书目名称 | Large Scale Data Analytics |
编辑 | Chung Yik Cho,Rong Kun Jason Tan,Amandeep S. Sidhu |
视频video | |
概述 | Presents large-scale protein data analytics.Introduces a language integrated query framework for big data.Provides efficient data restructuring of petascale data sources |
丛书名称 | Studies in Computational Intelligence |
图书封面 |  |
描述 | 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. |
出版日期 | Book 2019 |
关键词 | Biomedicine; Big Data; Computational Intelligence; Data Analytics; Language Integrated Queries |
版次 | 1 |
doi | https://doi.org/10.1007/978-3-030-03892-2 |
isbn_ebook | 978-3-030-03892-2Series ISSN 1860-949X Series E-ISSN 1860-9503 |
issn_series | 1860-949X |
copyright | Springer Nature Switzerland AG 2019 |