IBM software defined infrastructure for big data analytics workloads

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 Had...

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Detalles Bibliográficos
Autor Corporativo: International Business Machines Corporation. International Technical Support Organization (-)
Otros Autores: Quintero, Dino, author (author), De Souza Casali, Daniel, author, Lima, Marcelo Correia, author, Szabo, Istvan Gabor, author, Olejniczak, Maciej, author, Rodrigues de Mello, Tiago, author, Carlos dos Santos, Nilton, author
Formato: Libro electrónico
Idioma:Inglés
Publicado: Poughkeepsie, NY : IBM Corporation, International Technical Support Organization 2015.
Edición:First edition
Colección:IBM redbooks.
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009629567206719
Descripción
Sumario: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.
Notas:Number from resource description page: SG24-8234-00.
Descripción Física:1 online resource (1 volume) : illustrations
ISBN:9780738440774