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Classroom Contents
Runaway Complexity in Big Data Systems and a Plan to Stop It
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- 1 Introduction
- 2 What is a data system
- 3 Common sources of complexity
- 4 Human fault tolerance
- 5 Design for human error
- 6 Data loss
- 7 Mutability
- 8 Immutability
- 9 Normalization vs Denormalization
- 10 Denormalization
- 11 Schemas
- 12 Schemas are bad
- 13 Schemas are confusing
- 14 What is a schema
- 15 What is structural integrity
- 16 Preventing corruption
- 17 Detecting corruption
- 18 Preventing mistakes
- 19 Learning from experience
- 20 Why schemas are painful
- 21 My ideal schema tool
- 22 Apache Thrift
- 23 New Sequel
- 24 No Sequel
- 25 How would you build a better data system
- 26 What do we actually use data systems for
- 27 Data Systems
- 28 Example
- 29 Realtime Queries
- 30 Pre Computation
- 31 Pre Computation Example
- 32 Architecture
- 33 Functions
- 34 View
- 35 Batch Processing
- 36 MapReduce
- 37 BatchView Databases
- 38 BatchView Properties
- 39 BatchView Architecture
- 40 Batch Computation
- 41 RealTime Views
- 42 Lambda Architecture
- 43 Cap Theorem
- 44 Eventually Accurate
- 45 Maximizing Value
- 46 Tools
- 47 Land Architecture
- 48 Movement Mistakes
- 49 Normalization Personalization
- 50 The Future
- 51 Book
- 52 Performance
