Brainy 7.30.0 introduced a memory-derived synchronous cap on `find({ limit })`
to prevent OOM. The cap was sound in intent but ~4x too conservative in
calibration: assumed 100 KB per result while typical entity footprint is 7-10 KB
(384-dim float32 vector ≈ 1.5 KB + standard fields + metadata). On a 900 MB
free-memory box the cap derived to 9000 — breaking common safety-cap patterns
like `find({ type, where, limit: 10_000 })` that typically return 10-500
entities. Surfaced as a runtime regression with cascading 500s degrading
production dashboards.
Three concurrent fixes:
A. RECALIBRATE THE FORMULA
- src/utils/paramValidation.ts:175,196,212 — the three memory-derived priorities
(reservedQueryMemory / containerMemory / freeMemory) all divided by
100 * 1024 * 1024 (100 KB per result, ~10-15x over conservative). Replaced
with a new MAX_LIMIT_KB_PER_RESULT = 25 constant that matches observed
entity size.
- Result: 4 GB container cap goes 10_000 → 40_000; 2 GB cap goes 5_000 →
20_000; 900 MB free-memory cap goes 9_000 → ~36_000. 100k hard ceiling
unchanged. `maxQueryLimit` / `reservedQueryMemory` constructor overrides
unchanged in behavior.
B. TWO-TIER ENFORCEMENT (warn-then-throw)
- Below cap (limit <= maxLimit): silent pass, unchanged.
- Soft tier (maxLimit < limit <= 2 * maxLimit): NEW — one-time warning per
call site (dedup keyed on caller stack frame + limit value), query
proceeds. Pre-7.30.2 code that relied on the cap silently allowing typical
safety-cap limits keeps working; the warning teaches the recipe so consumers
can fix it intentionally.
- Hard tier (limit > 2 * maxLimit): throw with the same teaching message
format. Real OOM territory; the cap stops being a recommendation and becomes
a guardrail.
- The 2x soft margin absorbs typical safety-cap patterns (limit: 10_000
against a 9 K-cap box) without disabling OOM protection. Real OOM territory
on a JS in-memory brain is hundreds of thousands of results, not 10x the
safety cap.
C. IMPROVED ERROR / WARNING MESSAGE
- Same shape as the 7.30.1 enforcement-error messages: state the problem,
name the three escape valves (maxQueryLimit / reservedQueryMemory /
pagination), include caller location, link to docs.
- Extracted findCallerLocation() helper from brainy.ts to a new
src/utils/callerLocation.ts so both the subtype enforcement (7.30.1) and
the limit enforcement (7.30.2) share one implementation without circular
imports.
DOCS
- New docs/guides/find-limits.md (public: true) — full reference: why the cap
exists, the four memory sources the auto-config considers, the three escape
valves with when-to-use-which guidance, and an explicit "pagination is the
future-proof pattern" callout (8.0 may tighten the cap further; pagination
keeps working unchanged).
- docs/api/README.md find() entry gets a one-paragraph `limit` tip + pointer
to the new guide.
- RELEASES.md v7.30.2 entry.
TESTS
- New tests/integration/find-limits.test.ts (9 tests): below-cap silent pass;
soft-tier warns once per call site (dedup verified by exercising same vs.
different source lines via wrapper closures); soft-tier message format
(names all three escape valves + docs link); soft-tier message includes
caller location; hard-tier throws; hard-tier message format same as
soft-tier; consumer maxQueryLimit override raises the cap and shifts both
tiers accordingly; pre-7.30.2 regression scenario explicitly covered.
- tests/unit/utils/memoryLimits.test.ts — 4 tests updated for the recalibrated
cap values (hardcoded expected numbers bumped 4x to match new 25 KB/result
assumption).
- tests/unit/utils/paramValidation.test.ts — auto-limit test extended to cover
the three-tier semantics (below-cap pass / soft-tier silent / hard-tier
throw).
- Existing suites unchanged: subtype-and-facets 26/26, verb-subtype-and-
enforcement 30/30, strict-mode-self-test 13/13. Unit 1468/1468.
CORTEX COMPATIBILITY
- Zero Cortex changes required. Every change is JS-side: formula recalibration
runs in ValidationConfig.constructor(), two-tier enforcement runs in
validateFindParams(), both fire before any storage / index / Cortex call.
- The new guide notes that Brainy 8.0's Datomic-style Db.find() may tighten
per-call limits to keep snapshot semantics cheap; pagination remains the
pattern that's guaranteed to keep working.
REPO-WIDE CLEANUP
Brainy is the only Soulcraft project that is open source. This commit also
scrubs closed-source product names and product-specific class/field references
from every tracked file in the repo (src/, docs/, tests/, RELEASES.md,
CHANGELOG.md). Consumer-reported bugs, regression scenarios, and release
notes now refer to "a consumer", "a downstream application", "a production
deployment", or "an internal report" — never to the named product. Two
product-named test files renamed to neutral diagnostic names. CLAUDE.md gains
a project-level guard rule documenting the policy and an example list of the
identifiers that may not appear in tracked code.
Verification
- npx tsc --noEmit: clean
- npm test: 1468 / 1468 unit
- All four integration subtype + verb + strict + find-limits suites: 78/78
- npm run build: clean
- Closed-source product reference audit: clean
159 lines
5 KiB
TypeScript
159 lines
5 KiB
TypeScript
import { describe, it, expect, beforeEach } from 'vitest'
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import { Brainy } from '../../src/brainy.js'
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import { VerbType } from '../../src/types/graphTypes.js'
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/**
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* Regression test for v5.7.0 deadlock bug
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*
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* BUG DESCRIPTION:
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* v5.7.0 introduced a circular dependency deadlock during GraphAdjacencyIndex initialization:
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* - GraphAdjacencyIndex.rebuild() calls storage.getVerbs()
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* - storage.getVerbsBySource_internal() calls getGraphIndex()
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* - getGraphIndex() is waiting for rebuild() to complete
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* - DEADLOCK: Each waits for the other
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*
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* SYMPTOMS:
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* - ALL imports hang at "Reading Data Structure" stage
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* - brain.add() operations take 12+ seconds per entity (50x slower)
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* - No errors thrown - infinite wait
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* - Process continues (heartbeats) but makes no progress
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*
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* FIX (v5.7.1):
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* Reverted storage internals (getVerbsBySource_internal, getVerbsByTarget_internal)
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* to v5.6.3 implementation - no getGraphIndex() calls from storage layer.
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*
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* TEST STRATEGY:
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* 1. Create entities with relationships (triggers GraphAdjacencyIndex lazy init)
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* 2. Force rebuild by accessing graph operations
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* 3. Verify completes in <1 second (not 760+ seconds)
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*/
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describe('v5.7.0 Deadlock Regression', () => {
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let brain: Brainy
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beforeEach(async () => {
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brain = new Brainy({ storage: { type: 'memory' } })
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await brain.init()
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})
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it('should not deadlock during GraphAdjacencyIndex rebuild with existing verbs', async () => {
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// Create 10 entities
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const entities = []
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for (let i = 0; i < 10; i++) {
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const id = await brain.add({
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data: `Entity ${i}`,
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type: 'thing',
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metadata: { index: i }
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})
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entities.push(id)
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}
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// Create relationships between them (triggers GraphAdjacencyIndex)
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for (let i = 0; i < 9; i++) {
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await brain.relate({
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from: entities[i],
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to: entities[i + 1],
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type: VerbType.RelatedTo
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})
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}
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// This should complete in <1 second (not hang forever)
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const start = Date.now()
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// Force GraphAdjacencyIndex usage by querying relationships
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const relations = await brain.getRelations({ from: entities[0] })
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const elapsed = Date.now() - start
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// Verify no deadlock
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expect(elapsed).toBeLessThan(1000)
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expect(relations.length).toBeGreaterThan(0)
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})
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it('should handle imports without 12+ second delays per entity', async () => {
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// Simulate import workflow (like A consumer's Excel import)
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const start = Date.now()
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// Import 5 entities with relationships
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const importedEntities = []
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for (let i = 0; i < 5; i++) {
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const id = await brain.add({
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data: `Imported Entity ${i}`,
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type: 'person',
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metadata: {
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importId: 'test-import-001',
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sourceRow: i
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}
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})
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importedEntities.push(id)
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}
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// Add relationships
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for (let i = 0; i < 4; i++) {
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await brain.relate({
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from: importedEntities[i],
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to: importedEntities[i + 1],
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type: VerbType.Knows
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})
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}
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const elapsed = Date.now() - start
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// In v5.7.0, this took 12+ seconds per entity (60+ seconds total)
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// In v5.7.1, should complete in <5 seconds for 5 entities
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expect(elapsed).toBeLessThan(5000)
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// Verify all entities were created
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for (const id of importedEntities) {
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const entity = await brain.get(id)
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expect(entity).toBeDefined()
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}
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})
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it('should allow GraphAdjacencyIndex rebuild without circular dependency', async () => {
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// Create initial data
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const entity1 = await brain.add({ data: 'Node A', type: 'thing' })
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const entity2 = await brain.add({ data: 'Node B', type: 'thing' })
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const entity3 = await brain.add({ data: 'Node C', type: 'thing' })
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await brain.relate({ from: entity1, to: entity2, type: VerbType.RelatedTo })
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await brain.relate({ from: entity2, to: entity3, type: VerbType.RelatedTo })
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// Accessing storage internals should not cause deadlock
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// GraphAdjacencyIndex initialization should complete successfully
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const start = Date.now()
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// This would trigger initialization if not already done
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const relations = await brain.getRelations({ from: entity1 })
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const elapsed = Date.now() - start
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// Should be fast (no deadlock, no 12s delays)
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expect(elapsed).toBeLessThan(500)
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expect(relations).toHaveLength(1)
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expect(relations[0].to).toBe(entity2)
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})
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it('should handle multiple concurrent adds without deadlock', async () => {
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// Simulate concurrent entity creation (like batch import)
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const start = Date.now()
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const promises = []
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for (let i = 0; i < 10; i++) {
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promises.push(
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brain.add({
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data: `Concurrent Entity ${i}`,
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type: 'thing',
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metadata: { batch: true, index: i }
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})
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)
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}
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const ids = await Promise.all(promises)
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const elapsed = Date.now() - start
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// Should complete quickly (no 12s per entity delays)
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// 10 entities should take <2 seconds, not 120+ seconds
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expect(elapsed).toBeLessThan(2000)
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expect(ids).toHaveLength(10)
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})
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})
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