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Large Scale Data Analytics / by Chung Yik Cho, Rong Kun Jason Tan, John A. Leong, Amandeep S. Sidhu

By: Cho, Chung Yik, autor
Contributor(s): SpringerLink (Online service) | Leong, John A., autor | Sidhu, Amandeep S., autor | Tan, Rong Kun Jason., autor
Series: (Data Semantics and Cloud Computing, 2524-6593; 806); (Engineering (Springer-11647)).Publisher: Cham : Springer International Publishing : Imprint: Springer, 2019Description: 1 recurso en línea (IX, 89 páginas).ISBN: 9783030038922.Subject: Datos masivos | Informática | Estructuras de datos (Informática)Online resources: Acceso a este recurso digital (usuarios Universidad Europea de Madrid)Digital Resources
Contents:
Introduction -- Background -- Large scale data analytics -- Query framework -- Results and discussion -- Conclusion and future works
Abstract: This book presents a language integrated query framework for big data. The continuous, rapid growth of data information to volumes of up to terabytes (1,024 gigabytes) or petabytes (1,048,576 gigabytes) means that the need for a system to manage and query information from large scale data sources is becoming more urgent. Currently available frameworks and methodologies are limited in terms of efficiency and querying compatibility between data sources due to the differences in information storage structures. For this research, the authors designed and programmed a framework based on the fundamentals of language integrated query to query existing data sources without the process of data restructuring. A web portal for the framework was also built to enable users to query protein data from the Protein Data Bank (PDB) and implement it on Microsoft Azure, a cloud computing environment known for its reliability, vast computing resources and cost-effectiveness
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
LIBRO-E NO PRÉSTAMO LIBRO-E NO PRÉSTAMO Madrid Digital Acceso Electrónico (UEM) Ciencias e Ingeniería QA76.9 .B45 2019 EB (Browse shelf(Opens below)) Acceso electrónico eBooks24062072
Total holds: 0

Introduction -- Background -- Large scale data analytics -- Query framework -- Results and discussion -- Conclusion and future works

This book presents a language integrated query framework for big data. The continuous, rapid growth of data information to volumes of up to terabytes (1,024 gigabytes) or petabytes (1,048,576 gigabytes) means that the need for a system to manage and query information from large scale data sources is becoming more urgent. Currently available frameworks and methodologies are limited in terms of efficiency and querying compatibility between data sources due to the differences in information storage structures. For this research, the authors designed and programmed a framework based on the fundamentals of language integrated query to query existing data sources without the process of data restructuring. A web portal for the framework was also built to enable users to query protein data from the Protein Data Bank (PDB) and implement it on Microsoft Azure, a cloud computing environment known for its reliability, vast computing resources and cost-effectiveness

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