Big Data Management and Processing

Big Data Management and Processing (Chapman & Hall/CRC Big Data Series)19 May 2017
by Kuan-Ching Li and Hai Jiang
Pages: 487 pages
Publisher Finelybook 出版社: Chapman and Hall/CRC; 1 edition (16 Jun. 2017)
Language 语言: English
ISBN-10 书号: 1498768075
ISBN-13 书号: 9781498768078
B0725SBTDN
From the Foreword:
"Big Data Management and Processing
is [a] state-of-the-art book that deals with a wide range of topical themes in the field of Big Data. The book,which probes many issues related to this exciting and rapidly growing field,covers processing,management,analytics,and applications... [It] is a very valuable addition to the literature. It will serve as a source of up-to-date research in this continuously developing area. The book also provides an opportunity for researchers to explore the use of advanced computing technologies and their impact on enhancing our capabilities to conduct more sophisticated studies."
---Sartaj Sahni,University of Florida,USA
"Big Data Management and Processing covers the latest Big Data research results in processing,analytics,management and applications. Both fundamental insights and representative applications are provided. This book is a timely and valuable resource for students,researchers and seasoned practitioners in Big Data fields.
--Hai Jin,Huazhong University of Science and Technology,China
Big Data Management and Processing
explores a range of big data related issues and their impact on the design of new computing systems. The twenty-one chapters were carefully selected and feature contributions from several outstanding researchers. The book endeavors to strike a balance between theoretical and practical coverage of innovative problem solving techniques for a range of platforms. It serves as a repository of paradigms,technologies,and applications that target different facets of big data computing systems.
The first part of the book explores energy and resource management issues,as well as legal compliance and quality management for Big Data. It covers In-Memory computing and In-Memory data grids,as well as co-scheduling for high performance computing applications. The second part of the book includes comprehensive coverage of Hadoop and Spark,along with security,privacy,and trust challenges and solutions.
The latter part of the book covers mining and clustering in Big Data,and includes applications in genomics,hospital big data processing,and vehicular cloud computing. The book also analyzes funding for Big Data projects.
Contents
Chapter 1 Big Data: Legal Compliance and Quality Management
Chapter 2 Energy Management for Green Big Data Centers
Chapter 3 The Art of In-Memory Computing for Big Data Processing
Chapter 4 Scheduling Nested Transactions on In-Memory Data Grids
Chapter 5 Co-Scheduling High-Performance Computing Applications
Chapter 6 Resource Management for MapReduce Jobs Performing Big Data Analytics
Chapter 7 Tyche: An Efficient Ethernet-Based Protocol for Converged Networked Storage
Chapter 8 Parallel Backpropagation Neural Network for Big Data Processing on Many-Core Platform
Chapter 9 SQL-on-Hadoop Systems: State-of-the-Art Exploration,Models,Performances,Issues,and Recommendations
Chapter 10 One Platform Rules All: From Hadoop 1.0 to Hadoop 2.0 and Spark
Chapter 11 Security,Privacy,and Trust for User-Generated Content: The Challenges and Solutions
Chapter 12 Role of Real-Time Big Data Processing in the Internet of Things
Chapter 13 End-to-End Security Framework for Big Sensing Data Streams
Chapter 14 Considerations on the Use of Custom Accelerators for Big Data Analytics
Chapter 15 Complex Mining from Uncertain Big Data in Distributed Environments: Problems,Definitions,and Two Effective and Efficient Algorithms
Chapter 16 Clustering in Big Data
Chapter 17 Large Graph Computing Systems
Chapter 18 Big Data in Genomics
Chapter 19 Maximizing the Return on Investment in Big Data Projects: An Approach Based upon the Incremental Funding of Project Development
Chapter 20 Parallel Data Mining and Applications in Hospital Big Data Processing
Chapter 21 Big Data in the Parking Lot
前言:
“大数据管理与处理
是一本处于大数据领域的广泛主题的最先进的书。这本书探讨了与这个激动人心和快速发展的领域有关的许多问题，涵盖了处理，管理，分析和应用... [它]是文学中非常有价值的补充。它将作为这个不断发展的领域的最新研究的来源。本书还为研究人员提供了探索先进计算技术的使用及其对增强我们进行更复杂研究的能力的影响的机会。“
--- Sartaj Sahni，美国佛罗里达大学
“大数据管理与处理”涵盖了最新的大数据处理，分析，管理和应用研究成果，提供了基本的见解和代表性的应用，本书是为大数据领域的学生，研究人员和经验丰富的实践者提供的及时有价值的资源。
- 华金华中科技大学，中国
大数据管理和处理
探讨一系列大数据相关问题及其对新计算系统设计的影响。二十一章经过精心挑选，来自几位优秀研究人员的贡献。本书努力在一系列平台的创新性解决问题技术的理论和实践覆盖面之间取得平衡。它作为针对大数据计算系统不同方面的范式，技术和应用程序的存储库。
本书的第一部分探讨了能源和资源管理问题，以及大数据的合法合规和质量管理。它涵盖内存计算和内存数据网格，以及高性能计算应用程序的协调调度。本书的第二部分包括Hadoop和Spark的全面报道，以及安全，隐私和信任挑战和解决方案。
本书的后半部分涉及大数据挖掘和集群，包括基因组学，医院大数据处理和车载云计算应用。该书还分析了大数据项目的资金。
目录
第1章大数据: 法律合规和质量管理
第二章绿色大数据中心的能源管理
第3章大数据处理的内存计算技术
第4章调度内存数据网格上的嵌套事务
第5章共同调度高性能计算应用
MapReduce工作的第6章资源管理执行大数据分析
第7章Tyche: 用于融合网络存储的高效的基于以太网的协议
第8章多核平台大数据处理并行反向传播神经网络
第9章SQL-on-Hadoop系统: 最先进的探索，模型，表演，问题和建议
第10章一个平台规则全部: 从Hadoop 1.0到Hadoop 2.0和Spark
第11章用户生成内容的安全，隐私和信任: 挑战和解决方案
第12章实时大数据处理在物联网中的作用
第13章大型传感数据流的端到端安全框架
第14章关于使用自定义加速器进行大数据分析的注意事项
第15章分布式环境中不确定大数据的复杂挖掘: 问题，定义和两种有效和高效的算法
第16章大数据集群
第17章大图计算系统
第18章基因组学中的大数据
第十九章大数据项目投资回报最大化: 基于项目开发增量资金的方法
第20章医院大数据处理中的并行数据挖掘与应用
第21章停车场大数据

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