Big data systems : a 360-degree approach /
Jawwad Ahmad Shamsi, Muhammad Ali Khojaye.
Bok Engelsk 2021 · Electronic books.
| Medvirkende | Khojaye, Muhammad AlI, (author.)
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| Omfang | 1 online resource (xxvii, 312 pages) : : illustrations
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| Opplysninger | Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Contents -- Preface -- Author Bios -- Acknowledgments -- List of Examples -- List of Figures -- List of Tables -- Section I: Introduction -- Chapter 1: Introduction to Big Data Systems -- 1.1. INTRODUCTION: REVIEW OF BIG DATA SYSTEMS -- 1.2. UNDERSTANDING BIG DATA -- 1.3. TYPE OF DATA: TRANSACTIONAL OR ANALYTICAL -- 1.4. REQUIREMENTS AND CHALLENGES OF BIG DATA -- 1.5. CONCLUDING REMARKS -- 1.6. FURTHER READING -- 1.7. EXERCISE QUESTIONS -- Chapter 2: Architecture and Organization of Big Data Systems -- 2.1. ARCHITECTURE FOR BIG DATA SYSTEMS -- 2.2. ORGANIZATION OF BIG DATA SYSTEMS: CLUSTERS -- 2.3. CLASSIFICATION OF CLUSTERS: DISTRIBUTED MEMORY VS. SHARED MEMORY -- 2.4. CONCLUDING REMARKS -- 2.5. FURTHER READING -- 2.6. EXERCISE QUESTIONS -- Chapter 3: Cloud Computing for Big Data -- 3.1. CLOUD COMPUTING -- 3.2. VIRTUALIZATION -- 3.3. PROCESSOR VIRTUALIZATION -- 3.4. CONTAINERIZATION -- 3.5. VIRTUALIZATION OR CONTAINERIZATION -- 3.6. CLUSTER MANAGEMENT -- 3.7. FOG COMPUTING -- 3.8. EXAMPLES -- 3.9. CONCLUDING REMARKS -- 3.10. FURTHER READING -- 3.11. EXERCISE QUESTIONS -- Section II: Storage and Processing for Big Data -- Chapter 4: HADOOP: An Efficient Platform for Storing and Processing Big Data -- 4.1. REQUIREMENTS FOR PROCESSING AND STORING BIG DATA -- 4.2. HADOOP - THE BIG PICTURE -- 4.3. HADOOP DISTRIBUTED FILE SYSTEM -- 4.4. MAPREDUCE -- 4.5. HBASE -- 4.6. CONCLUDING REMARKS -- 4.7. FURTHER READING -- 4.8. EXERCISE QUESTIONS -- Chapter 5: Enhancements in Hadoop -- 5.1. ISSUES WITH HADOOP -- 5.2. YARN -- 5.3. PIG -- 5.4. HIVE -- 5.5. DREMEL -- 5.6. IMPALA -- 5.7. DRILL -- 5.8. DATA TRANSFER -- 5.9. AMBARI -- 5.10. CONCLUDING REMARKS -- 5.11. FURTHER READING -- 5.12. EXERCISE QUESTIONS -- Chapter 6: Spark -- 6.1. LIMITATIONS OF MAPREDUCE -- 6.2. INTRODUCTION TO SPARK.. - 6.3. SPARK CONCEPTS -- 6.4. SPARK SQL -- 6.5. SPARK MLLIB -- 6.6. STREAM-BASED SYSTEM -- 6.7. SPARK STREAMING -- 6.8. GRAPHX -- 6.9. CONCLUDING REMARKS -- 6.10. FURTHER READING -- 6.11. EXERCISE QUESTIONS -- Chapter 7: NoSQL Systems -- 7.1. INTRODUCTION -- 7.2. HANDLING BIG DATA SYSTEMS - PARALLEL RDBMS -- 7.3. EMERGENCE OF NOSQL SYSTEMS -- 7.4. KEY-VALUE DATABASE -- 7.5. DOCUMENT-ORIENTED DATABASE -- 7.6. COLUMN-ORIENTED DATABASE -- 7.7. GRAPH DATABASE -- 7.8. CONCLUDING REMARKS -- 7.9. FURTHER READING -- 7.10. EXERCISE QUESTIONS -- Chapter 8: NewSQL Systems -- 8.1. INTRODUCTION -- 8.2. TYPES OF NEWSQL SYSTEMS -- 8.3. FEATURES -- 8.4. NEWSQL SYSTEMS: CASE STUDIES -- 8.5. CONCLUDING REMARKS -- 8.6. FURTHER READING -- 8.7. EXERCISE QUESTIONS -- Section III: Networking, Security, and Privacy for Big Data -- Chapter 9: Networking for Big Data -- 9.1. NETWORK ARCHITECTURE FOR BIG DATA SYSTEMS -- 9.2. CHALLENGES AND REQUIREMENTS -- 9.3. NETWORK PROGRAMMABILITY AND SOFTWARE-DEFINED NETWORKING -- 9.4 LOW-LATENCY AND HIGHSPEED DATA TRANSFER -- 9.5. AVOIDING TCP INCAST - ACHIEVING LOWLATENCY AND HIGH-THROUGHPUT -- 9.6. FAULT TOLERANCE -- 9.7. CONCLUDING REMARKS -- 9.8. FURTHER READING -- 9.9. EXERCISE QUESTIONS -- Chapter 10: Security for Big Data -- 10.1. INTRODUCTION -- 10.2. SECURITY REQUIREMENTS -- 10.3. SECURITY: ATTACK TYPES AND MECHANISMS -- 10.4. ATTACK DETECTION AND PREVENTION -- 10.5. CONCLUDING REMARKS -- 10.6. FURTHER READING -- 10.7. EXERCISE QUESTIONS -- Chapter 11: Privacy for Big Data -- 11.1. INTRODUCTION -- 11.2. UNDERSTANDING BIG DATA AND PRIVACY -- 11.3. PRIVACY VIOLATIONS AND THEIR IMPACT -- 11.4. TYPES OF PRIVACY VIOLATIONS -- 11.5. PRIVACY PROTECTION SOLUTIONS AND THEIR LIMITATIONS -- 11.6. CONCLUDING REMARKS -- 11.7. FURTHER READING -- 11.8. EXERCISE QUESTIONS -- Section IV: Computation for Big Data.. - Chapter 12: High-Performance Computing for Big Data -- 12.1. INTRODUCTION -- 12.2. SCALABILITY: NEED FOR HPC -- 12.3. GRAPHIC PROCESSING UNIT -- 12.4. TENSOR PROCESSING UNIT -- 12.5. HIGH SPEED INTERCONNECTS -- 12.6. MESSAGE PASSING INTERFACE -- 12.7. OPENMP -- 12.8. OTHER FRAMEWORKS -- 12.9. CONCLUDING REMARKS -- 12.10. FURTHER READING -- 12.11. EXERCISE QUESTIONS -- Chapter 13: Deep Learning with Big Data -- 13.1. INTRODUCTION -- 13.2. FUNDAMENTALS -- 13.3. NEURAL NETWORK -- 13.4. TYPES OF DEEP NEURAL NETWORK -- 13.5. BIG DATA APPLICATIONS USING DEEP LEARNING -- 13.6. CONCLUDING REMARKS -- 13.7. FURTHER READING -- 13.8. EXERCISE QUESTIONS -- Section V: Case Studies and Future Trends -- Chapter 14: Big Data: Case Studies and Future Trends -- 14.1. GOOGLE EARTH ENGINE -- 14.2. FACEBOOK MESSAGES APPLICATION -- 14.3. HADOOP FOR REAL-TIME ANALYTICS -- 14.4. BIG DATA PROCESSING AT UBER -- 14.5. BIG DATA PROCESSING AT LINKEDIN -- 14.6. DISTRIBUTED GRAPH PROCESSING AT GOOGLE -- 14.7. FUTURE TRENDS -- 14.8. CONCLUDING REMARKS -- 14.9. FURTHER READING -- 14.10. EXERCISE QUESTIONS -- Bibliography -- Index.
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| ISBN | 0-429-15544-1. - 0-429-53157-5. - 1-4987-5271-3
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