Projections

Declarative Projections in Cratis allow you to create read models from events stored in the event log. They provide different levels of complexity from simple auto-mapping to sophisticated hierarchical models with joins.

Projection recipes

Recipe	Description
Simple projection	Basic projection using AutoMap()
AutoMap	Automatic property mapping at different levels
Passive	In-memory projections for on-demand lookups
Set properties	Explicit property mapping and transformations
Children	Hierarchical data models with child collections
Joins	Cross-stream projections using joins
Functions	Mathematical operations and calculations
Composite keys	Multi-property key identification
Event context	Using event metadata in projections
FromEvery	Setting properties for all events in a projection
Initial values	Default values for read model properties
RemoveWithJoin	Cross-stream child removal
FromEventSequence	Sourcing events from specific event sequences
NotRewindable	Forward-only projections that cannot be replayed

Key concepts

Auto-mapping vs explicit mapping

• Auto-mapping: Automatically maps properties with matching names between events and read models
  • Use .AutoMap() in fluent projections (IProjectionFor<T>)
  • Use [FromEvent<TEvent>] in model-bound projections for the same functionality
• Explicit mapping: Gives you full control over property transformations and mappings
  • Use .Set(), .Add(), etc. in fluent projections
  • Use [SetFrom<TEvent>], [AddFrom<TEvent>], etc. in model-bound projections

Event handling

• Projections can handle multiple event types
• Each event type can have its own property mappings
• Properties are updated incrementally as events are processed

Keys and identification

• Event source ID is used as the default key for read models
• Child collections use custom identifiers for individual items
• Joins use keys to link data from different streams

Performance

• Projections are automatically maintained as events are appended
• The system handles indexing and query optimization
• Consider join complexity and update frequency when designing projections