Add 'percentile' (with a 'p' fraction in [0,1]) and 'distinctCount' to the
aggregation engine. Both are exact, computed from a per-metric value multiset
(MetricState.valueCounts) maintained incrementally and delete-safe; percentile
uses numpy-linear interpolation. The multiset is JSON-serializable so results
survive persistence. 35 aggregation unit tests pass.
Add a write-time incremental aggregation engine that maintains running
totals on every add/update/delete for O(1) read performance. Integrates
into brain.find({ aggregate }) for a unified query API.
Core features:
- AggregationIndex with defineAggregate()/removeAggregate() API
- Five aggregation operations: SUM, COUNT, AVG, MIN, MAX
- GROUP BY with multiple dimensions including time windows
- Time window bucketing: hour, day, week, month, quarter, year, custom
- Materialization of results as NounType.Measurement entities
- Debounced persistence of definitions and state to storage
- Definition change detection via FNV-1a hashing with auto-rebuild
- Infinite loop prevention for materialized entities
- 'aggregation' plugin provider key for native acceleration
- Lazy initialization (created on first defineAggregate() call)
- 73 tests (unit + integration) covering all functionality
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
