Sinopsis
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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De la contraportada
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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Large Scale Data Analytics.
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Cham, Springer., 2019
ISBN 10: 3030038912
ISBN 13: 9783030038915
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ix, 89 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Sprache: Englisch. Nº de ref. del artículo: 8730EB
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Large Scale Data Analytics
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Springer International Publishing Jan 2019, 2019
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 100 pp. Englisch. Nº de ref. del artículo: 9783030038915
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Large Scale Data Analytics
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Springer International Publishing, 2019
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Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents large-scale protein data analyticsIntroduces a language integrated query framework for big dataProvides efficient data restructuring of petascale data sourcesThis book presents a language integrated query framework for big . Nº de ref. del artículo: 256090879
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Large Scale Data Analytics (Studies in Computational Intelligence, 806)
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Large Scale Data Analytics (Studies in Computational Intelligence, 806)
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Large Scale Data Analytics (Studies in Computational Intelligence, 806)
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Large Scale Data Analytics
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Springer Nature Switzerland, 2019
ISBN 10: 3030038912
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Buch. Condición: Neu. Large Scale Data Analytics | Chung Yik Cho (u. a.) | Buch | ix | Englisch | 2019 | Springer Nature Switzerland | EAN 9783030038915 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Nº de ref. del artículo: 114730819
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Large Scale Data Analytics
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Springer International Publishing, Springer Nature Switzerland Jan 2019, 2019
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Buch. Condición: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 100 pp. Englisch. Nº de ref. del artículo: 9783030038915
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Large Scale Data Analytics
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Springer International Publishing, 2019
ISBN 10: 3030038912
ISBN 13: 9783030038915
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Nº de ref. del artículo: 9783030038915
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