This book is a concise guide to getting started with Hadoop and getting the most out of your Hadoop clusters. My early experiences with Hadoop were wonderful and stressful. While Hadoop supplied the tools to scale applications, it lacked documentati
书名：Pro Hadoop 语言：英文 This book is a concise guide to getting started with Hadoop and getting the most out of your Hadoop clusters. My early experiences with Hadoop were wonderful and stressful. While Hadoop supplied the tools to scale applications, i
书名：Hadoop The Definitive Guide 语言：英文 The rest of this book is organized as follows. Chapter 2 provides an introduction to MapReduce. Chapter 3 looks at Hadoop filesystems, and in particular HDFS, in depth. Chapter 4 covers the fundamentals of I/O in
原书地址： http://www.amazon.com/Hadoop-Definitive-Guide-Tom-White/dp/0596521979/ This book helps you: Use the Hadoop Distributed File System (HDFS) for storing large datasets, and run distributed computations over those datasets using MapReduce Become f
Hadoop: The Definitive Guide 1. Meet Hadoop 2. MapReduce 3. The Hadoop Distributed Filesystem 4. Hadoop I/O 5. Developing a MapReduce Application 6. How MapReduce Works 7. MapReduce Types and Formats 8. MapReduce Features 9. Setting Up a Hadoop Clus
In many ways, this is how I feel about Hadoop. Its inner workings are complex, resting as they do on a mixture of distributed systems theory, practical engineering, and com- mon sense. And to the uninitiated, Hadoop can appear alien. But it doesn’t
What you’ll learn * Set up a stand–alone Hadoop cluster the smart way, laid out simply and step by step so you can get up and running quickly to build your next data center, collaborative, data–intensive Internet services application, Software as a
Chapter 1 Getting Started with Hadoop Core Chapter 2 The Basics of a MapReduce Job Chapter 3 The Basics of Multimachine Clusters Chapter 4 HDFS Details for Multimachine Clusters Chapter 5 MapReduce Details for Multimachine Clusters Chapter 6 Tuning
利用JPA做“公共黑板”，解决了数据挖掘中hadoop的子任务无法共享数据的问题，提出了树型结构的高效算法。具体实现了kdtree的hadoop版本。 代码可以在http://svn.javaforge.com/svn/hadoopjpa/HadoopDataMining check out. 需要先注册；如果不能成功，换小写地址。 下面是ris格式的引文，存盘后可为endnote等文献管理软件导入。 TY - CHAP AU - Lai, Yang AU - ZhongZhi, Shi A2
"Hadoop in Action" teaches readers how to use Hadoop and write MapReduce programs. The intended readers are programmers, architects, and project managers who have to process large amounts of data offline. "Hadoop in Action" will lead the reader from
This book is a concise guide to getting started with Hadoop and getting the most out of your Hadoop clusters. My early experiences with Hadoop were wonderful and stressful.
this book is a concise guide to getting started with Hadoop and getting the most out of your Hadoop clusters. My early experiences with Hadoop were wonderful and stressful. While Hadoop supplied the tools to scale applications, it lacked documentati
Hadoop is quite a fascinating and interesting project that has seen quite a lot of interest and contributions from the various organizations and institutions. Hadoop has come a long way, from being a batch processing system to a data lake and high-v
Practical Hadoop Migration: How to Integrate Your RDBMS with the Hadoop Ecosystem and Re-Architect Relational Applications to NoSQL Re-architect relational applications to NoSQL, integrate relational database management systems with the Hadoop ecosy
In Expert Hadoop® Administration, leading Hadoop administrator Sam R. Alapati brings together authoritative knowledge for creating, configuring, securing, managing, and optimizing production Hadoop clusters in any environment. Drawing on his experie
In Expert Hadoop® Administration, leading Hadoop administrator Sam R. Alapati brings together authoritative knowledge for creating, configuring, securing, managing, and optimizing production Hadoop clusters in any environment. Drawing on his experie
In Expert Hadoop® Administration, leading Hadoop administrator Sam R. Alapati brings together authoritative knowledge for creating, configuring, securing, managing, and optimizing production Hadoop cl usters in any environment. Drawing on his experi
