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Data, Semantics and Cloud Computing

Large Scale Data Analytics

Authors: Cho, C.Y., Tan, R.K.J., Leong, J.A., Sidhu, A.S.

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  • Presents large-scale protein data analytics
  • Introduces a language integrated query framework for big data
  • Provides efficient data restructuring of petascale data sources
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About this book

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.

Table of contents (6 chapters)

Table of contents (6 chapters)

Buy this book

eBook $109.00
price for USA in USD
  • ISBN 978-3-030-03892-2
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $149.99
price for USA in USD
  • ISBN 978-3-030-03891-5
  • Free shipping for individuals worldwide
  • Immediate ebook access, if available*, with your print order
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Large Scale Data Analytics
Authors
Series Title
Data, Semantics and Cloud Computing
Series Volume
806
Copyright
2019
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-03892-2
DOI
10.1007/978-3-030-03892-2
Hardcover ISBN
978-3-030-03891-5
Series ISSN
2524-6593
Edition Number
1
Number of Pages
IX, 89
Topics

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