Virtualizing Hadoop: How to Install, Deploy, and Optimize Hadoop in a Virtualized Architecture

Preface

A key objective around Hadoop and big data is being able to get insight faster with a higher degree of accuracy with less risk. Business, government, schools, and science are all looking at leveraging data-driven decisions around big data and fast data. Organizations are also looking at ways to reduce the cost of working with data as well as how to improve the efficiency for processing data. This requires a platform that can rapidly provision new clusters for development, testing, and proof of concept or proof of value projects. A platform running Hadoop must have the agility and flexibility to absorb the rapid changes of the ecosystems around big data, the changing rates and volumes of evolving applications, and the evolving frameworks ...