Large scale and big data : processing and management / edited by Sherif Sakr and Mohamed Medhat Gaber

Format:

Book

Contributor:

Sakr, Sherif

Gaber, Mohamed Medhat.

Language:

English

Physical Description:

1 online resource (612 p.)

Place of Publication:

Boca Raton : Taylor & Francis, [2014]

Summary:

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-- Provided by publisher.

Contents:

Front Cover; Contents; Preface; Editors; Contributors; Chapter 1: Distributed Programming for the Cloud : Models, Challenges, and Analytics Engines; Chapter 2: MapReduce Family of Large-Scale Data-Processing Systems; Chapter 3: iMapReduce : Extending MapReduce for Iterative Processing; Chapter 4: Incremental MapReduce Computations; Chapter 5: Large-Scale RDF Processing with MapReduce; Chapter 6: Algebraic Optimization of RDF Graph Pattern Queries on MapReduce; Chapter 7: Network Performance Aware Graph Partitioning for Large Graph Processing Systems in the Cloud

Chapter 8: PEGASUS : A System for Large-Scale Graph ProcessingChapter 9: An Overview of the NoSQL World; Chapter 10: Consistency Management in Cloud Storage Systems; Chapter 11: CloudDB AutoAdmin : A Consumer-Centric Framework for SLA Management of Virtualized Database Servers; Chapter 12: An Overview of Large-Scale Stream Processing Engines; Chapter 13: Advanced Algorithms for Efficient Approximate Duplicate Detection in Data Streams Using Bloom Filters; Chapter 14: Large-Scale Network Traffic Analysis for Estimating the Size of IP Addresses and Detecting Traffic Anomalies

Chapter 15: Recommending Environmental Big Data Using Semantically Guided Machine LearningChapter 16: Virtualizing Resources for the Cloud; Chapter 17: Toward Optimal Resource Provisioning for Economical and Green MapReduce Computing in the Cloud; Chapter 18: Performance Analysis for Large IaaS Clouds; Chapter 19: Security in Big Data and Cloud Computing : Challenges, Solutions, and Open Problems; Back Cover

Notes:

An Auerbach book.

ISBN:

9780429103568

0429103565

9781466581500

1466581506

OCLC:

881458050