Copyright
Brief Table of Contents
Table of Contents
Preface
Acknowledgments
About this Book
Chapter 1. A new paradigm for Big Data
1.1. How this book is structured
1.2. Scaling with a traditional database
1.2.1. Scaling with a queue
1.2.2. Scaling by sharding the database
1.2.3. Fault-tolerance issues begin
1.2.4. Corruption issues
1.2.5. What went wrong?
1.2.6. How will Big Data techniques help?
1.3. NoSQL is not a panacea
1.4. First principles
1.5. Desired properties of a Big Data system
1.5.1. Robustness and fault tolerance
1.5.2. Low latency reads and updates
1.5.3. Scalability
1.5.4. Generalization
1.5.5. Extensibility
1.5.6. Ad hoc queries
1.5.7. Minimal maintenance
1.5.8. Debuggability
1.6. The problems with fully incremental architectures
1.6.1. Operational complexity
1.6.2. Extreme complexity of achieving eventual consistency
1.6.3. Lack of human-fault tolerance
1.6.4. Fully incremental solution vs. Lambda Architecture solution
1.7. Lambda Architecture
1.7.1. Batch layer
1.7.2. Serving layer
1.7.3. Batch and serving layers satisfy almost all properties
1.7.4. Speed layer
1.8. Recent trends in technology