IBM Software Defined Infrastructure for Big Data Analytics Workloads

IBM Software Defined Infrastructure for Big Data Analytics Workloads

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

Date de publication : 2015-06-29

Éditeur : IBM Redbooks

Nombre de pages : 178

Résumé du livre

This IBM® Redbooks® publication documents how IBM Platform Computing, with its IBM Platform Symphony® MapReduce framework, IBM Spectrum Scale (based Upon IBM GPFSTM), 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 SystemsTM to help uncover insights among client’s data so they can optimize product development and business results.

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