不得以任何方式复制或抄袭本书之部分或全部内容
版权所有,侵权必究
图书在版编目(CIP)数
Druid实时大数据分析原理与实践/欧阳辰等著.一北京:电子工业出版社,20173
ISBN978-7-121-30623-5
1.①D…Ⅱ.①欧…Ⅲ.①数据处理ⅣV①TP274
中guo版本图书馆CIP数据核字(2016)第304239号
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责任编辑:葛娜
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出版发行:电子工业出版社
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开本:787×98016印张:22字数:478千字
版次:2017年3月第1版
印次:2017年3月第1次印刷
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Foreword
Like many popular open source projects, Druid was initially created to solve a problem. We were
trying to build an interactive analytics UI at a small advertising technology startup in San Francisco,
and struggled to find a technology that could rapidly aggregate, slice and dice, and drill down into
massive data sets. Eric Tschetter started the first lines of Druid to tackle this challenge, and that work
has somehow led to an international community forming around the project.
I joined Eric on Druid soon after the project started, and for a while, the Druid world consisted
of only 2 engineers. The first version of Druid was extremely minimalistic; there was a single process
type, the\"compute\"node, and a handful of queries, but the core that was there was just enough to
olve the problems with scale and performance we had at that time
Our Druid cluster in the early yea
aggressively develop features and fix bugs. There were a lot of late nights in those days. I can still
clearly re.C.A.L.L. waking up in the middle of the night to fix an outage, and occasionally cursing loudly
because the only reason the pager went off was because it was out of batteries.
As Druid matured, and as data volumes grew, we continued to face challenges around perfo
mance at scale and operational stability. Running in the then notoriously finicky Amazon Web Ser
vices cloud environment wasn't always easy, and led us to make the decision to break up\"compute
nodes into different components so that individual components could be fine tuned at scale, and any
one component could fail without impacting the functionality of the other components. I am glad
we made those decisions because it led us to sleep much more at night
It has been extremely rewarding to watch the grassroots growth of the open source community
Unlike other popular open source projects, Druid was not developed at a major technology company
or famous research lab. We open sourced the project without much attention, and the first open source
version of the project almost didn't have querying capabilities. We weren't allowed to open source

Foreword
many pieces of the codebase, including most of the queries we developed. The night before officially
announced the project, Eric was up writing Group By queries in a hotel room just so people could
have a way of getting data out of Druid. After we released Druid, the code repository was completely
undocumented and barely functional. I don' t think a single organization tried to use Druid when it
ras first open sourced
I've long lost count of how many companies actually run Druid in production today, but I am
glad people have found value from our work. I was very excited to learn that Qiyun Liu was writing a
book on Druid. I hope through his book, you will learn much more about our project, and learn how
leverage it to bring value to your organization.
Co-Founder, Druid
Co-Founder and CEO, Imply
San francisco, California
016.11.20


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