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  • Book
  • © 2019

Large Scale Data Analytics

Authors:

  1. Chung Yik Cho

    1. Curtin Malaysia Research Institute, Curtin University, Miri, Malaysia

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  2. Rong Kun Jason Tan

    1. Curtin Malaysia Research Institute, Curtin University, Miri, Malaysia

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  3. John A. Leong

    1. Curtin Malaysia Research Institute, Curtin University, Miri, Malaysia

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  4. Amandeep S. Sidhu

    1. Biological Mapping Research Institute, Perth, Australia

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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

Part of the book series: Studies in Computational Intelligence (SCI, volume 806)

Part of the book sub series: Data, Semantics and Cloud Computing (DSCC)

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Table of contents (6 chapters)

  1. Front Matter

    Pages i-ix
    PDF

  2. Introduction

    • Chung Yik Cho, Rong Kun Jason Tan, John A. Leong, Amandeep S. Sidhu
    Pages 1-4

  3. Background

    • Chung Yik Cho, Rong Kun Jason Tan, John A. Leong, Amandeep S. Sidhu
    Pages 5-18

  4. Large Scale Data Analytics

    • Chung Yik Cho, Rong Kun Jason Tan, John A. Leong, Amandeep S. Sidhu
    Pages 19-25

  5. Query Framework

    • Chung Yik Cho, Rong Kun Jason Tan, John A. Leong, Amandeep S. Sidhu
    Pages 27-45

  6. Results and Discussion

    • Chung Yik Cho, Rong Kun Jason Tan, John A. Leong, Amandeep S. Sidhu
    Pages 47-50

  7. Conclusion and Future Works

    • Chung Yik Cho, Rong Kun Jason Tan, John A. Leong, Amandeep S. Sidhu
    Pages 51-52

  8. Back Matter

    Pages 53-89
    PDF
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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.
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Keywords

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Authors and Affiliations

  • Curtin Malaysia Research Institute, Curtin University, Miri, Malaysia

    Chung Yik Cho, Rong Kun Jason Tan, John A. Leong

  • Biological Mapping Research Institute, Perth, Australia

    Amandeep S. Sidhu

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Bibliographic Information

  • Book Title: Large Scale Data Analytics

  • Authors: Chung Yik Cho, Rong Kun Jason Tan, John A. Leong, Amandeep S. Sidhu

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-030-03892-2

  • Publisher: Springer Cham

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer Nature Switzerland AG 2019

  • Hardcover ISBN: 978-3-030-03891-5Published: 25 January 2019

  • eBook ISBN: 978-3-030-03892-2Published: 09 January 2019

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: IX, 89

  • Topics: Mathematical and Computational Engineering

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Buy it now

eBook USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

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