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Titlebook: High-Performance Big-Data Analytics; Computing Systems an Pethuru Raj,Anupama Raman,Siddhartha Duggirala Book 2015 Springer International P

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發(fā)表于 2025-3-21 18:18:24 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱High-Performance Big-Data Analytics
副標(biāo)題Computing Systems an
編輯Pethuru Raj,Anupama Raman,Siddhartha Duggirala
視頻videohttp://file.papertrans.cn/427/426641/426641.mp4
概述Vividly illustrates the benefits of using high-performance infrastructures for next-generation data analytics.Provides numerous and varied case studies and examples of best practice.Includes learning
叢書(shū)名稱Computer Communications and Networks
圖書(shū)封面Titlebook: High-Performance Big-Data Analytics; Computing Systems an Pethuru Raj,Anupama Raman,Siddhartha Duggirala Book 2015 Springer International P
描述This book presents a detailed review of high-performance computing infrastructures for next-generation big data and fast data analytics. Features: includes case studies and learning activities throughout the book and self-study exercises in every chapter; presents detailed case studies on social media analytics for intelligent businesses and on big data analytics (BDA) in the healthcare sector; describes the network infrastructure requirements for effective transfer of big data, and the storage infrastructure. .requirements of applications which generate big data; examines real-time analytics solutions; introduces in-database processing and in-memory analytics techniques for data mining; discusses the use of mainframes for handling real-time big data and the latest types of data management systems for BDA; provides information on the use of cluster, grid and cloud computing systems for BDA; reviews the peer-to-peer techniques and tools and the common information visualization techniques, used in BDA.
出版日期Book 2015
關(guān)鍵詞Big Data Analytics; Hadoop Distributed File System (HDFS); Hadoop Software Framework; Internet of Thing
版次1
doihttps://doi.org/10.1007/978-3-319-20744-5
isbn_softcover978-3-319-36324-0
isbn_ebook978-3-319-20744-5Series ISSN 1617-7975 Series E-ISSN 2197-8433
issn_series 1617-7975
copyrightSpringer International Publishing Switzerland 2015
The information of publication is updating

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沙發(fā)
發(fā)表于 2025-3-21 21:08:41 | 只看該作者
板凳
發(fā)表于 2025-3-22 04:13:10 | 只看該作者
1617-7975 ase studies and examples of best practice.Includes learning This book presents a detailed review of high-performance computing infrastructures for next-generation big data and fast data analytics. Features: includes case studies and learning activities throughout the book and self-study exercises in
地板
發(fā)表于 2025-3-22 05:48:52 | 只看該作者
In-Database Processing and In-Memory Analytics,rocessing to the data is the principle advocated by in-database processing, while the in memory focuses on keeping the data completely in memory to increase the processing speed. In this chapter, we will learn and analyze these two and study some use case to improve our understanding.
5#
發(fā)表于 2025-3-22 11:53:56 | 只看該作者
High-Performance Grids and Clusters,rids is vastly different. The clusters are generally employed with the locally interconnected systems, whereas grids are employed at a much wider and distributed scale. In this chapter we will learn more about these two interconnected paradigms and study some use cases.
6#
發(fā)表于 2025-3-22 13:34:40 | 只看該作者
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8#
發(fā)表于 2025-3-22 22:56:02 | 只看該作者
High-Performance Computing (HPC) Paradigms, extinct but have surprised the business on how it has evolved with better capabilities to handle real-time data and the so-called big data. This chapter covers all interesting solutions on how mainframe can still be used to provide better client solutions.
9#
發(fā)表于 2025-3-23 03:51:01 | 只看該作者
High-Performance Peer-to-Peer Systems,jor theme for high-performance computing. With goals of dynamism, ad hoc collaboration, and cost sharing, these platforms show the following distinguishing traits: decentralization, highly scalability, and low cost of ownership. In this chapter, we learn about the design goals and principles and various commercial and scientific systems available.
10#
發(fā)表于 2025-3-23 08:38:05 | 只看該作者
Big Data Analytics for Healthcare,nts. In this chapter, we will talk about various market factors affecting healthcare and how big data and analytics can help bring out value from data. We will look into interesting facts about various technology adoptions like IBM Watson and how these new technology adoptions play a vital role in improving the quality of care.
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