Implementing IBM InfoSphere BigInsights on IBM System x

An IBM Redbooks publication

Published 12 June 2013

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ISBN-10: 0738438286
ISBN-13: 9780738438283
IBM Form #: SG24-8077-01
(224 pages)

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Authors: Mike Ebbers, Renata Ghisloti de Souza, Marcelo Correia Lima, Peter McCullagh, Michael Nobles, Dustin VanStee, Brandon Waters

Abstract

As world activities become more integrated, the rate of data growth has been increasing exponentially. And as a result of this data explosion, current data management methods can become inadequate. People are using the term big data (sometimes referred to as Big Data) to describe this latest industry trend. IBM® is preparing the next generation of technology to meet these data management challenges.

To provide the capability of incorporating big data sources and analytics of these sources, IBM developed a stream-computing product that is based on the open source computing framework Apache Hadoop. Each product in the framework provides unique capabilities to the data management environment, and further enhances the value of your data warehouse investment.

In this IBM Redbooks® publication, we describe the need for big data in an organization. We then introduce IBM InfoSphere® BigInsights™ and explain how it differs from standard Hadoop. BigInsights provides a packaged Hadoop distribution, a greatly simplified installation of Hadoop and corresponding open source tools for application development, data movement, and cluster management. BigInsights also brings more options for data security, and as a component of the IBM big data platform, it provides potential integration points with the other components of the platform.

A new chapter has been added to this edition. Chapter 11 describes IBM Platform Symphony®, which is a new scheduling product that works with IBM Insights, bringing low-latency scheduling and multi-tenancy to IBM InfoSphere BigInsights.

The book is designed for clients, consultants, and other technical professionals.

Table of contents

Chapter 1. A whole new world of big data
Chapter 2. Why choose BigInsights
Chapter 3. BigInsights network architecture
Chapter 4. BigInsights hardware architecture
Chapter 5. Operating system prerequisites for BigInsights
Chapter 6. BigInsights installation
Chapter 7. Cluster validation
Chapter 8. BigInsights capabilities
Chapter 9. BigInsights hardware monitoring and alerting
Chapter 10. BigInsights security design
Chapter 11. IBM Platform Symphony
Appendix A. M4 reference architecture
Appendix B. Installation values
Appendix C. Checklist

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