Handbook of Big Data Technologies下载

Title: Handbook of Big Data Technologies Length: 895 pages Edition: 1st ed. 2017 Language: English Publisher: Springer Publication Date: 2017-03-26 ISBN-10: 3319493396 ISBN-13: 9783319493398 Table of Contents Part I Fundamentals of Big Data Processing Big Data Storage and Data Models 1 Storage Models 2 Data Models Big Data Programming Models 1 MapReduce 2 Functional Programming 3 SQL-Like 4 Actor Model 5 Statistical and Analytical 6 Dataflow-Based 7 Bulk Synchronous Parallel 8 High Level DSL 9 Discussion and Conclusion Programming Platforms for Big Data Analysis 1 Introduction 2 Requirements of Big Data Programming Support 3 Classification of Programming Platforms 4 Major Existing Programming Platforms 5 A Unifying Framework 6 Conclusion and Future Directions Big Data Analysis on Clouds 1 Introduction 2 Introducing Cloud Computing 3 Cloud Solutions for Big Data 4 Systems for Big Data Analytics in the Cloud 5 Research Trends 6 Conclusions Data Organization and Curation in Big Data 1 Big Data Indexing Techniques 2 Data Organization and Layout Techniques 3 Non-traditional Workloads in Big Data 4 Curation and Metadata Management in Big Data 5 Conclusion Big Data Query Engines 1 Introduction 2 Massively Parallel Query Engines 3 Hadoop Query Engines 4 SQL on Hadoop 5 Query Optimization 6 Query Execution 7 Summary Large-Scale Data Stream Processing Systems 1 Introduction 2 Programming Models 3 System Support for Distributed Data Streaming 4 Case Study: Stream Processing with Apache Flink 5 Applications, Trends and Open Challenges 6 Conclusions and Outlook Part II Semantic Big Data Management Semantic Data Integration 1 An Important Challenge 2 Current State-of-the-Art 3 The Path Forward Linked Data Management 1 Introduction 2 Background Information 3 Native Linked Data Stores 4 Provenance for Linked Data Non-native RDF Storage Engines 1 Introduction 2 Storing Linked Data Using Relational Databases 3 No-SQL Stores 4 Massively Parallel Processing for Linked Data Exploratory Ad-Hoc Analytics for Big Data 1 Exploratory Analytics for Big Data 2 A Top-K Entity Augmentation System 3 DrillBeyond -- Processing Open World SQL 4 Summary and Future Work Pattern Matching Over Linked Data Streams 1 Overview 2 Linked Data Dissemination System 3 Experimental Evaluation 4 Related Work 5 Summary Searching the Big Data: Practices and Experiences in Efficiently Querying Knowledge Bases 1 Introduction 2 Background 3 The Framework of Cache-Based Knowledge Base Querying 4 Similar Queries Suggestion 5 Cache Replacement 6 Implementation and Experimental Evaluation 7 Related Work 8 Discussion and Conclusion Part III Big Graph Analytics Management and Analysis of Big Graph Data: Current Systems and Open Challenges 1 Introduction 2 Graph Databases 3 Graph Processing 4 Graph Dataflow Systems 5 Gradoop 6 Comparison 7 Current Research and Open Challenges 8 Conclusions and Outlook Similarity Search in Large-Scale Graph Databases 1 Introduction 2 Preliminaries 3 The Pruning-Verification Framework 4 State-of-the-Art Approaches 5 Future Research Directions 6 Summary Big-Graphs: Querying, Mining, and Beyond 1 Introduction 2 Graph Data Models 3 Pattern Matching Techniques Over Big-Graphs 4 Mining Techniques Over Big-Graphs 5 Open Problems 6 Conclusions 7 About Authors Link and Graph Mining in the Big Data Era 1 Introduction 2 Definitions 3 Temporal Evolution 4 Link Prediction 5 Community Detection 6 Graphs in Big Data 7 Weighted Networks 8 Extending Graph Models: Multilayer Networks 9 Open Challenges 10 Conclusions Granular Social Network: Model and Applications 1 Introduction 2 Preliminaries 3 Literature Review 4 Fuzzy Granular Social Networks (FGSN) 5 Discussions and Conclusions Part IV Big Data Applications Big Data, IoT and Semantics 1 Introduction 2 Semantics for Big Data 3 Big Data and Semantics in the Internet of Things 4 Social Mining 5 Graph Mining 6 Big Stream Data Mining 7 Geo-Referenced Data Mining 8 Conclusion SCADA Systems in the Cloud 1 Introduction 2 Related Work 3 An Overview of SCADA 4 Moving SCADA to the Cloud 5 Conceptual SCADA Cloud Orchestration Framework 6 Results 7 Conclusion Quantitative Data Analysis in Finance 1 Introduction 2 The Three V's of Big Data in High Frequency Data 3 Data Cleaning, Aggregating and Management 4 Modeling High Frequency Data in Finance 5 Portfolio Selection and Evaluation 6 The Future 7 Conclusion Emerging Cost Effective Big Data Architectures 1 Introduction 2 Emerging Solutions for Big Data 3 Future Directions 4 Conclusion Bringing High Performance Computing to Big Data Algorithms 1 Introduction 2 GPU Acceleration of Alternating Least Squares 3 GPU Acceleration of Singular Value Decomposition 4 Conclusions Cognitive Computing: Where Big Data Is Driving Us 1 Cognitive Computing: An Alternative Approach for Clear Understanding 2 Big Data Impulsing Cognitive System 3 Traditional Systems versus Cognitive Systems? 4 Data Mining in the Era of Cognitive Systems 5 Design Methods for Cognitive Systems 6 Cognitive Systems 7 The Future of Cognitive Systems 8 Final Remarks Privacy-Preserving Record Linkage for Big Data: Current Approaches and Research Challenges 1 Introduction 2 Background 3 Privacy Aspects and Techniques for PPRL 4 Scalability Techniques for PPRL 5 Multi-party PPRL 6 Open Challenges 7 Conclusions