Large scale and big data : processing and management

✍ Scribed by Sherif Sakr; Mohamed Medhat Gaber

• Publisher: Taylor & Francis
• Year: 2014
• Tongue: English
• Leaves: 610
• Category: Library

✦ Synopsis

''This book provides a central source of reference on the various data management techniques of large scale data processing and its technology application. This book presents chapters written by leading researchers, academics, and practitioners in the field, all of which have been reviewed by independent reviewers. The book covers the latest research discoveries and applications. Coverage includes cloud data management architectures, big data analytics visualization, data management, analytics for vast amounts of unstructured data, clustering, classification, link analysis of big data, scalable data mining, and machine learning techniques''-- Read more...

✦ Table of Contents

Content: Chapter 1. Distributed programming for the cloud : models, challenges, and analytics engines / Mohammad Hammoud and Majd F. Sakr --
chapter 2. MapReduce family of large-scale data-processing systems / Sherif Sakr, Anna Liu, and Ayman G. Fayoumi --
chapter 3. iMapReduce : extending MapReduce for iterative processing / Yanfeng Zhang, Qixin Gao, Lixin Gao, and Cuirong Wang --
chapter 4. Incremental MapReduce computations / Pramod Bhatotia, Alexander Wieder, Umut A. Acar, and Rodrigo Rodrigues --
chapter 5. Large-scale RDF processing with MapReduce / Alexander Schätzle, Martin Przyjaciel-Zablocki, Thomas Hornung, and Georg Lausen --
chapter 6. Algebraic optimization of RDF graph pattern queries on MapReduce / Kemafor Anyanwu, Padmashree Ravindra, and HyeongSik Kim --
chapter 7. Network performance aware graph partitioning for large graph processing systems in the cloud / Rishan Chen, Xuetian Weng, Bingsheng He, Byron Choi, and Mao Yang --
chapter 8. PEGASUS : a system for large-scale graph processing / Charalampos E. Tsourakakis --
chapter 9. An overview of the NoSQL world / Liang Zhao, Sherif Sakr, and Anna Liu --
chapter 10. Consistency management in cloud storage systems / Houssem-Eddine Chihoub, Shadi Ibrahim, Gabriel Antoniu, and Maria S. Perez --
chapter 11. CloudDB AutoAdmin : a consumer-centric framework for SLA management of virtualized database servers / Sherif Sakr, Liang Zhao, and Anna Liu --
chapter 12. An overview of large-scale stream processing engines / Radwa Elshawi and Sherif Sakr --
chapter 13. Advanced algorithms for efficient approximate duplicate detection in data streams using bloom filters / Sourav Dutta and Ankur Narang --
chapter 14. Large-scale network traffic analysis for estimating the size of IP addresses and detecting traffic anomalies / Ahmed Metwally, Fabio Soldo, Matt Paduano, and Meenal Chhabra --
chapter 15. Recommending environmental big data using semantically guided machine learning / Ritaban Dutta, Ahsan Morshed, and Jagannath Aryal --
chapter 16. Virtualizing resources for the cloud / Mohammad Hammoud and Majd F. Sakr --
chapter 17. Toward optimal resource provisioning for economical and green MapReduce computing in the cloud / Keke Chen, Shumin Guo, James Powers, and Fengguang Tian --
chapter 18. Performance analysis for large IaaS clouds / Rahul Ghosh, Francesco Longo, and Kishor S. Trivedi --
chapter 19. Security in big data and cloud computing : challenges, solutions, and open problems / Ragib Hasan.
Abstract: ''This book provides a central source of reference on the various data management techniques of large scale data processing and its technology application. This book presents chapters written by leading researchers, academics, and practitioners in the field, all of which have been reviewed by independent reviewers. The book covers the latest research discoveries and applications. Coverage includes cloud data management architectures, big data analytics visualization, data management, analytics for vast amounts of unstructured data, clustering, classification, link analysis of big data, scalable data mining, and machine learning techniques''