David Snelling
21d02d3bae
nounCountsByType (read by stats().entitiesByType / counts.byTypeEnum) was incremented in saveNoun_internal(), which runs on every noun write — including the HNSW index re-saving a node whenever its neighbor links change. So per-type counts grew with graph connectivity instead of entity count (an internal report saw 8 documents read as 44). Moved the increment into saveNounMetadata_internal(), gated on isNew + visibility, exactly parallel to the authoritative total; the visibility-flip path adjusts it in lockstep too. Tests: tests/unit/storage/stats-count-accuracy.test.ts (30 dense-type entities -> exactly 30 across stats/counts/getNounCount) + de-theatricalized the >=2 assertion in brainy-core.unit.test.ts to exact equality. Build green; 1455 unit green. Part of the 8.0 readiness audit Phase 1; cold-reopen count rehydration is still WIP.
58 lines
2.6 KiB
TypeScript
58 lines
2.6 KiB
TypeScript
/**
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* @module tests/unit/storage/stats-count-accuracy
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* @description Regression for per-type count inflation. `nounCountsByType` (read by
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* `brain.stats().entitiesByType` and `counts.byTypeEnum`) used to be incremented in
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* `saveNoun_internal()`, which runs on EVERY noun write — including the HNSW index
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* re-saving a node whenever its neighbor links change. So the per-type counts grew
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* with graph connectivity rather than entity count (an internal report saw 8
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* documents read as 44). The counter is now maintained in `saveNounMetadata_internal()`
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* gated on `isNew` + visibility, exactly parallel to the authoritative total — so the
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* per-type counts must equal the entity count EXACTLY, no matter how dense the graph.
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*
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* These assert exact equality on purpose: the prior `toBeGreaterThanOrEqual` style
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* passed for any inflated value and masked the bug.
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*/
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import { describe, it, expect } from 'vitest'
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import { Brainy } from '../../../src/brainy.js'
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import { NounType } from '../../../src/types/graphTypes.js'
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describe('per-type count accuracy (HNSW re-save inflation)', () => {
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it('stats()/counts report the EXACT entity count for a single dense type', async () => {
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const brain = new Brainy({ requireSubtype: false, storage: { type: 'memory' } })
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await brain.init()
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try {
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// Enough nodes that HNSW links each new node to existing neighbors and
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// re-saves them — the exact path that used to double-count.
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const N = 30
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for (let i = 0; i < N; i++) {
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await brain.add({ data: { name: `person ${i}` }, type: NounType.Person })
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}
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const stats = await brain.stats()
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expect(stats.entityCount).toBe(N)
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expect(stats.entitiesByType[NounType.Person]).toBe(N)
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expect(brain.counts.byTypeEnum(NounType.Person)).toBe(N)
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expect(await brain.getNounCount()).toBe(N)
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} finally {
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await brain.close()
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}
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})
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it('keeps per-type counts exact across multiple types', async () => {
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const brain = new Brainy({ requireSubtype: false, storage: { type: 'memory' } })
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await brain.init()
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try {
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for (let i = 0; i < 12; i++) await brain.add({ data: { n: `p${i}` }, type: NounType.Person })
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for (let i = 0; i < 7; i++) await brain.add({ data: { n: `d${i}` }, type: NounType.Document })
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const stats = await brain.stats()
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expect(stats.entitiesByType[NounType.Person]).toBe(12)
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expect(stats.entitiesByType[NounType.Document]).toBe(7)
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expect(stats.entityCount).toBe(19)
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expect(brain.counts.byTypeEnum(NounType.Person)).toBe(12)
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expect(brain.counts.byTypeEnum(NounType.Document)).toBe(7)
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} finally {
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await brain.close()
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}
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})
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})
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