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Ibm Data Engine For Hadoop And Spark

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Ibm Data Engine For Hadoop And Spark

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Author : Dino Quintero
language : en
Publisher: IBM Redbooks
Release Date : 2016-08-24

Ibm Data Engine For Hadoop And Spark written by Dino Quintero and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-24 with Computers categories.

This IBM® Redbooks® publication provides topics to help the technical community take advantage of the resilience, scalability, and performance of the IBM Power SystemsTM 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.

Ibm Data Engine For Hadoop And Spark

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Author : Dino Quintero
language : en
Publisher:
Release Date : 2016

Ibm Data Engine For Hadoop And Spark written by Dino Quintero and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Data mining categories.

Ibm Power Systems L And Lc Server Positioning Guide

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Author : Scott Vetter
language : en
Publisher: IBM Redbooks
Release Date : 2017-02-16

Ibm Power Systems L And Lc Server Positioning Guide written by Scott Vetter and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-16 with Computers categories.

This IBM® RedpaperTM publication is written to assist you in locating the optimal server/workload fit within the IBM Power SystemsTM L and IBM OpenPOWER LC product lines. IBM has announced several scale-out servers, and as a partner in the OpenPOWER organization, unique design characteristics that are engineered into the LC line have broadened the suite of available workloads beyond typical client OS hosting. This paper looks at the benefits of the Power Systems L servers and OpenPOWER LC servers, and how they are different, providing unique benefits for Enterprise workloads and use cases.

Bridging Relational And Nosql Databases

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Author : Gaspar, Drazena
language : en
Publisher: IGI Global
Release Date : 2017-11-30

Bridging Relational And Nosql Databases written by Gaspar, Drazena and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-30 with Computers categories.

Relational databases have been predominant for many years and are used throughout various industries. The current system faces challenges related to size and variety of data thus the NoSQL databases emerged. By joining these two database models, there is room for crucial developments in the field of computer science. Bridging Relational and NoSQL Databases is an innovative source of academic content on the convergence process between databases and describes key features of the next database generation. Featuring coverage on a wide variety of topics and perspectives such as BASE approach, CAP theorem, and hybrid and native solutions, this publication is ideally designed for professionals and researchers interested in the features and collaboration of relational and NoSQL databases.

Ibm Software Defined Infrastructure For Big Data Analytics Workloads

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Author : Dino Quintero
language : en
Publisher: IBM Redbooks
Release Date : 2015-06-29

Ibm Software Defined Infrastructure For Big Data Analytics Workloads written by Dino Quintero and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-29 with Computers categories.

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.

Ibm Reference Architecture For Genomics Power Systems Edition

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Author : Dino Quintero
language : en
Publisher: IBM Redbooks
Release Date : 2016-04-05

Ibm Reference Architecture For Genomics Power Systems Edition written by Dino Quintero and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-05 with Computers categories.

This IBM® Redbooks® publication introduces the IBM Reference Architecture for Genomics, IBM Power SystemsTM edition on IBM POWER8®. It addresses topics such as why you would implement Life Sciences workloads on IBM POWER8, and shows how to use such solution to run Life Sciences workloads using IBM PlatformTM Computing software to help set up the workloads. It also provides technical content to introduce the IBM POWER8 clustered solution for Life Sciences workloads. This book customizes and tests Life Sciences workloads with a combination of an IBM Platform Computing software solution stack, Open Stack, and third party applications. All of these applications use IBM POWER8, and IBM Spectrum ScaleTM for a high performance file system. This book helps strengthen IBM Life Sciences solutions on IBM POWER8 with a well-defined and documented deployment model within an IBM Platform Computing and an IBM POWER8 clustered environment. This system provides clients in need of a modular, cost-effective, and robust solution with a planned foundation for future growth. This book highlights IBM POWER8 as a flexible infrastructure for clients looking to deploy life sciences workloads, and at the same time reduce capital expenditures, operational expenditures, and optimization of resources. This book helps answer clients' workload challenges in particular with Life Sciences applications, and provides expert-level documentation and how-to-skills to worldwide teams that provide Life Sciences solutions and support to give a broad understanding of a new architecture.

Big Data Management And Processing

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Author : Kuan-Ching Li
language : en
Publisher: CRC Press
Release Date : 2017-05-19

Big Data Management And Processing written by Kuan-Ching Li and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-19 with Business & Economics categories.

From the Foreword: "Big Data Management and Processing is [a] state-of-the-art book that deals with a wide range of topical themes in the field of Big Data. The book, which probes many issues related to this exciting and rapidly growing field, covers processing, management, analytics, and applications... [It] is a very valuable addition to the literature. It will serve as a source of up-to-date research in this continuously developing area. The book also provides an opportunity for researchers to explore the use of advanced computing technologies and their impact on enhancing our capabilities to conduct more sophisticated studies." ---Sartaj Sahni, University of Florida, USA "Big Data Management and Processing covers the latest Big Data research results in processing, analytics, management and applications. Both fundamental insights and representative applications are provided. This book is a timely and valuable resource for students, researchers and seasoned practitioners in Big Data fields. --Hai Jin, Huazhong University of Science and Technology, China Big Data Management and Processing explores a range of big data related issues and their impact on the design of new computing systems. The twenty-one chapters were carefully selected and feature contributions from several outstanding researchers. The book endeavors to strike a balance between theoretical and practical coverage of innovative problem solving techniques for a range of platforms. It serves as a repository of paradigms, technologies, and applications that target different facets of big data computing systems. The first part of the book explores energy and resource management issues, as well as legal compliance and quality management for Big Data. It covers In-Memory computing and In-Memory data grids, as well as co-scheduling for high performance computing applications. The second part of the book includes comprehensive coverage of Hadoop and Spark, along with security, privacy, and trust challenges and solutions. The latter part of the book covers mining and clustering in Big Data, and includes applications in genomics, hospital big data processing, and vehicular cloud computing. The book also analyzes funding for Big Data projects.

Ibm Platform Computing Solutions For High Performance And Technical Computing Workloads

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Author : Dino Quintero
language : en
Publisher: IBM Redbooks
Release Date : 2015-06-19

Ibm Platform Computing Solutions For High Performance And Technical Computing Workloads written by Dino Quintero and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-19 with Computers categories.

This IBM® Redbooks® publication is a refresh of IBM Technical Computing Clouds, SG24-8144, Enhance Inbound and Outbound Marketing with a Trusted Single View of the Customer, SG24-8173, and IBM Platform Computing Integration Solutions, SG24-8081, with a focus on High Performance and Technical Computing on IBM Power SystemsTM. This book describes synergies across the IBM product portfolio by using case scenarios and showing solutions such as IBM SpectrumTM Scale (formerly GPFSTM). This book also reflects and documents the IBM Platform Computing Cloud Services as part of IBM Platform Symphony® for analytics workloads and IBM Platform LSF® (with new features, such as a Hadoop connector, a MapReduce accelerator, and dynamic cluster) for job scheduling. Both products are used to help customers schedule and analyze large amounts of data for business productivity and competitive advantages. This book is targeted at technical professionals (consultants, technical support staff, IT Architects, and IT Specialists) that are responsible for delivering cost-effective cloud services and big data solutions on IBM Power Systems to uncover insights among client data so that they can take actions to optimize business results, product development, and scientific discoveries.

Data Analytics For Pandemics

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Author : Gitanjali Rahul Shinde
language : en
Publisher: CRC Press
Release Date : 2020-08-30

Data Analytics For Pandemics written by Gitanjali Rahul Shinde and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-30 with Computers categories.

Epidemic trend analysis, timeline progression, prediction, and recommendation are critical for initiating effective public health control strategies, and AI and data analytics play an important role in epidemiology, diagnostic, and clinical fronts. The focus of this book is data analytics for COVID-19, which includes an overview of COVID-19 in terms of epidemic/pandemic, data processing and knowledge extraction. Data sources, storage and platforms are discussed along with discussions on data models, their performance, different big data techniques, tools and technologies. This book also addresses the challenges in applying analytics to pandemic scenarios, case studies and control strategies. Aimed at Data Analysts, Epidemiologists and associated researchers, this book: discusses challenges of AI model for big data analytics in pandemic scenarios; explains how different big data analytics techniques can be implemented; provides a set of recommendations to minimize infection rate of COVID-19; summarizes various techniques of data processing and knowledge extraction; enables users to understand big data analytics techniques required for prediction purposes.

Big Data 2 0 Processing Systems

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Author : Sherif Sakr
language : en
Publisher: Springer Nature
Release Date : 2020-07-09

Big Data 2 0 Processing Systems written by Sherif Sakr and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-09 with Computers categories.

This book provides readers the “big picture” and a comprehensive survey of the domain of big data processing systems. For the past decade, the Hadoop framework has dominated the world of big data processing, yet recently academia and industry have started to recognize its limitations in several application domains and thus, it is now gradually being replaced by a collection of engines that are dedicated to specific verticals (e.g. structured data, graph data, and streaming data). The book explores this new wave of systems, which it refers to as Big Data 2.0 processing systems. After Chapter 1 presents the general background of the big data phenomena, Chapter 2 provides an overview of various general-purpose big data processing systems that allow their users to develop various big data processing jobs for different application domains. In turn, Chapter 3 examines various systems that have been introduced to support the SQL flavor on top of the Hadoop infrastructure and provide competing and scalable performance in the processing of large-scale structured data. Chapter 4 discusses several systems that have been designed to tackle the problem of large-scale graph processing, while the main focus of Chapter 5 is on several systems that have been designed to provide scalable solutions for processing big data streams, and on other sets of systems that have been introduced to support the development of data pipelines between various types of big data processing jobs and systems. Next, Chapter 6 focuses on covering the emerging frameworks and systems in the domain of scalable machine learning and deep learning processing. Lastly, Chapter 7 shares conclusions and an outlook on future research challenges. This new and considerably enlarged second edition not only contains the completely new chapter 6, but also offers a refreshed content for the state-of-the-art in all domains of big data processing over the last years. Overall, the book offers a valuable reference guide for professional, students, and researchers in the domain of big data processing systems. Further, its comprehensive content will hopefully encourage readers to pursue further research on the subject.

Ibm Data Engine For Hadoop And Spark

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