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Big Data Made Easy - A Working Guide to the Complete Hadoop Toolset (Paperback, 1st ed.): Michael Frampton Big Data Made Easy - A Working Guide to the Complete Hadoop Toolset (Paperback, 1st ed.)
Michael Frampton
R2,418 Discovery Miles 24 180 Ships in 18 - 22 working days

Many corporations are finding that the size of their data sets are outgrowing the capability of their systems to store and process them. The data is becoming too big to manage and use with traditional tools. The solution: implementing a big data system. As Big Data Made Easy: A Working Guide to the Complete Hadoop Toolset shows, Apache Hadoop offers a scalable, fault-tolerant system for storing and processing data in parallel. It has a very rich toolset that allows for storage (Hadoop), configuration (YARN and ZooKeeper), collection (Nutch and Solr), processing (Storm, Pig, and Map Reduce), scheduling (Oozie), moving (Sqoop and Avro), monitoring (Chukwa, Ambari, and Hue), testing (Big Top), and analysis (Hive). The problem is that the Internet offers IT pros wading into big data many versions of the truth and some outright falsehoods born of ignorance. What is needed is a book just like this one: a wide-ranging but easily understood set of instructions to explain where to get Hadoop tools, what they can do, how to install them, how to configure them, how to integrate them, and how to use them successfully. And you need an expert who has worked in this area for a decade-someone just like author and big data expert Mike Frampton. Big Data Made Easy approaches the problem of managing massive data sets from a systems perspective, and it explains the roles for each project (like architect and tester, for example) and shows how the Hadoop toolset can be used at each system stage. It explains, in an easily understood manner and through numerous examples, how to use each tool. The book also explains the sliding scale of tools available depending upon data size and when and how to use them. Big Data Made Easy shows developers and architects, as well as testers and project managers, how to: Store big data Configure big data Process big data Schedule processes Move data among SQL and NoSQL systems Monitor data Perform big data analytics Report on big data processes and projects Test big data systems Big Data Made Easy also explains the best part, which is that this toolset is free. Anyone can download it and-with the help of this book-start to use it within a day. With the skills this book will teach you under your belt, you will add value to your company or client immediately, not to mention your career.

Complete Guide to Open Source Big Data Stack (Paperback, 1st ed.): Michael Frampton Complete Guide to Open Source Big Data Stack (Paperback, 1st ed.)
Michael Frampton
R1,140 R968 Discovery Miles 9 680 Save R172 (15%) Ships in 18 - 22 working days

See a Mesos-based big data stack created and the components used. You will use currently available Apache full and incubating systems. The components are introduced by example and you learn how they work together. In the Complete Guide to Open Source Big Data Stack, the author begins by creating a private cloud and then installs and examines Apache Brooklyn. After that, he uses each chapter to introduce one piece of the big data stack-sharing how to source the software and how to install it. You learn by simple example, step by step and chapter by chapter, as a real big data stack is created. The book concentrates on Apache-based systems and shares detailed examples of cloud storage, release management, resource management, processing, queuing, frameworks, data visualization, and more. What You'll Learn Install a private cloud onto the local cluster using Apache cloud stack Source, install, and configure Apache: Brooklyn, Mesos, Kafka, and Zeppelin See how Brooklyn can be used to install Mule ESB on a cluster and Cassandra in the cloud Install and use DCOS for big data processing Use Apache Spark for big data stack data processing Who This Book Is For Developers, architects, IT project managers, database administrators, and others charged with developing or supporting a big data system. It is also for anyone interested in Hadoop or big data, and those experiencing problems with data size.

Embodiments of Will (Paperback): Michael Frampton Embodiments of Will (Paperback)
Michael Frampton
R1,954 Discovery Miles 19 540 Ships in 18 - 22 working days

This book examines the two chief anatomical and physiological embodi ment theories of voluntary animal motion, which I call the cardiosinew and cerebroneuromuscular theories of motion, from the time of Aristotle (384-322 B.C.) to that of Mondino (d. A.D. 1326). The study of animal motion commenced with the ancient Greek natural scientist Aristotle who wrote the monograph 'On the motion of animals' (De motu animalium). Subsequent inquiries into voluntary animal motion may be found in a variety of Greek, Latin, and Arabic compendia, commentaries, and encyclopedias throughout the ancient and medieval periods. The motion of animals was considered relevant to natural philosophers and theologians investigating the nature of the soul, and to physicians seeking to discover the causes of disorders of voluntary movement such as epilepsy and tetany. The book fills a gap in the scholarly literature concerned with pre-modern studies of the anatomical and physiological mechanisms of will and bodily movement. The accompanying photographs of my own anatomical dissections illuminate ancient and medieval conceptual, empirical, and experimental methods of anatomical and physiological research.

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