IBM Software Defined Infrastructure for Big Data Analytics Workloads

IBM Software Defined Infrastructure for Big Data Analytics Workloads

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This IBMAr RedbooksAr publication documents how IBM Platform Computing, with its IBM Platform SymphonyAr MapReduce framework, IBM Spectrum Scale (based Upon IBM GPFSTM), IBM Platform LSFAr, 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.7.1. IBM. Platform. Computing. cloud. services. Engineering, scientific, financial, or research workloads are not the only demanding workloads for technical and high-performance computing (HPC) infrastructures. Big data problems are solved anbsp;...

Title:IBM Software Defined Infrastructure for Big Data Analytics Workloads
Author: Dino Quintero, Daniel de Souza Casali, Marcelo Correia Lima, Istvan Gabor Szabo, Maciej Olejniczak, Tiago Rodrigues de Mello, Nilton Carlos dos Santos, IBM Redbooks
Publisher:IBM Redbooks - 2015-06-29

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