IBM Data Engine for Hadoop and Spark
An IBM Redbooks publication
Published 24 August 2016
IBM Form #: SG24-8359-00
Rate and comment
Authors: Dino Quintero, Luis Bolinches, Aditya Gandakusuma Sutandyo, Nicolas Joly, Reinaldo Tetsuo Katahira
This IBM® Redbooks® publication provides topics to help the technical community take advantage of the resilience, scalability, and performance of the IBM Power Systems™ platform to implement or integrate an IBM Data Engine for Hadoop and Spark solution for analytics solutions to access, manage, and analyze data sets to improve business outcomes.
This book documents topics to demonstrate and take advantage of the analytics strengths of the IBM POWER8® platform, the IBM analytics software portfolio, and selected third-party tools to help solve customer's data analytic workload requirements. This book describes how to plan, prepare, install, integrate, manage, and show how to use the IBM Data Engine for Hadoop and Spark solution to run analytic workloads on IBM POWER8. In addition, this publication delivers documentation to complement available IBM analytics solutions to help your data analytic needs.
This publication strengthens the position of IBM analytics and big data solutions with a well-defined and documented deployment model within an IBM POWER8 virtualized environment so that customers have a planned foundation for security, scaling, capacity, resilience, and optimization for analytics workloads.
This book is targeted at technical professionals (analytics consultants, technical support staff, IT Architects, and IT Specialists) that are responsible for delivering analytics solutions and support on IBM Power Systems.
Related Blog Posts
Table of contents
Chapter 1. Introduction to IBM Data Engine for Hadoop and Spark
Chapter 2. Solution reference architecture
Chapter 3. Use case scenario for the IBM Data Engine for Hadoop and Spark
Chapter 4. Operational guidelines
Chapter 5. Multitenancy
Appendix A. Ordering the solution
Appendix B. Script to clone partitions
Others who read this publication also read
Follow IBM Redbooks
Follow IBM Redbooks