Encyclopedia of Big Data Technologies

Preface......Page 5 Big Semantic Data Processing......Page 7 Big Data Applications......Page 8 Big Data Security and Privacy......Page 9 Data Compression......Page 10 Big Stream Processing......Page 11 About the Editors......Page 12 About the Section Editors......Page 15 List of Contributors......Page 24 Overview......Page 44 Key Research Findings......Page 45 Specification of NMSI......Page 46 Blotter Architecture......Page 47 Single Data Center Protocol......Page 48 Examples of Applications......Page 51 References......Page 52 Active Disk......Page 53 Overview......Page 54 Storage......Page 55 Memory: Processing-In-Memory (PIM)......Page 57 Active Network......Page 58 References......Page 59 Context......Page 61 Methods......Page 62 Future Research......Page 64 References......Page 65 Overview......Page 66 YARN Architecture......Page 68 Resource Utilization......Page 69 Cluster Scalability......Page 70 Long-Running Services......Page 71 Further Improvements......Page 72 References......Page 74 Definitions......Page 75 TPC......Page 76 Big Data Technologies......Page 77 Foundations......Page 78 Key Applications......Page 81 References......Page 82 Introduction......Page 84 Application Model and APIs......Page 85 Checkpointing......Page 86 High Availability......Page 89 Partitioners......Page 90 Dynamic Partitioning......Page 91 Integration Using Apex Library......Page 92 References......Page 93 Historical Background......Page 94 Foundations......Page 96 Time Handling......Page 98 State and Fault Tolerance......Page 99 References......Page 100 Definitions......Page 101 Overview......Page 102 Fault Tolerance and High Availability......Page 103 Writing to Kafka......Page 104 Kafka Connect Framework......Page 105 Streams and Tables......Page 106 Time Semantics......Page 107 References......Page 108 Historical Background......Page 109 Foundations......Page 110 Key Applications......Page 111 Overview......Page 113 Partitioned Log Processing......Page 114 Fault-Tolerant Local State......Page 116 Cluster-Based Task Scheduling......Page 118 References......Page 119 Overview......Page 120 Spark Streaming......Page 121 Examples of Applications......Page 122 References......Page 123 Overview......Page 124 Key Research Findings......Page 127 References......Page 128 Definitions......Page 129 Key Research Findings......Page 130 Examples of Application......Page 131 References......Page 132 Introduction......Page 133 Computational Model......Page 134 System Workflow......Page 135 Error Estimation......Page 136 Discussion......Page 137 Related Work......Page 138 References......Page 139 Approximate Reasoning......Page 140 Overview......Page 141 Key Research Findings......Page 142 Spatial Batch Processing......Page 143 Spatial Joins......Page 144 Lambda Architecture......Page 145 Apache Hadoop......Page 146 Big Data as a Service......Page 147 Future Directions for Research......Page 148 References......Page 149 Definitions......Page 151 Convergence and Divergence......Page 152 Artifact-Centric Process Models......Page 153 Artifact-Centric Process Mining......Page 155 Key Research Findings......Page 157 Future Directions for Research......Page 158 References......Page 159 Definitions......Page 160 Auditing the Results......Page 161 Auditing Adoption......Page 162 Automated Creation of Infographics......Page 163 Automated Process Discovery......Page 164 Log Quality......Page 165 Process Discovery Algorithms......Page 166 Directly Follows-Based Techniques......Page 167 Structured Miner......Page 168 α-Algorithms......Page 169 Cross-References......Page 170 References......Page 171 A Bit of History......Page 173 Classification......Page 174 HermiT......Page 175 Applications......Page 176 References......Page 177 Availability......Page 179 Overview......Page 180 Test Environment Preparation......Page 181 Scheduling and Accounting of Benchmark Operations......Page 182 Examples of Application......Page 183 Overview......Page 184 Introduction......Page 185 Data Generation......Page 186 Data Interoperability......Page 187 Smart Cities and Homes......Page 188 Health......Page 189 Business......Page 190 Open Issues......Page 191 Summary......Page 193 References......Page 194 Introduction......Page 195 Research, Technological and Social Challenges in Smart Cities......Page 196 Urban Big Data Collected in Smart Cities......Page 197 Smart City Applications......Page 198 References......Page 200 The Data......Page 201 Computational Power......Page 202 Analysis of These Data......Page 203 Definitions......Page 204 Introduction......Page 205 Gene Expression Data......Page 206 Mass Spectrometry Data......Page 207 The EMBL Nucleotide Sequence Database......Page 208 Protein Data Bank (PDB)......Page 209 DIP......Page 210 Biological Databases on the Cloud......Page 211 Affymetrix Power Tools......Page 212 easyExon......Page 213 Analysis of Mass Spectrometry Data: Protein Identification......Page 214 XPRESS......Page 215 Analysis of Protein Interaction Networks: Protein Complexes Prediction......Page 216 Mawish......Page 217 MAGNA......Page 218 Conclusions......Page 219 References......Page 220 Univariate Forecasting Methods......Page 223 Multivariate Forecasting Methods......Page 224 Machine Learning Approaches......Page 225 References......Page 226 Exascale Computing......Page 227 Convergence of Big Data and Exascale Computing......Page 228 Challenges and Opportunities......Page 229 Definitions......Page 230 Background......Page 231 Motivations......Page 232 Characteristics......Page 233 Role of Big Data......Page 234 Healthcare......Page 235 Research Directions......Page 236 Cross-References......Page 237 References......Page 238 Definitions......Page 239 Introduction......Page 240 Toward Big Data Collection in Vehicular Networks......Page 242 Security Requirements and System Model for Secure Big Data Collection in IoVs......Page 243 Open Research Challenges and Future Directions......Page 244 References......Page 245 Recommender Systems......Page 246 Recommender Systems and Online Social Networks......Page 248 Recommender Systems and Location-Based Social Networks......Page 250 References......Page 251 Introduction......Page 252 Manufacturing Industry Transaction Processing......Page 253 Analytics and Decision Support Requirements......Page 254 Organization Readiness and Affordability......Page 255 Definitions......Page 256 Lambda Architecture......Page 257 Big Data Architecture Framework (BDAF)......Page 258 SOLID......Page 259 Summary of Architectures......Page 260 Examples of Applications......Page 261 References......Page 262 Overview......Page 263 Tools of Deep Learning Big Data......Page 264 Conclusion......Page 267 References......Page 268 Overview......Page 269 Research Findings......Page 271 KDD Applied to LMI......Page 272 Application 2: LMI for Producing Official Statistics......Page 274 Future Directions for Research......Page 275 Concluding Remarks......Page 277 References......Page 278 Definitions......Page 279 Intrusion Detection......Page 280 Intrusion Detection: Methods and Techniques......Page 281 From Raw Data to Cyber Threat Intelligence......Page 283 Future Directions for Research......Page 286 Synonyms......Page 287 Overview......Page 288 Characterization of Health-Related Big Data......Page 289 Omics Data......Page 290 Business, Organizational, and External Data......Page 291 Clinical Decision Support......Page 292 Health and Wellness Monitoring......Page 293 Opportunities and Issues......Page 294 References......Page 295 Overview......Page 297 Consumer Phase Data......Page 298 How Big Data Is Transforming Automotive Industry......Page 299 Future Opportunities and Challenges for Big Data in Automotive Industry......Page 301 Synonyms......Page 303 Traffic Classification......Page 304 Big Data Challenges on Network Monitoring......Page 305 Big Data Technologies in Network Monitoring......Page 306 Data Management......Page 307 Research Directions......Page 309 References......Page 310 Introduction......Page 311 Functionalities and Features of a Big Data Platform for CH Applications......Page 312 CHIS: A Big Data Platform for CH Applications......Page 313 Synonyms......Page 316 Call Detail Record (CDR)......Page 317 Passive Monitoring......Page 319 Technical Areas......Page 321 Anomaly Detection......Page 322 Human Mobility......Page 323 Cross-References......Page 324 References......Page 325 Definitions......Page 326 Overview......Page 327 Literature Review in Network Anomaly Detection......Page 328 Key Research Findings on Network Anomaly Detection......Page 330 Challenges in Applying Big Data in Network Anomaly Detection......Page 332 Conclusion......Page 333 References......Page 334 Overview......Page 335 Smart Cities Big Data: A Holistic View......Page 336 Applications......Page 340 Challenges as Lessons Learned......Page 342 Cross-References......Page 343 Synonyms......Page 344 Online Social Networks......Page 345 Social Network Analysis......Page 346 Influence Diffusion......Page 347 Community Detection......Page 349 References......Page 350 Overview......Page 351 Real-Time Big Data Analytics in the Cloud......Page 352 Security of Big Data Against Internal Attackers......Page 353 IoT Big Data in the Cloud......Page 354 Cloud-Based Big Data Analytics Tools......Page 355 Future Directions for Research......Page 356 References......Page 357 Overview......Page 358 Record-Level Nonadaptive Indexing......Page 361 Record-Level Adaptive Indexing......Page 363 Split-Level Indexing......Page 364 Hadoop-RDBMS Hybrid Indexing......Page 365 References......Page 367 Introduction......Page 368 Security Properties......Page 369 CIA Triad......Page 370 Classification......Page 371 References......Page 372 Overview......Page 373 From Data Storage to Data Disposal......Page 374 DNA-Specific Compression......Page 375 Integration of Heterogeneous Data......Page 376 Bioinformatics for Sequencing Data......Page 377 References......Page 378 Overview......Page 379 Systems and Techniques......Page 380 References......Page 382 Overview......Page 384 Platforms: Data Organization and Distribution......Page 385 Technological Infrastructure......Page 387 Data Modeling......Page 389 Examples of Application......Page 391 References......Page 393 Overview......Page 394 The KG Landscape in Biomedical Domains......Page 395 Bio2RDF......Page 396 Genome-Wide Association Studies (GWAS)......Page 397 Machine Learning in Bio with KGs......Page 398 Cross-References......Page 399 References......Page 400 Overview......Page 401 Big Data Challenges......Page 402 Databases......Page 403 Ontologies......Page 404 References......Page 406 Big Spatial Data Access Methods......Page 408 Overview......Page 409 Key Research Findings......Page 410 Blockchain Topologies......Page 411 Blockchain Consensus......Page 412 Blockchain Systems......Page 415 References......Page 418 Communication......Page 420 Limitations......Page 421 Apache Hama......Page 422 References......Page 423 Definitions......Page 424 Business Process Event Data......Page 425 Business Process Models......Page 426 Business Process Analytics Techniques......Page 427 Event Data Management......Page 428 Process Discovery and Conformance Checking......Page 429 Online and Predictive Process Analytics......Page 430 Business Process Anomaly Detection......Page 431 Overview......Page 432 Classification-Based Deviance Mining......Page 433 Model-Based Approaches......Page 435 Similarity/Clustering-Based Approaches......Page 437 Discussion and Directions of Future Research......Page 438 References......Page 440 Overview......Page 441 The XES Standard......Page 442 Correlation Challenge......Page 443 Granularity Challenge......Page 444 Event Log Visualizations......Page 445 Timeline Charts......Page 446 Dependency Graphs......Page 447 Handoff Graphs......Page 450 References......Page 451 Overview......Page 452 Leveraging Activity Labels......Page 453 Alternative Techniques......Page 454 Approaches for Evaluating Process Model Matching Techniques......Page 455 Future Directions for Research......Page 456 References......Page 457 Defining PPIs......Page 459 Evaluating PPIs......Page 460 Performance Measurement Models......Page 461 PPI Definition Approaches......Page 462 Future Directions for Research......Page 463 References......Page 464 Overview......Page 465 Framework......Page 466 Log Querying......Page 467 Model Querying......Page 468 Log and Model Querying......Page 470 References......Page 471 Business Process Variants Analysis......Page 473 Overview......Page 474 External Storage Systems for Caching......Page 475 Apache Ignite HDFS Cache......Page 476 Conclusion......Page 477 Definitions......Page 478 HDD-Based High-Density Storage......Page 479 Key Research Findings......Page 480 CSD Storage Manager......Page 481 Database Query Executor......Page 482 Examples of Application......Page 483 Future Directions for Research......Page 484 References......Page 485 Clojure for Instant Prototyping, with a REPL......Page 486 Clojure for Code as Data......Page 487 Clojure Laziness and Reducers......Page 488 Clojure for Multi-threading......Page 489 Clojure for the Backend......Page 490 Clojure for the Front End......Page 491 Clojure for Big Data......Page 492 Clojure for Machine Learning......Page 493 Clojure for Teaching......Page 494 Overview......Page 495 Key Research Findings......Page 496 Examples of Application......Page 498 Future Directions for Research......Page 499 Cloud Databases......Page 500 Elastic Compute......Page 501 Additional Features and Opportunities......Page 502 Cloud and Database Systems......Page 503 Google BigQuery......Page 505 References......Page 506 Overview......Page 507 Related Work......Page 508 File Organization......Page 509 File Organization......Page 510 Conclusions......Page 511 Overview......Page 512 Foundations......Page 513 Key Applications......Page 516 References......Page 517 Run-Length Compressed CSAs and FM-Indexes......Page 518 Lempel-Ziv and Grammar-Based Indexes......Page 519 Graph-Based Indexes......Page 520 Cross-References......Page 521 References......Page 522 Historical Trends in Computer Architecture......Page 524 How Big Data Affects Computer Architecture......Page 525 Architectural Aids to Data Translations......Page 526 Memory, Processing, and Interconnects......Page 527 References......Page 528 Overview......Page 530 Cost Model for Data Retention......Page 531 Implications of the Cost Model......Page 532 Definitions......Page 534 Concurrency Semantics......Page 535 Register......Page 536 Synchronization Model......Page 537 Extended Behavior Under Concurrency......Page 538 Guaranties and Limitations......Page 539 Reversible Computation......Page 540 Verification......Page 541 References......Page 542 Definitions......Page 543 Dimensions of Conformance......Page 544 Types of Conformance......Page 546 Token Replay......Page 547 Cost-Based Alignment......Page 548 Cost-Based Fitness Metric......Page 550 Artificial Negative Events......Page 551 Examples of Application......Page 553 References......Page 555 Overview......Page 556 SQL-Like Syntax......Page 557 Stream-Relational Algebra......Page 558 Future Directions for Research......Page 560 References......Page 561 Overview......Page 562 Commutativity and Convergence......Page 563 Application-Level Correctness Semantics......Page 564 Versioning and Snapshots......Page 565 References......Page 566 Introduction......Page 568 Security Issues in Cloud......Page 569 Co-resident Attack......Page 570 Defense Methods......Page 571 Definitions......Page 572 Scientific Fundamentals......Page 573 Key Applications......Page 574 References......Page 575 Cryptocurrency......Page 576 Overview......Page 577 Enforcing Data Quality Rules......Page 578 Data Transformation......Page 579 Applications of Data Cleaning......Page 581 References......Page 582 Data Differencing......Page 583 Levels of Abstraction: The JDL Model......Page 584 Computational Resources for Big Data Fusion: Cloud Computing......Page 586 Application Examples......Page 587 References......Page 588 Overview......Page 589 P2P Data Management......Page 592 References......Page 593 Architecture......Page 594 Ingestion Layer......Page 595 Storage Layer......Page 596 Lazy and Pay-as-You-Go Concepts......Page 597 Data Governance and Data Quality......Page 598 Future Directions for Research......Page 599 References......Page 600 Media for Long-Term Data Storage......Page 601 Data Decay and Device Lifespans......Page 602 Future Directions......Page 603 References......Page 604 Overview......Page 605 Key Research Findings......Page 606 Examples of Application......Page 607 Future Directions for Research......Page 608 References......Page 609 Overview......Page 610 Provenance Phases in Big Data Workflows......Page 611 Examples Applications......Page 613 References......Page 614 Semantic Web Data Quality......Page 615 Accessibility Dimensions......Page 616 Intrinsic Dimensions......Page 617 Contextual Dimensions......Page 618 Representing Quality Metadata as Linked Data: The W3C Data Quality Vocabulary......Page 619 References......Page 620 Data Unavailability, Corruption, and Loss......Page 621 Error-Detecting Codes......Page 622 Data Dispersion......Page 623 References......Page 624 Data Validation......Page 625 Overview......Page 626 Data Parsing and Structuring......Page 627 Data Profiling......Page 628 Data Enrichment and Distillation......Page 629 Future Directions for Research......Page 630 Inferential Methods to Accelerate Wrangling......Page 631 References......Page 632 Background......Page 633 Basic Concepts......Page 634 Definitions......Page 635 Fundamental Results......Page 636 Client Monotonic (CM)......Page 637 Snapshot Isolation (SI)......Page 638 A Three-Dimensional View of Data Consistency......Page 639 Examples of Application......Page 640 References......Page 641 Overview......Page 643 Positioning DBaaS......Page 644 Disadvantages of the DBaaS Model......Page 645 Types of Databases......Page 646 Future Directions for Research......Page 647 References......Page 648 Data-Driven Process Simulation......Page 649 Entity Types......Page 650 Queue Discipline......Page 651 Resource Schedules......Page 652 Future Directions for Research......Page 653 References......Page 654 Introduction......Page 656 Decision Mining as a Classification Problem......Page 659 Extension of the Basic Technique......Page 660 Non-compliance and Invisible Steps......Page 661 Overlapping Rules......Page 662 Example Cases and Tool Support......Page 663 Conclusion......Page 665 References......Page 666 Introduction......Page 667 Process Discovery......Page 668 Conformance Checking......Page 669 Compliance Monitoring......Page 670 Conclusion......Page 671 References......Page 672 Definitions......Page 674 Overview......Page 675 Key Research Findings......Page 678 Future Directions for Research......Page 679 References......Page 680 Overview......Page 681 Deep Neural Networks......Page 682 Convolutional Neural Networks......Page 683 Recurrent Neural Networks and Long Short Time Memory Networks......Page 684 Autoencoders......Page 685 Examples of Application......Page 687 Future Directions for Research......Page 688 References......Page 689 Definitions......Page 690 Time......Page 691 General Requirements of Stream Processing......Page 692 References......Page 693 Overview......Page 694 Classical Sampling......Page 695 Sketch-Based Sampling......Page 696 On Computing the Diameter......Page 697 Examples of Application......Page 698 References......Page 699 Definitions......Page 700 String-to-String Correction and Differencing......Page 701 A Sample Implementation......Page 702 Compressing Collections of Files......Page 703 Examples of Applications......Page 704 Future Directions for Research......Page 705 References......Page 706 Definitions......Page 707 Key Research Findings......Page 708 Examples of Application......Page 711 References......Page 712 Basic Approach......Page 713 Negative Labels......Page 715 Embedding-Based Methods......Page 716 Leveraging Auxiliary Information for Supervision......Page 717 References......Page 718 Overview......Page 719 Replication Policy......Page 720 Examples of Application......Page 721 Ceph......Page 722 References......Page 723 Overview......Page 724 Incremental View Maintenance......Page 725 Compilation Overview......Page 727 Forming Distributed Programs......Page 728 Inter-statement Optimization......Page 730 Distributed View Update......Page 732 Dynamic Scaling......Page 733 Historical Background......Page 734 Foundations......Page 735 Triggering Mechanism......Page 736 State Transfer......Page 737 Cross-References......Page 738 References......Page 739 GPU......Page 740 Die-Stacked DRAM......Page 741 RDMA......Page 742 References......Page 743 Historical Background......Page 744 Related Work......Page 745 Foundations......Page 746 Content Metadata......Page 747 Batch Model Building......Page 748 Metrics......Page 749 Historical Background......Page 751 Foundations......Page 752 Key Research Findings......Page 754 References......Page 755 Hardware Approaches......Page 756 DBMS Approaches......Page 757 Energy-Efficient Data Analysis on Mobile Computing......Page 758 Energy-Efficient Query Processing in Sensor Networks......Page 760 Conclusion and Future Direction......Page 761 References......Page 762 Causes of Energy Dissipation......Page 763 Memory/Storage Energy Requirements......Page 765 Communication Energy Requirements......Page 766 Future Directions......Page 767 References......Page 768 Definitions......Page 769 Overview......Page 770 Key Research Findings......Page 771 Examples of Application......Page 772 References......Page 773 Process Characteristics......Page 774 Event Log Characteristics......Page 775 Further Reading......Page 777 References......Page 778 Definitions......Page 780 State-of-the-Art & Contemporary Applications......Page 781 Concept of Attack Graph for Interconnected Systems......Page 782 Natural Computing for Resilience and Self-Organized Mechanism......Page 783 Conclusion and Scope of Future Research......Page 784 Extract-Transform-Load......Page 785 Overview......Page 786 The Social Dimension Model......Page 788 The DeepWalk Model......Page 789 The node2vec Model......Page 791 Examples of Application......Page 793 References......Page 794 Formalization of SPARQL Over Federated RDF Data......Page 795 Query Processing......Page 796 Query Decomposition and Source Selection......Page 797 Query Execution Techniques......Page 798 Challenges of Using the Semantic Web as a Federation......Page 799 References......Page 800 Overview......Page 802 Introduction......Page 803 Literature Review......Page 804 Efficient Natural Language Processing (NLP) Techniques for Flood Detection Using Social Media Big Data Text Streams......Page 805 Deep Neural Network (DNN)......Page 806 State-of-the-Art NLP Systems for Flood Detection Using Big Data Streams......Page 807 Flood Detection from Social Media Visual Big Data Stream: Machine Learning and Deep Learning Techniques......Page 808 Importance of Deep Learning (DL) Algorithms in Event Prediction......Page 809 Conclusion......Page 810 References......Page 811 Overview......Page 812 Hadoop-Based RDF Systems......Page 813 Spark-Based RDF Systems......Page 815 References......Page 817 Functional Benchmark......Page 818 Overview......Page 819 Alignment-Based FASTQ Compressors......Page 820 The CRAM Format and Reference-Based Compressors......Page 821 References......Page 822 Definitions......Page 823 Synchronous Replication......Page 824 Concurrency and Conflict Resolutions......Page 825 Key Research Findings......Page 826 Future Directions for Research......Page 827 References......Page 828 Synonyms......Page 829 Strongly Consistent Transactions......Page 830 Weak and Relaxed Transactional Semantics......Page 832 Examples of Application......Page 833 References......Page 834 GPU......Page 836 Mobile Platforms......Page 837 Multi-package......Page 839 References......Page 840 String Grammars......Page 841 Equality Checking......Page 842 Grammar Compressors......Page 843 Graph Grammars......Page 844 Grammar Compressors......Page 845 Future Directions of Research......Page 846 References......Page 847 Introduction......Page 848 Real Graphs Properties......Page 849 Barabasi-Albert......Page 850 Online Queries......Page 851 Experiment Design......Page 852 References......Page 853 Graph Compression......Page 854 Graph Schemas, Instances, and Queries......Page 855 Data Exchange Solutions and Universal Representatives......Page 856 Query Answering and Query Rewriting......Page 857 Graph Data Exchange......Page 858 Mapping Management for Data Graphs......Page 859 Future Directions for Research......Page 860 References......Page 861 Classification......Page 862 Storage Representations......Page 863 Declarative QLs......Page 864 Low Level......Page 865 Native Graph Processing......Page 866 Discussion......Page 868 References......Page 869 Overview......Page 870 Key Research Findings......Page 871 The Property Graph Model......Page 872 The Nested Data Model......Page 873 A Brief Comparison of Models......Page 874 Graph Drawing......Page 875 Graph Search with Keywords......Page 876 Exploratory Graph Analysis......Page 877 Reformulation of Graph Queries......Page 878 Key Applications......Page 879 References......Page 880 The Workload......Page 881 LUBM......Page 883 LDBC SNB Interactive......Page 884 LDBC Graphalytics......Page 885 Usage-Driven Query Analysis and Benchmarking......Page 886 References......Page 887 Overview......Page 888 Invariants and Centrality Indices......Page 889 Local Properties......Page 890 Shortest Paths......Page 891 Alternative Definitions......Page 892 References......Page 893 Overview......Page 894 OLAP on Graph Data......Page 895 Dynamic Graph Analytics......Page 896 Future Directions of Research......Page 897 Definitions......Page 898 Vertex-Based Partitioning......Page 899 Objective Functions......Page 900 Examples of Application......Page 901 References......Page 903 Path Queries......Page 905 Regular Path Queries......Page 906 Regular Path Queries with Inverse......Page 907 Conjunctive Regular Path Queries......Page 908 Simple Path Semantics......Page 909 References......Page 910 Overview......Page 911 Making Big Graphs Small......Page 912 User-Friendly Pattern Matching......Page 913 References......Page 914 Definitions......Page 915 Overview......Page 916 BSP Graph Processing Frameworks......Page 917 Single-Machine Graph Processing Frameworks......Page 918 Example of Application......Page 919 Future Directions for Research......Page 920 References......Page 922 Key Research Findings......Page 923 Graph Pattern Matching......Page 924 Path Queries......Page 925 Beyond Patterns......Page 926 Composability......Page 927 References......Page 928 Subgraph Queries......Page 930 Vertex-at-a-time Approaches......Page 931 Query Decompositions......Page 932 Regular Path Queries......Page 933 Relational Algebra and Datalog-Based Approaches......Page 934 Finite Automata-Based Approaches......Page 935 Research Directions......Page 936 References......Page 937 Adjacency Representation......Page 938 Property Representation......Page 939 Indexing......Page 940 Examples of Applications......Page 942 References......Page 943 Overview......Page 944 Undirected Graph Drawing......Page 945 Spring-Electrical Model......Page 946 Spring/Stress Model......Page 947 Layered Graph Layout......Page 948 Future Directions for Research......Page 949 Time-Varying and Complex Graphs......Page 950 References......Page 951 Green Big Data......Page 952 Introduction......Page 953 HDFS......Page 954 MapReduce......Page 955 Hadoop Software......Page 957 Factors that Affect Reliability......Page 958 Reliability of Storage Medias......Page 959 SSD......Page 960 Promising Future Trend......Page 961 Definitions......Page 962 Video and Image Compression......Page 963 Memory Systems......Page 964 References......Page 965 Definitions......Page 967 Communication Patterns in Transaction Processing......Page 968 Key Research Findings......Page 969 Logical or Physiological Partitioning......Page 970 Future Directions of Research: Toward Many Cores......Page 971 Conclusions......Page 972 References......Page 973 Definitions......Page 974 Architectural Considerations......Page 975 Access Paths and Interface Extensions......Page 977 Recovery and Instant Restart......Page 978 References......Page 979 Healthcare Ontologies......Page 981 Control-Flow-Based Techniques......Page 982 Data-Based Techniques......Page 983 Core BPMN and Activity Markers......Page 984 Complete BPMN......Page 985 Conclusion and Final Considerations......Page 986 Definitions......Page 987 Overview......Page 988 Storage and Retrieval......Page 989 Indexing Using Multiversion Arrays......Page 990 Runtime Environment Aspects......Page 991 Examples of Application......Page 992 References......Page 993 Running on Hadoop, Scalability, and High Availability......Page 994 “Unstructured” and Text Data......Page 995 Partition Pruning......Page 996 Query Execution......Page 997 SQL......Page 998 Security......Page 999 Definitions......Page 1000 Holistic Matching for Schema and Ontology Integration......Page 1001 Holistic Matching of Web Forms and Web Tables......Page 1002 References......Page 1004 HopsFS vs. HDFS......Page 1005 MySQL's NDB Distributed Relational Database......Page 1006 Distribution-Aware Transactions (DAT)......Page 1008 HopsFS Distributed Metadata......Page 1009 HopsFS Transactional Operations......Page 1012 Transactional File System Operation......Page 1013 Subtree Operations......Page 1014 Storing Small Files in the Database......Page 1015 Results......Page 1016 References......Page 1018 Overview......Page 1019 Key Research Findings......Page 1020 Unified Data The Encyclopedia of Big Data Technologies provides IT professionals, educators, researchers and students with a comprehensive set of definitions covering the most relevant Big Data technologies. The encyclopedia articles will be authored by a worldwide subject matter experts in industry and academia, this unique publication, in multiple volumes, covers a wide range of Big Data topics. The editorial board of the encyclopedia consists of 35 well-respected scholars. The sections are designed to capture the most relevant terms and assigned to experts that develop articles in a consistent and standardized way. This extensive reference work answers the need for solid and comprehensive research source in the domain of big data technologies. The encyclopedia will not be focused only on one discipline, research area or one type of data. It will cover all related technical disciplines for big data technologies such as big data storage systems, NoSQL database, cloud computing, distributed systems, machine learning and social technologies. In particular, this encyclopedia will provide comprehensive reading materials for a large range of audiences and has potential to influence readers to think further and investigate the area that are novel to them. -- Provided by publisher