feat(8.0)!: delete fork/branch/commit/history/versions — superseded by the Db API

The COW version-control surface (fork, branches, checkout, commit,
getHistory/streamHistory, asOfCommit, brain.versions) is gone, along with
its subsystems: src/versioning/, the COW object store (CommitLog,
CommitObject, RefManager, TreeObject), HistoricalStorageAdapter, and the
TypeAwareHNSWIndex path it kept alive. The Db API (now/transact/asOf/
with/persist/restore) is the one versioning model in 8.0.

Survivors and replacements:
- BlobStorage survives (the VFS stores file content through it), relocated
  to src/storage/blobStorage.ts with binaryDataCodec.ts; its adapter
  interface is now BlobStoreAdapter, slimmed to the consumed surface
  (write/read/has/delete/getMetadata + MIME-aware compression policy).
- brain.migrate() backup branches are replaced by persist-before-migrate:
  MigrateOptions.backupTo persists a hard-link snapshot of the current
  generation before any transform runs; MigrationResult.backupPath reports
  it, and brain.restore(path) brings it back wholesale.
- CLI: cow.ts (fork/branch/checkout/history/migrate) is replaced by
  snapshot.ts — snapshot <path>, restore <path>, history (tx-log),
  generation.
- New public read API: brain.transactionLog({limit}) exposes the reified
  tx-log (generation/timestamp/meta, newest first) that backs the CLI
  history command; TxLogEntry is exported.

Tests: superseded suites deleted; fork/commit blocks excised from shared
suites; BlobStorage tests relocated + reworked against the slimmed store;
migration tests now prove the backupTo snapshot/restore round trip; new
transactionLog coverage in db-mvcc.
This commit is contained in:
David Snelling 2026-06-10 15:22:47 -07:00
parent 431cd64406
commit 8f93add705
64 changed files with 1444 additions and 16313 deletions

View file

@ -59,10 +59,6 @@ export class JsHnswVectorIndex implements VectorIndexProvider {
// save, so the migration converges under live traffic with no big-bang.
private connectionsCodec: ConnectionsCodec | null = null
// COW (Copy-on-Write) support
private cowEnabled: boolean = false
private cowModifiedNodes: Set<string> = new Set()
private cowParent: JsHnswVectorIndex | null = null
// Deferred HNSW persistence for cloud storage performance
// In deferred mode, HNSW connections are only persisted on flush/close
@ -301,99 +297,6 @@ export class JsHnswVectorIndex implements VectorIndexProvider {
return this.persistMode
}
/**
* Enable COW (Copy-on-Write) mode - Instant fork via shallow copy
*
* Snowflake-style instant fork: O(1) shallow copy of Maps, lazy deep copy on write.
*
* @param parent - Parent HNSW index to copy from
*
* Performance:
* - Fork time: <10ms for 1M+ nodes (just copies Map references)
* - Memory: Shared reads, only modified nodes duplicated (~10-20% overhead)
* - Reads: Same speed as parent (shared data structures)
*
* @example
* ```typescript
* const parent = new JsHnswVectorIndex(config)
* // ... parent has 1M nodes ...
*
* const fork = new JsHnswVectorIndex(config)
* fork.enableCOW(parent) // <10ms - instant!
*
* // Reads share data
* await fork.search(query) // Fast, uses parent's data
*
* // Writes trigger COW
* await fork.addItem(newItem) // Deep copies only modified nodes
* ```
*/
public enableCOW(parent: JsHnswVectorIndex): void {
this.cowEnabled = true
this.cowParent = parent
// Shallow copy Maps - O(1) per Map, just copies references
// All nodes/connections are shared until first write
this.nouns = new Map(parent.nouns)
this.highLevelNodes = new Map()
for (const [level, nodeSet] of parent.highLevelNodes.entries()) {
this.highLevelNodes.set(level, new Set(nodeSet))
}
// Copy scalar values
this.entryPointId = parent.entryPointId
this.maxLevel = parent.maxLevel
this.dimension = parent.dimension
// Share cache (COW at cache level)
this.unifiedCache = parent.unifiedCache
// Share config and distance function
this.config = parent.config
this.distanceFunction = parent.distanceFunction
this.useParallelization = parent.useParallelization
prodLog.info(`HNSW COW enabled: ${parent.nouns.size} nodes shallow copied`)
}
/**
* Ensure node is copied before modification (lazy COW)
*
* Deep copies a node only when first modified. Subsequent modifications
* use the already-copied node.
*
* @param nodeId - Node ID to ensure is copied
* @private
*/
private ensureCOW(nodeId: string): void {
if (!this.cowEnabled) return
if (this.cowModifiedNodes.has(nodeId)) return // Already copied
const original = this.nouns.get(nodeId)
if (!original) return
// Deep copy connections Map (separate Map + Sets for each level)
const connectionsCopy = new Map<number, Set<string>>()
for (const [level, ids] of original.connections.entries()) {
connectionsCopy.set(level, new Set(ids))
}
// Deep copy node
const nodeCopy: HNSWNoun = {
id: original.id,
vector: [...original.vector], // Deep copy vector array
connections: connectionsCopy,
level: original.level,
// Copy SQ8 quantized data if present
quantizedVector: original.quantizedVector ? new Uint8Array(original.quantizedVector) : undefined,
codebookMin: original.codebookMin,
codebookMax: original.codebookMax
}
this.nouns.set(nodeId, nodeCopy)
this.cowModifiedNodes.add(nodeId)
}
/**
* Calculate distances between a query vector and multiple vectors in parallel
* This is used to optimize performance for search operations
@ -602,8 +505,6 @@ export class JsHnswVectorIndex implements VectorIndexProvider {
continue
}
// COW: Ensure neighbor is copied before modification
this.ensureCOW(neighborId)
noun.connections.get(level)!.add(neighborId)
@ -965,16 +866,12 @@ export class JsHnswVectorIndex implements VectorIndexProvider {
return false
}
// COW: Ensure node is copied before modification
this.ensureCOW(id)
const noun = this.nouns.get(id)!
// Remove connections to this noun from all neighbors
for (const [level, connections] of noun.connections.entries()) {
for (const neighborId of connections) {
// COW: Ensure neighbor is copied before modification
this.ensureCOW(neighborId)
const neighbor = this.nouns.get(neighborId)
if (!neighbor) {
@ -994,8 +891,6 @@ export class JsHnswVectorIndex implements VectorIndexProvider {
for (const [nounId, otherNoun] of this.nouns.entries()) {
if (nounId === id) continue // Skip the noun being removed
// COW: Ensure noun is copied before modification
this.ensureCOW(nounId)
for (const [level, connections] of otherNoun.connections.entries()) {
if (connections.has(id)) {
@ -1881,8 +1776,6 @@ export class JsHnswVectorIndex implements VectorIndexProvider {
* Ensure a noun doesn't have too many connections at a given level
*/
private async pruneConnections(noun: HNSWNoun, level: number): Promise<void> {
// COW: Ensure noun is copied before modification
this.ensureCOW(noun.id)
const connections = noun.connections.get(level)!
if (connections.size <= this.config.M) {

View file

@ -1,763 +0,0 @@
/**
* Type-Aware HNSW Index - Phase 2 Billion-Scale Optimization
*
* Maintains separate HNSW graphs per entity type for massive memory savings:
* - Memory @ 1B scale: PROJECTED 384GB 50GB (-87% from architectural analysis, not yet benchmarked)
* - Query speed: PROJECTED 10x faster for single-type queries (not yet benchmarked)
* - Storage: Already type-first from Phase 1a
*
* Architecture:
* - One JsHnswVectorIndex per NounType (42 total)
* - Lazy initialization (indexes created on first use)
* - Type routing for optimal performance
* - Falls back to multi-type search when type unknown
*/
import { JsHnswVectorIndex } from './hnswIndex.js'
import {
DistanceFunction,
HNSWConfig,
Vector,
VectorDocument
} from '../coreTypes.js'
import { NounType, NOUN_TYPE_COUNT, TypeUtils } from '../types/graphTypes.js'
import { euclideanDistance } from '../utils/index.js'
import type { BaseStorage } from '../storage/baseStorage.js'
import { prodLog } from '../utils/logger.js'
// Default HNSW parameters (same as JsHnswVectorIndex)
const DEFAULT_CONFIG: HNSWConfig = {
M: 16,
efConstruction: 200,
efSearch: 50,
ml: 16
}
/**
* Type-aware HNSW statistics
*/
export interface TypeAwareHNSWStats {
totalNodes: number
totalMemoryMB: number
typeCount: number
typeStats: Map<NounType, {
nodeCount: number
memoryMB: number
maxLevel: number
entryPointId: string | null
}>
memoryReductionPercent: number
estimatedMonolithicMemoryMB: number
}
/**
* TypeAwareHNSWIndex - Separate HNSW graphs per entity type
*
* Phase 2 of billion-scale optimization roadmap.
* PROJECTED: Reduces HNSW memory by 87% @ billion scale (calculated from architecture, not yet benchmarked).
*/
export class TypeAwareHNSWIndex {
// One HNSW index per noun type (lazy initialization)
private indexes: Map<NounType, JsHnswVectorIndex> = new Map()
// Configuration
private config: HNSWConfig
private distanceFunction: DistanceFunction
private storage: BaseStorage | null
private useParallelization: boolean
private persistMode: 'immediate' | 'deferred'
/**
* Create a new TypeAwareHNSWIndex
*
* @param config HNSW configuration (M, efConstruction, efSearch, ml)
* @param distanceFunction Distance function (default: euclidean)
* @param options Additional options (storage, parallelization, persistMode)
*/
constructor(
config: Partial<HNSWConfig> = {},
distanceFunction: DistanceFunction = euclideanDistance,
options: { useParallelization?: boolean; storage?: BaseStorage; persistMode?: 'immediate' | 'deferred' } = {}
) {
this.config = { ...DEFAULT_CONFIG, ...config }
this.distanceFunction = distanceFunction
this.storage = options.storage || null
this.useParallelization =
options.useParallelization !== undefined
? options.useParallelization
: true
this.persistMode = options.persistMode || 'immediate'
prodLog.info('TypeAwareHNSWIndex initialized (Phase 2: Type-Aware HNSW)')
}
/**
* Enable COW (Copy-on-Write) mode - Instant fork via shallow copy
*
* Propagates enableCOW() to all underlying type-specific HNSW indexes.
* Each index performs O(1) shallow copy of its own data structures.
*
* @param parent - Parent TypeAwareHNSWIndex to copy from
*/
public enableCOW(parent: TypeAwareHNSWIndex): void {
// Shallow copy indexes Map
this.indexes = new Map(parent.indexes)
// Enable COW on each underlying type-specific index
for (const [type, parentIndex] of parent.indexes.entries()) {
const childIndex = new JsHnswVectorIndex(this.config, this.distanceFunction, {
useParallelization: this.useParallelization,
storage: this.storage || undefined,
persistMode: this.persistMode
})
childIndex.enableCOW(parentIndex)
this.indexes.set(type, childIndex)
}
prodLog.info(`TypeAwareHNSWIndex COW enabled: ${parent.indexes.size} type-specific indexes shallow copied`)
}
/**
* Flush dirty HNSW data to storage for all type-specific indexes
*
* In deferred persistence mode, HNSW connections are tracked as dirty but not
* immediately persisted. Call flush() to persist all pending changes across
* all type-specific indexes.
*
* @returns Total number of nodes flushed across all indexes
*/
public async flush(): Promise<number> {
if (this.indexes.size === 0) {
return 0
}
const flushPromises = Array.from(this.indexes.values()).map(index =>
index.flush()
)
const results = await Promise.all(flushPromises)
const totalFlushed = results.reduce((sum, count) => sum + count, 0)
if (totalFlushed > 0) {
prodLog.info(`[TypeAwareHNSW] Flushed ${totalFlushed} dirty nodes across ${this.indexes.size} type indexes`)
}
return totalFlushed
}
/**
* Get the total number of dirty (unpersisted) nodes across all type-specific indexes
*/
public getDirtyNodeCount(): number {
let total = 0
for (const index of this.indexes.values()) {
total += index.getDirtyNodeCount()
}
return total
}
/**
* Get the current persist mode
*/
public getPersistMode(): 'immediate' | 'deferred' {
return this.persistMode
}
/**
* Switch persist mode at runtime. Propagates to all existing type-specific indexes.
* Used by addMany() to defer persistence during batch operations.
*/
public setPersistMode(mode: 'immediate' | 'deferred'): void {
this.persistMode = mode
for (const index of this.indexes.values()) {
if (typeof (index as any).setPersistMode === 'function') {
(index as any).setPersistMode(mode)
}
}
}
/**
* Get or create HNSW index for a specific type (lazy initialization)
*
* Indexes are created on-demand to save memory.
* Only types with entities get an index.
*
* @param type The noun type
* @returns JsHnswVectorIndex for this type
*/
private getIndexForType(type: NounType): JsHnswVectorIndex {
// Validate type is a valid NounType
const typeIndex = TypeUtils.getNounIndex(type)
if (typeIndex === undefined || typeIndex === null || typeIndex < 0) {
throw new Error(
`Invalid NounType: ${type}. Must be one of the 42 defined types.`
)
}
if (!this.indexes.has(type)) {
prodLog.info(`Creating HNSW index for type: ${type}`)
const index = new JsHnswVectorIndex(this.config, this.distanceFunction, {
useParallelization: this.useParallelization,
storage: this.storage || undefined,
persistMode: this.persistMode
})
this.indexes.set(type, index)
}
const index = this.indexes.get(type)
if (!index) {
throw new Error(
`Unexpected: Index for type ${type} not found after creation`
)
}
return index
}
/**
* Add a vector to the type-aware index
*
* Routes to the correct type's HNSW graph.
*
* @param item Vector document to add
* @param type The noun type (required for routing)
* @returns The item ID
*/
public async addItem(item: VectorDocument, type: NounType): Promise<string> {
if (!item || !item.vector) {
throw new Error(
'Invalid VectorDocument: item or vector is null/undefined'
)
}
if (!type) {
throw new Error('Type is required for type-aware indexing')
}
const index = this.getIndexForType(type)
return await index.addItem(item)
}
/**
* Search for nearest neighbors (type-aware)
*
* **Single-type search** (fast path):
* ```typescript
* await index.search(queryVector, 10, 'person')
* // Searches only person graph (100M nodes instead of 1B)
* ```
*
* **Multi-type search**:
* ```typescript
* await index.search(queryVector, 10, ['person', 'organization'])
* // Searches person + organization, merges results
* ```
*
* **All-types search** (fallback):
* ```typescript
* await index.search(queryVector, 10)
* // Searches all 42 graphs (slower but comprehensive)
* ```
*
* @param queryVector Query vector
* @param k Number of results
* @param type Type or types to search (undefined = all types)
* @param filter Optional filter function
* @returns Array of [id, distance] tuples sorted by distance
*/
public async search(
queryVector: Vector,
k: number = 10,
type?: NounType | NounType[],
filter?: (id: string) => Promise<boolean>,
options?: { rerank?: { multiplier: number }; candidateIds?: string[] }
): Promise<Array<[string, number]>> {
// Single-type search (fast path)
if (type && typeof type === 'string') {
const index = this.getIndexForType(type)
return await index.search(queryVector, k, filter, options)
}
// Multi-type search (handle empty array edge case)
if (type && Array.isArray(type) && type.length > 0) {
return await this.searchMultipleTypes(queryVector, k, type, filter, options)
}
// All-types search (slowest path + empty array fallback)
return await this.searchAllTypes(queryVector, k, filter, options)
}
/**
* Search across multiple specific types
*
* @param queryVector Query vector
* @param k Number of results
* @param types Array of types to search
* @param filter Optional filter function
* @returns Merged and sorted results
*/
private async searchMultipleTypes(
queryVector: Vector,
k: number,
types: NounType[],
filter?: (id: string) => Promise<boolean>,
options?: { rerank?: { multiplier: number }; candidateIds?: string[] }
): Promise<Array<[string, number]>> {
const allResults: Array<[string, number]> = []
// Search each specified type
for (const type of types) {
if (this.indexes.has(type)) {
const index = this.indexes.get(type)!
const results = await index.search(queryVector, k, filter, options)
allResults.push(...results)
}
}
// Merge and sort by distance
allResults.sort((a, b) => a[1] - b[1])
// Return top k
return allResults.slice(0, k)
}
/**
* Search across all types (fallback for type-agnostic queries)
*
* This is the slowest path, but provides comprehensive results.
* Used when type cannot be inferred from query.
*
* @param queryVector Query vector
* @param k Number of results
* @param filter Optional filter function
* @returns Merged and sorted results from all types
*/
private async searchAllTypes(
queryVector: Vector,
k: number,
filter?: (id: string) => Promise<boolean>,
options?: { rerank?: { multiplier: number }; candidateIds?: string[] }
): Promise<Array<[string, number]>> {
const allResults: Array<[string, number]> = []
// Search each type's graph
for (const [type, index] of this.indexes.entries()) {
const results = await index.search(queryVector, k, filter, options)
allResults.push(...results)
}
// Merge and sort by distance
allResults.sort((a, b) => a[1] - b[1])
// Return top k
return allResults.slice(0, k)
}
/**
* Remove an item from the index
*
* @param id Item ID to remove
* @param type The noun type (required for routing)
* @returns True if item was removed, false if not found
*/
public async removeItem(id: string, type: NounType): Promise<boolean> {
const index = this.indexes.get(type)
if (!index) {
return false // Type has no index (no items ever added)
}
return await index.removeItem(id)
}
/**
* Get total number of items across all types
*
* @returns Total item count
*/
public size(): number {
let total = 0
for (const index of this.indexes.values()) {
total += index.size()
}
return total
}
/**
* Get number of items for a specific type
*
* @param type The noun type
* @returns Item count for this type
*/
public sizeForType(type: NounType): number {
const index = this.indexes.get(type)
return index ? index.size() : 0
}
/**
* Clear all indexes
*/
public clear(): void {
for (const index of this.indexes.values()) {
index.clear()
}
this.indexes.clear()
}
/**
* Clear index for a specific type
*
* @param type The noun type to clear
*/
public clearType(type: NounType): void {
const index = this.indexes.get(type)
if (index) {
index.clear()
this.indexes.delete(type)
}
}
/**
* Get configuration
*
* @returns HNSW configuration
*/
public getConfig(): HNSWConfig {
return { ...this.config }
}
/**
* Get distance function
*
* @returns Distance function
*/
public getDistanceFunction(): DistanceFunction {
return this.distanceFunction
}
/**
* Set parallelization (applies to all indexes)
*
* @param useParallelization Whether to use parallelization
*/
public setUseParallelization(useParallelization: boolean): void {
this.useParallelization = useParallelization
for (const index of this.indexes.values()) {
index.setUseParallelization(useParallelization)
}
}
/**
* Get parallelization setting
*
* @returns Whether parallelization is enabled
*/
public getUseParallelization(): boolean {
return this.useParallelization
}
/**
* Rebuild HNSW indexes from storage (type-aware)
*
* CRITICAL: This implementation uses type-filtered pagination to avoid
* loading ALL entities for each type (which would be 42 billion reads @ 1B scale).
*
* Can rebuild all types or specific types.
* Much faster than rebuilding a monolithic index.
*
* @param options Rebuild options
*/
public async rebuild(
options: {
types?: NounType[] // Rebuild specific types (undefined = all types)
batchSize?: number // Entities per batch
onProgress?: (type: NounType, loaded: number, total: number) => void
} = {}
): Promise<void> {
if (!this.storage) {
prodLog.warn('TypeAwareHNSW rebuild skipped: no storage adapter')
return
}
const batchSize = options.batchSize || 1000
// Determine which types to rebuild
const typesToRebuild = options.types || this.getAllNounTypes()
prodLog.info(
`Rebuilding ${typesToRebuild.length} type-aware HNSW indexes from persisted data...`
)
// Clear all indexes we're rebuilding
for (const type of typesToRebuild) {
const index = this.getIndexForType(type)
;(index as any).nouns.clear()
}
// Determine preloading strategy (adaptive caching) for entire dataset
const stats = await this.storage.getStatistics()
const entityCount = stats?.totalNodes || 0
const vectorMemory = entityCount * 1536 // 384 dims × 4 bytes
// Use first index's cache (they all share the same UnifiedCache)
const firstIndex = this.getIndexForType(typesToRebuild[0])
const cacheStats = (firstIndex as any).unifiedCache.getStats()
const availableCache = cacheStats.maxSize * 0.80
const shouldPreload = vectorMemory < availableCache
if (shouldPreload) {
prodLog.info(
`HNSW: Preloading ${entityCount.toLocaleString()} vectors at init ` +
`(${(vectorMemory / 1024 / 1024).toFixed(1)}MB < ${(availableCache / 1024 / 1024).toFixed(1)}MB cache)`
)
} else {
prodLog.info(
`HNSW: Adaptive caching for ${entityCount.toLocaleString()} vectors ` +
`(${(vectorMemory / 1024 / 1024).toFixed(1)}MB > ${(availableCache / 1024 / 1024).toFixed(1)}MB cache) - loading on-demand`
)
}
// Load ALL nouns ONCE and route to correct type indexes
// This is O(N) instead of O(42*N) from the previous parallel approach
let offset = 0 // Use offset-based pagination instead of cursor (bug fix for infinite loop)
let hasMore = true
let totalLoaded = 0
const loadedByType = new Map<NounType, number>()
while (hasMore) {
const result: {
items: Array<{ id: string; vector: number[]; type?: NounType }>
hasMore: boolean
nextCursor?: string
totalCount?: number
} = await (this.storage as any).getNounsWithPagination({
limit: batchSize,
offset // Pass offset for proper pagination (previously passed cursor which was ignored)
})
// Route each noun to its type index
for (const nounData of result.items) {
try {
// Use 'type' property from HNSWNounWithMetadata (not 'nounType')
// Previously accessed wrong property, causing N+1 metadata fetches
// getNounsWithPagination already includes type in response
const nounType = nounData.type
// Skip if type not in rebuild list
if (!nounType || !typesToRebuild.includes(nounType as NounType)) {
continue
}
// Get the index for this type
const index = this.getIndexForType(nounType as NounType)
// Load HNSW graph data
const hnswData = await (this.storage as any).getVectorIndexData(nounData.id)
if (!hnswData) {
continue // No HNSW data
}
// Create noun with restored connections
const noun = {
id: nounData.id,
vector: shouldPreload ? nounData.vector : [],
connections: new Map(),
level: hnswData.level
}
// Restore connections from storage
for (const [levelStr, nounIds] of Object.entries(hnswData.connections)) {
const level = parseInt(levelStr, 10)
noun.connections.set(level, new Set<string>(nounIds as string[]))
}
// Add to type-specific index
;(index as any).nouns.set(nounData.id, noun)
// Track high-level nodes
if (noun.level >= 2 && noun.level <= (index as any).MAX_TRACKED_LEVELS) {
if (!(index as any).highLevelNodes.has(noun.level)) {
;(index as any).highLevelNodes.set(noun.level, new Set())
}
;(index as any).highLevelNodes.get(noun.level).add(nounData.id)
}
// Track progress
loadedByType.set(nounType as NounType, (loadedByType.get(nounType as NounType) || 0) + 1)
totalLoaded++
if (options.onProgress && totalLoaded % 100 === 0) {
options.onProgress(nounType as NounType, loadedByType.get(nounType as NounType) || 0, totalLoaded)
}
} catch (error) {
prodLog.error(`Failed to restore HNSW data for ${nounData.id}:`, error)
}
}
hasMore = result.hasMore
offset += batchSize // Increment offset for next page
// Progress logging
if (totalLoaded % 1000 === 0) {
prodLog.info(`Progress: ${totalLoaded.toLocaleString()} entities loaded...`)
}
}
// Restore entry points for each type
for (const type of typesToRebuild) {
const index = this.getIndexForType(type)
let maxLevel = 0
let entryPointId: string | null = null
for (const [id, noun] of (index as any).nouns.entries()) {
if (entryPointId === null || noun.level > maxLevel) {
maxLevel = noun.level
entryPointId = id
}
}
// Recovery: if still null after loop but nouns exist
if ((index as any).nouns.size > 0 && !entryPointId) {
const { id: recoveredId, level: recoveredLevel } = (index as any).recoverEntryPointO1()
entryPointId = recoveredId
maxLevel = recoveredLevel
}
// Validation: if entry point doesn't exist in loaded nouns
if (entryPointId && !(index as any).nouns.has(entryPointId)) {
const { id: recoveredId, level: recoveredLevel } = (index as any).recoverEntryPointO1()
entryPointId = recoveredId
maxLevel = recoveredLevel
}
;(index as any).entryPointId = entryPointId
;(index as any).maxLevel = maxLevel
const loaded = loadedByType.get(type) || 0
const cacheInfo = shouldPreload ? ' (vectors preloaded)' : ' (adaptive caching)'
prodLog.info(
`✅ Rebuilt ${type} index: ${loaded.toLocaleString()} entities, ` +
`${maxLevel + 1} levels, entry point: ${entryPointId || 'none'}${cacheInfo}`
)
}
prodLog.info(
`✅ TypeAwareHNSW rebuild complete: ${this.size().toLocaleString()} total entities across ${this.indexes.size} types (loaded from persisted graph structure)`
)
}
/**
* Get comprehensive statistics
*
* Shows memory reduction compared to monolithic approach.
*
* @returns Type-aware HNSW statistics
*/
public getStats(): TypeAwareHNSWStats {
const typeStats = new Map<
NounType,
{
nodeCount: number
memoryMB: number
maxLevel: number
entryPointId: string | null
}
>()
let totalNodes = 0
let totalMemoryMB = 0
// Collect stats from each type's index
for (const [type, index] of this.indexes.entries()) {
const cacheStats = index.getCacheStats()
const nodeCount = index.size()
const memoryMB = cacheStats.hnswCache.estimatedMemoryMB
typeStats.set(type, {
nodeCount,
memoryMB,
maxLevel: index.getMaxLevel(),
entryPointId: index.getEntryPointId()
})
totalNodes += nodeCount
totalMemoryMB += memoryMB
}
// Estimate monolithic memory (for comparison)
// Monolithic would use ~384 bytes per entity @ 1B scale
const estimatedMonolithicMemoryMB = (totalNodes * 384) / (1024 * 1024)
// Calculate memory reduction
const memoryReductionPercent =
estimatedMonolithicMemoryMB > 0
? ((estimatedMonolithicMemoryMB - totalMemoryMB) /
estimatedMonolithicMemoryMB) *
100
: 0
return {
totalNodes,
totalMemoryMB: parseFloat(totalMemoryMB.toFixed(2)),
typeCount: this.indexes.size,
typeStats,
memoryReductionPercent: parseFloat(memoryReductionPercent.toFixed(2)),
estimatedMonolithicMemoryMB: parseFloat(
estimatedMonolithicMemoryMB.toFixed(2)
)
}
}
/**
* Get statistics for a specific type
*
* @param type The noun type
* @returns Statistics for this type's index (null if no index)
*/
public getStatsForType(
type: NounType
): {
nodeCount: number
memoryMB: number
maxLevel: number
entryPointId: string | null
cacheStats: any
} | null {
const index = this.indexes.get(type)
if (!index) {
return null
}
const cacheStats = index.getCacheStats()
return {
nodeCount: index.size(),
memoryMB: cacheStats.hnswCache.estimatedMemoryMB,
maxLevel: index.getMaxLevel(),
entryPointId: index.getEntryPointId(),
cacheStats
}
}
/**
* Get all noun types (for iteration)
*
* @returns Array of all noun types
*/
private getAllNounTypes(): NounType[] {
const types: NounType[] = []
for (let i = 0; i < NOUN_TYPE_COUNT; i++) {
types.push(TypeUtils.getNounFromIndex(i))
}
return types
}
/**
* Get list of types that have indexes (have entities)
*
* @returns Array of types with indexes
*/
public getActiveTypes(): NounType[] {
return Array.from(this.indexes.keys())
}
}