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Handbook of Big Data Technologies /

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 i...

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Bibliographic Details
Corporate Authors: SpringerLink Online service
Group Author: Zomaya, Albert Y; Sakr, Sherif
Published: Springer International Publishing : Imprint: Springer,
Publisher Address: Cham :
Publication Dates: 2017.
Literature type: eBook
Language: English
Subjects:
Computer science
Big data
Computer organization
Computer programming
Data structures Computer science
Electrical engineering
Computer Systems Organization and Communication Networks
Communications Engineering, Networks
Data Storage Representation
Programming Techniques
Big Data/Analytics
Online Access: http://dx.doi.org/10.1007/978-3-319-49340-4
Summary: 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 syste
Carrier Form: 1 online resource (XIII, 895 pages) : illustrations
ISBN: 9783319493404
Index Number: QA76
CLC: TP303
Contents: Big Data Storage Models -- Big Data Programming Models -- Programming Platforms for Big Data Analysis -- Big Data Analysis on Clouds -- Data Organization and Curation in Big Data -- Big Data Query Engines -- Unbounded Data Processing -- Semantic Data Integration -- Linked Data Management -- Non-native RDF Storage Engines -- Exploratory Ad-hoc Analysis for Big Data -- Pattern Matching over Linked Data Streams -- Searching the Big Data Practices and Experiences in Efficiently Querying Knowledge Bases -- Management and Analysis of Big Graph Data -- Similarity Search in Large-Scale Graph Databas

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