IBM Software Defined Infrastructure for Big Data Analytics Workloads

An IBM Redbooks publication

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Published on 29 June 2015

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ISBN-10: 0738440779
ISBN-13: 9780738440774
IBM Form #: SG24-8265-00


Authors: Dino Quintero, Daniel de Souza Casali, Marcelo Correia Lima, Istvan Gabor Szabo, Maciej Olejniczak, Tiago Rodrigues de Mello and Nilton Carlos dos Santos

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    Abstract

    This IBM® Redbooks® publication documents how IBM Platform Computing, with its IBM Platform Symphony® MapReduce framework, IBM Spectrum Scale (based Upon IBM GPFS™), IBM Platform LSF®, the Advanced Service Controller for Platform Symphony are work together as an infrastructure to manage not just Hadoop-related offerings, but many popular industry offeringsm such as Apach Spark, Storm, MongoDB, Cassandra, and so on.

    It describes the different ways to run Hadoop in a big data environment, and demonstrates how IBM Platform Computing solutions, such as Platform Symphony and Platform LSF with its MapReduce Accelerator, can help performance and agility to run Hadoop on distributed workload managers offered by IBM. This information is for technical professionals (consultants, technical support staff, IT architects, and IT specialists) who are responsible for delivering cost-effective cloud services and big data solutions on IBM Power Systems™ to help uncover insights among client’s data so they can optimize product development and business results.

    Table of Contents

    Chapter 1. Introduction to big data

    Chapter 2. Big data, analytics, and risk calculation software portfolio

    Chapter 3. IBM Platform Symphony with Application Service Controller

    Chapter 4. Mixed IBM Power Systems and Intel environment for big data

    Chapter 5. IBM Spectrum Scale for big data environments

    Chapter 6. IBM Application Service Controller in a mixed environment

    Chapter 7. IBM Platform Computing cloud services

     

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