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Titlebook: Handbook of Big Data Technologies; Albert Y. Zomaya,Sherif Sakr Book 2017 Springer International Publishing AG 2017 Big Data.MapReduce.Had

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书目名称Handbook of Big Data Technologies
编辑Albert Y. Zomaya,Sherif Sakr
视频video
概述Provides essential reader insight into the vast potential power and value of Big Data resources.Offers the reader a comprehensive examination of Big Data technologies.Inspects both theoretical and pra
图书封面Titlebook: Handbook of Big Data Technologies;  Albert Y. Zomaya,Sherif Sakr Book 2017 Springer International Publishing AG 2017 Big Data.MapReduce.Had
描述This handbook offers comprehensive coverage of recent advancements in Big Data technologies and related paradigms.  Chapters are authored by international leading experts in the field, and have been reviewed and revised for maximum reader value. The volume consists of twenty-five chapters organized into four main parts. Part one covers the fundamental concepts of Big Data technologies including data curation mechanisms, data models, storage models, programming models and programming platforms. It also dives into the details of implementing Big SQL query engines and big stream processing systems.  Part Two focuses on the semantic aspects of Big Data management including data integration and exploratory ad hoc analysis in addition to structured querying and pattern matching techniques.  Part Three presents a comprehensive overview of large scale graph processing. It covers the most recent research in large scale graph processing platforms, introducing several scalablegraph querying and mining mechanisms in domains such as social networks.  Part Four details novel applications that have been made possible by the rapid emergence of Big Data technologies such as Internet-of-Things (IOT)
出版日期Book 2017
关键词Big Data; MapReduce; Hadoop; Spark; Big graph analytics; Data analytics; Big SQL; Big Data applications; Gir
版次1
doihttps://doi.org/10.1007/978-3-319-49340-4
isbn_softcover978-3-319-84138-0
isbn_ebook978-3-319-49340-4
copyrightSpringer International Publishing AG 2017
The information of publication is updating

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Big Data Analysis on Cloudstorage, process and analysis capabilities. Those data volumes, commonly referred as Big Data, can be exploited to extract useful information and to produce helpful knowledge for science, industry, public services and in general for humankind. Big Data analytics refer to advanced mining techniques ap
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Data Organization and Curation in Big Data analytics are getting more complex, the advances in big data applications are no longer hindered by their ability to collect or generate data. But instead, by their ability to efficiently and effectively manage the available data. Therefore, numerous scalable and distributed infrastructures have be
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Big Data Query Enginesare used in several big data applications ranging from the generation of simple reports to running deep and complex query workloads. The insights drawn by running big data analytics depend primarily on the capabilities of the underlying query engine, which is responsible for translating user queries
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Semantic Data Integrationuly useful, scientists need not only to be able to access it, but also be able to interpret and use it. Doing this requires semantic context. Semantic Data Integration is an active field of research, and this chapter describes the current challenges and how existing approaches are addressing them. T
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Non-native RDF Storage Enginesn be stored according to many different data storage models. Some of these attempt to use general purpose database storage techniques to persist Linked Data, hence they can leverage existing data processing environments (e.g., big Hadoop clusters). We therefore look at the multiplicity of Linked Dat
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