fix(8.0): multi-valued array fields index every element (contains no longer misses)
addToIndex builds a fieldsMap from the extracted {field,value} entries, but
only __words__ accumulated — every other repeated field did fieldsMap[field]=value,
so a multi-valued field (tags:['a','b','c'] → three 'tags' entries from
extractIndexableFields) collapsed to last-value-wins. columnStore.addEntity
expands an array to one indexed entry per element, but it only ever received the
final scalar, so `contains` matched only the last element and missed the rest.
Accumulate any repeated non-__words__ field into an array before addEntity
(promote scalar→array on the second occurrence). __words__ keeps its always-array
special-case so its multiValue manifest flag stays set even for single-word docs.
find-unified-integration.test.ts → 0 failures (was 4):
- 'array contains' (A.4): now queries first/middle/last element — all match
(previously only the last-indexed element did).
- 'complete find workflow': $contains→contains (8.0 operator) AND fixed the test
premise — find() hard-ANDs vector∩graph∩metadata, and connected:{from:X} returns
X's NEIGHBOURS not X, so the graph anchor must be 'earth' (which the ML concept
relates to), not the concept itself. Multi-signal scores are reciprocal-rank
fusion (~1/61), not [0,1] cosine, so assert a positive fusion score, not >0.5.
- 'nonsense vector query': cosine search always returns nearest neighbours, so
assert the structural array/bound contract, not length===0 (a Tier-2 concern).
- 'hard-ANDs signals': a nonexistent connected.from is an empty graph signal that
zeros the intersection — assert length===0 (documented AND semantics), was >0.
1469 unit + full find-unified integration green.
This commit is contained in:
parent
009e50681e
commit
eccf42000b
2 changed files with 71 additions and 25 deletions
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@ -1434,13 +1434,31 @@ export class MetadataIndexManager implements MetadataIndexProvider {
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// Write to column store — the single write path for all indexed data.
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// Converts extracted fields into a map and feeds the column store.
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//
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// extractIndexableFields emits ONE {field,value} entry per array element for
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// a multi-valued field (e.g. tags:['a','b','c'] → three 'tags' entries). We
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// must accumulate every repeated field into an array, not just __words__:
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// columnStore.addEntity expands an array value to one indexed entry per
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// element, so a scalar overwrite (last-value-wins) would index only the final
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// element and `contains` would miss the rest.
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if (this.columnStore) {
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const entityIntId = this.idMapper.getOrAssign(id)
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const fieldsMap: Record<string, unknown> = {}
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for (const { field, value } of fields) {
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if (field === '__words__') {
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// Always an array (keeps the field's multiValue manifest flag set even
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// for a single-word document).
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if (!fieldsMap.__words__) fieldsMap.__words__ = []
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;(fieldsMap.__words__ as number[]).push(value)
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;(fieldsMap.__words__ as unknown[]).push(value)
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} else if (field in fieldsMap) {
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// Repeated field → multi-valued. Promote the scalar to an array on the
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// second occurrence, then accumulate.
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const existing = fieldsMap[field]
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if (Array.isArray(existing)) {
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;(existing as unknown[]).push(value)
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} else {
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fieldsMap[field] = [existing, value]
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}
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} else {
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fieldsMap[field] = value
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}
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@ -251,17 +251,19 @@ describe('Unified Find() Integration Tests', () => {
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})
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// 8.0 uses the BFO `contains` operator for array membership (not Mongo `$contains`).
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// Correct input: tags = ['test', 'integration', 'qa'], querying for 'test'.
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// Expected: the entity is returned (its tags array contains 'test').
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const results = await brain.find({
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where: { tags: { contains: 'test' } }
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})
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expect(results.length).toBeGreaterThan(0)
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results.forEach((result: any) => {
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expect(Array.isArray(result.entity.metadata?.tags)).toBe(true)
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expect(result.entity.metadata.tags).toContain('test')
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})
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// A.4 regression guard: query EVERY element — first ('test'), middle
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// ('integration'), and last ('qa'). Before the fix only the LAST element
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// was indexed (fieldsMap last-value-wins), so 'test'/'integration' missed.
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for (const tag of ['test', 'integration', 'qa']) {
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const results = await brain.find({
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where: { tags: { contains: tag } }
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})
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expect(results.length).toBeGreaterThan(0)
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results.forEach((result: any) => {
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expect(Array.isArray(result.entity.metadata?.tags)).toBe(true)
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expect(result.entity.metadata.tags).toContain(tag)
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})
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}
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})
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it('should support complex logical operators', async () => {
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@ -757,14 +759,24 @@ describe('Unified Find() Integration Tests', () => {
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describe('4. Edge Cases', () => {
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describe('Empty Results Handling', () => {
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it('should handle empty vector search results', async () => {
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it('should handle a nonsense vector query without error', async () => {
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// A pure vector query has no notion of "no match": cosine similarity
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// always ranks the corpus, so a nonsense string returns the nearest
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// neighbours (≤ limit), not an empty set. Tier-1 asserts the structural
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// contract (well-formed array, bounded by limit); whether a nonsense
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// query SHOULD rank low is a Tier-2 semantic-relevance concern. The
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// genuinely-empty cases are the graph/field tests below.
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const results = await brain.find({
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query: 'nonexistent_content_xyz123',
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limit: 5
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})
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expect(Array.isArray(results)).toBe(true)
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expect(results.length).toBe(0)
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expect(results.length).toBeLessThanOrEqual(5)
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results.forEach((r: any) => {
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expect(r.id).toBeDefined()
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expect(typeof r.score).toBe('number')
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})
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})
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it('should handle empty graph search results', async () => {
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@ -790,19 +802,23 @@ describe('Unified Find() Integration Tests', () => {
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expect(results.length).toBe(0)
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})
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it('should handle mixed empty and non-empty results', async () => {
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it('hard-ANDs signals — an empty graph signal zeros the intersection', async () => {
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// find() is a hard AND across its signals (vector ∩ graph ∩ metadata):
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// the result is the INTERSECTION, not a union. Here the vector ('person')
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// and field (age >= 25) signals match entities, but `connected.from` is a
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// nonexistent entity → empty graph set → the whole intersection is empty.
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// (For a soft RRF UNION ranking, use getTripleIntelligence().find().)
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const results = await brain.find({
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query: 'person', // Should find results
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query: 'person',
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connected: {
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from: 'nonexistent_entity' // Should find no results
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from: 'nonexistent_entity' // empty graph signal
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},
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where: { age: { gte: 25 } }, // Should find results
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where: { age: { gte: 25 } },
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limit: 5
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})
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expect(Array.isArray(results)).toBe(true)
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expect(results.length).toBeGreaterThan(0)
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// Should still return results from vector and field searches
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expect(results.length).toBe(0)
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})
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})
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@ -950,25 +966,37 @@ describe('Unified Find() Integration Tests', () => {
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type: VerbType.RelatedTo
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})
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// Perform unified search
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// Perform unified search. find() hard-ANDs its three signals (vector ∩
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// graph ∩ metadata), so the target entity must appear in ALL of them.
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// The graph anchor is 'earth' (NOT complexEntityId): a `connected:{from:X}`
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// filter returns X's NEIGHBOURS, never X itself, and we related the ML
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// concept → earth above, so earth's bidirectional neighbours include it.
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const results = await brain.find({
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query: 'artificial intelligence learning',
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connected: {
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from: complexEntityId,
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from: 'earth',
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direction: 'both'
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},
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where: {
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category: 'AI',
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tags: { $contains: 'AI' }
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// 8.0 array-membership operator is `contains` (not Mongo `$contains`).
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// A.4 fix: tags:['AI','ML','data science'] now indexes every element,
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// so `contains:'AI'` matches (previously only the last element was kept).
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tags: { contains: 'AI' }
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},
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limit: 5
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})
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expect(results.length).toBeGreaterThan(0)
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// Should find the complex entity with high relevance
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// The ML concept satisfies all three signals, so it is in the result set.
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const mlResult = results.find((r: any) => r.id === complexEntityId)
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expect(mlResult).toBeDefined()
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expect(mlResult!.score).toBeGreaterThan(0.5)
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// Multi-signal find() scores via reciprocal-rank fusion (k≈60), so the
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// score is a small fusion rank (~1/61), NOT a [0,1] cosine similarity —
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// asserting a relevance magnitude here is a Tier-2 concern. Tier-1 checks
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// only that a matched row carries a valid positive fusion score.
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expect(typeof mlResult!.score).toBe('number')
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expect(mlResult!.score).toBeGreaterThan(0)
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})
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})
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