<div>This handbook offers comprehensive coverage of recent advancements in Big Data technologies and related paradigms. Β 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 organ
Handbook of Big Data Technologies
β Scribed by Albert Y. Zomaya, Sherif Sakr
- Publisher
- Springer
- Year
- 2017
- Tongue
- English
- Leaves
- 890
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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 scalable graph 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), Cognitive Computing and SCADA Systems. All parts of the book discuss open research problems, including potential opportunities, that have arisen from the rapid progress of Big Data technologies and the associated increasing requirements of application domains.
Designed for researchers, IT professionals and graduate students, this book is a timely contribution to the growing Big Data field. Big Data has been recognized as one of leading emerging technologies that will have a major contribution and impact on the various fields of science and varies aspect of the human society over the coming decades. Therefore, the content in this book will be an essential tool to help readers understand the development and future of the field.
β¦ Table of Contents
Front Matter....Pages i-xiii
Front Matter....Pages 1-1
Big Data Storage and Data Models....Pages 3-29
Big Data Programming Models....Pages 31-63
Programming Platforms for Big Data Analysis....Pages 65-99
Big Data Analysis on Clouds....Pages 101-142
Data Organization and Curation in Big Data....Pages 143-178
Big Data Query Engines....Pages 179-217
Large-Scale Data Stream Processing Systems....Pages 219-260
Front Matter....Pages 261-261
Semantic Data Integration....Pages 263-305
Linked Data Management....Pages 307-338
Non-native RDF Storage Engines....Pages 339-364
Exploratory Ad-Hoc Analytics for Big Data....Pages 365-407
Pattern Matching Over Linked Data Streams....Pages 409-427
Searching the Big Data: Practices and Experiences in Efficiently Querying Knowledge Bases....Pages 429-453
Front Matter....Pages 455-455
Management and Analysis of Big Graph Data: Current Systems and Open Challenges....Pages 457-505
Similarity Search in Large-Scale Graph Databases....Pages 507-529
Big-Graphs: Querying, Mining, and Beyond....Pages 531-582
Link and Graph Mining in the Big Data Era....Pages 583-616
Granular Social Network: Model and Applications....Pages 617-651
Front Matter....Pages 653-653
Big Data, IoT and Semantics....Pages 655-690
SCADA Systems in the Cloud....Pages 691-718
Front Matter....Pages 653-653
Quantitative Data Analysis in Finance....Pages 719-753
Emerging Cost Effective Big Data Architectures....Pages 755-776
Bringing High Performance Computing to Big Data Algorithms....Pages 777-806
Cognitive Computing: Where Big Data Is Driving Us....Pages 807-850
Privacy-Preserving Record Linkage for Big Data: Current Approaches and Research Challenges....Pages 851-895
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