Online release of Data-Oriented Design :
This is the free, online, reduced version. Some inessential chapters are excluded from this version, but in the spirit of this being an education resource, the essentials are present for anyone wanting to learn about data-oriented design.
Expect some odd formatting and some broken images and listings as this is auto generated and the Latex to html converters available are not perfect. If the source code listing is broken, you should be able to find the referenced source on github. If you like what you read here, consider purchasing the real paper book from here, as not only will it look a lot better, but it will help keep this version online for those who cannot afford to buy it. Please send any feedback to support@dataorienteddesign.com

Contents

• Data-Oriented Design
  • It's all about the data
  • Data is not the problem domain
  • Data and statistics
  • Data can change
  • How is data formed?
  • What can provide a computational framework for such complex data?
  • Conclusions and takeaways
  
  
• Relational Databases
  • Complex state
  • What can provide a computational framework for complex data?
  • Normalising your data
  • Normalisation
    • Primary keys
    • 1^st Normal Form
    • 2^nd Normal Form
    • 3^rd Normal Form
    • Boyce-Codd Normal Form
    • Domain Key / Knowledge
    • Reflections
  • Operations
  • Summing up
  • Stream Processing
  • Why does database technology matter?
  
  
• Existential Processing
  • Complexity
  • Debugging
  • Why use an if
  • Types of processing
  • Don't use booleans
  • Don't use enums quite as much
  • Prelude to polymorphism
  • Dynamic runtime polymorphism
  • Event handling
  
  
• Component Based Objects
  • Components in the wild
  • Away from the hierarchy
  • Towards managers
  • There is no entity
  
  
• Hierarchical Level of Detail and Implicit-state
  • Existence from Null to Infinity
  • Mementos
  • JIT mementos
  • Alternative axes
    • The true measure
    • Beyond space
  • Collective lodding - or how to reduce your instance count.
  
  
• Searching
  • Indexes
  • Data-oriented Lookup
  • Finding lowest or highest is a sorting problem
  • Finding random is a hash/tree issue
  
  
• Sorting
  • Do you need to?
  • Maintain by insertion sort or parallel merge sort
  • Sorting for your platform
  
  
• Optimisations and Implementations
  • When should we optimise?
  • Feedback
    • Know your limits
  • A strategy for optimisation
    • Define the problem
    • Measure
    • Analyse
    • Implement
    • Confirm
    • Summary
  • Tables
  • Transforms
  • Spatial sets for collisions
  • Lazy evaluation for the masses
  • Necessity, or not getting what you didn't ask for
  • Varying length sets
  • Joins as intersections
  • Data-driven techniques
    • SIMD
  • Structs of arrays
  
  
• Helping the compiler
  • Reducing order dependence
  • Reducing memory dependency
  • Write buffer awareness
  • Aliasing
  • Return value optimisation
  • Cache line utilisation
  • False sharing
  • Speculative execution awareness
  • Branch prediction
  • Don't get evicted
  • Auto vectorisation
  
  
• Maintenance and reuse
  • Cosmic hierarchies
  • Debugging
    • Lifetimes
    • Avoiding pointers
    • Bad State
  • Reusability
  • Reusable functions
  • Unit testing
  • Refactoring
  
  
• What's wrong?
  • The harm
  • Mapping the problem
  • Internalised state
  • Instance oriented development
  • Hierarchical design vs change
  • Divisions of labour
  • Reusable generic code

0