Initial commit: Brainy - Multi-Dimensional AI Database
Open source vector database with HNSW indexing, graph relationships, and metadata facets. Features CLI with professional augmentation registry integration for discovering extensions and capabilities.
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dist/storage/enhancedCacheManager.js
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dist/storage/enhancedCacheManager.js
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/**
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* Enhanced Multi-Level Cache Manager with Predictive Prefetching
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* Optimized for HNSW search patterns and large-scale vector operations
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*/
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// Prefetch prediction strategies
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var PrefetchStrategy;
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(function (PrefetchStrategy) {
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PrefetchStrategy["GRAPH_CONNECTIVITY"] = "connectivity";
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PrefetchStrategy["VECTOR_SIMILARITY"] = "similarity";
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PrefetchStrategy["ACCESS_PATTERN"] = "pattern";
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PrefetchStrategy["HYBRID"] = "hybrid";
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})(PrefetchStrategy || (PrefetchStrategy = {}));
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/**
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* Enhanced cache manager with intelligent prefetching for HNSW operations
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* Provides multi-level caching optimized for vector search workloads
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*/
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export class EnhancedCacheManager {
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constructor(config = {}) {
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this.hotCache = new Map();
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this.warmCache = new Map();
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this.prefetchQueue = new Set();
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this.accessPatterns = new Map(); // Track access times
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this.vectorIndex = new Map(); // For similarity calculations
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this.prefetchInProgress = false;
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// Statistics and monitoring
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this.stats = {
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hotCacheHits: 0,
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hotCacheMisses: 0,
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warmCacheHits: 0,
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warmCacheMisses: 0,
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prefetchHits: 0,
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prefetchMisses: 0,
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totalPrefetched: 0,
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predictionAccuracy: 0,
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backgroundOptimizations: 0
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};
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this.config = {
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hotCacheMaxSize: 1000,
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hotCacheEvictionThreshold: 0.8,
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warmCacheMaxSize: 10000,
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warmCacheTTL: 300000, // 5 minutes
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prefetchEnabled: true,
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prefetchStrategy: PrefetchStrategy.HYBRID,
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prefetchBatchSize: 50,
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predictionLookahead: 3,
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similarityThreshold: 0.8,
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maxSimilarityDistance: 2.0,
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backgroundOptimization: true,
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statisticsCollection: true,
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...config
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};
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// Start background optimization if enabled
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if (this.config.backgroundOptimization) {
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this.startBackgroundOptimization();
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}
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}
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/**
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* Set storage adapters for warm/cold storage operations
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*/
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setStorageAdapters(storageAdapter, batchOperations) {
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this.storageAdapter = storageAdapter;
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this.batchOperations = batchOperations;
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}
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/**
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* Get item with intelligent prefetching
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*/
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async get(id) {
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const startTime = Date.now();
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// Update access pattern
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this.recordAccess(id, startTime);
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// Check hot cache first
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let entry = this.hotCache.get(id);
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if (entry && !this.isExpired(entry)) {
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entry.lastAccessed = startTime;
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entry.accessCount++;
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this.stats.hotCacheHits++;
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// Trigger predictive prefetch
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if (this.config.prefetchEnabled) {
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this.schedulePrefetch(id, entry.data);
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}
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return entry.data;
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}
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this.stats.hotCacheMisses++;
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// Check warm cache
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entry = this.warmCache.get(id);
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if (entry && !this.isExpired(entry)) {
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entry.lastAccessed = startTime;
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entry.accessCount++;
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this.stats.warmCacheHits++;
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// Promote to hot cache if frequently accessed
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if (entry.accessCount > 3) {
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this.promoteToHotCache(id, entry);
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}
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return entry.data;
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}
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this.stats.warmCacheMisses++;
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// Load from storage
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const item = await this.loadFromStorage(id);
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if (item) {
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// Cache the item
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await this.set(id, item);
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// Trigger predictive prefetch
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if (this.config.prefetchEnabled) {
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this.schedulePrefetch(id, item);
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}
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}
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return item;
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}
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/**
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* Get multiple items efficiently with batch operations
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*/
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async getMany(ids) {
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const result = new Map();
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const uncachedIds = [];
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// Check caches first
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for (const id of ids) {
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const cached = await this.get(id);
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if (cached) {
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result.set(id, cached);
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}
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else {
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uncachedIds.push(id);
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}
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}
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// Batch load uncached items
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if (uncachedIds.length > 0 && this.batchOperations) {
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const batchResult = await this.batchOperations.batchGetNodes(uncachedIds);
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// Cache loaded items
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for (const [id, item] of batchResult.items) {
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await this.set(id, item);
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result.set(id, item);
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}
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}
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return result;
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}
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/**
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* Set item in cache with metadata
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*/
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async set(id, item) {
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const now = Date.now();
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const entry = {
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data: item,
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lastAccessed: now,
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accessCount: 1,
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expiresAt: now + this.config.warmCacheTTL,
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connectedNodes: this.extractConnectedNodes(item),
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predictionScore: 0
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};
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// Store vector for similarity calculations
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if ('vector' in item && item.vector) {
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this.vectorIndex.set(id, item.vector);
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entry.vectorSimilarity = 0;
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}
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// Add to warm cache initially
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this.warmCache.set(id, entry);
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// Clean up if needed
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if (this.warmCache.size > this.config.warmCacheMaxSize) {
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this.evictFromWarmCache();
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}
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// Update statistics
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this.stats.warmCacheHits++; // Count as a potential future hit
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}
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/**
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* Intelligent prefetch based on access patterns and graph structure
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*/
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async schedulePrefetch(currentId, currentItem) {
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if (this.prefetchInProgress || !this.config.prefetchEnabled) {
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return;
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}
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// Use different strategies based on configuration
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let candidateIds = [];
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switch (this.config.prefetchStrategy) {
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case PrefetchStrategy.GRAPH_CONNECTIVITY:
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candidateIds = this.predictByConnectivity(currentId, currentItem);
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break;
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case PrefetchStrategy.VECTOR_SIMILARITY:
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candidateIds = await this.predictBySimilarity(currentId, currentItem);
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break;
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case PrefetchStrategy.ACCESS_PATTERN:
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candidateIds = this.predictByAccessPattern(currentId);
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break;
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case PrefetchStrategy.HYBRID:
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candidateIds = await this.hybridPrediction(currentId, currentItem);
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break;
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}
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// Filter out already cached items
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const uncachedIds = candidateIds.filter(id => !this.hotCache.has(id) && !this.warmCache.has(id)).slice(0, this.config.prefetchBatchSize);
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if (uncachedIds.length > 0) {
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this.executePrefetch(uncachedIds);
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}
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}
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/**
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* Predict next nodes based on graph connectivity
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*/
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predictByConnectivity(currentId, currentItem) {
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const candidates = [];
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if ('connections' in currentItem && currentItem.connections) {
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const connections = currentItem.connections;
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// Add immediate neighbors with higher priority for lower levels
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for (const [level, nodeIds] of connections.entries()) {
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const priority = Math.max(1, 5 - level); // Higher priority for level 0
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for (const nodeId of nodeIds) {
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// Add based on priority
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for (let i = 0; i < priority; i++) {
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candidates.push(nodeId);
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}
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}
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}
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}
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// Shuffle and deduplicate
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const shuffled = candidates.sort(() => Math.random() - 0.5);
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return [...new Set(shuffled)];
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}
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/**
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* Predict next nodes based on vector similarity
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*/
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async predictBySimilarity(currentId, currentItem) {
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if (!('vector' in currentItem) || !currentItem.vector) {
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return [];
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}
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const currentVector = currentItem.vector;
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const similarities = [];
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// Calculate similarities with vectors in cache
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for (const [id, vector] of this.vectorIndex.entries()) {
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if (id === currentId)
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continue;
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const similarity = this.cosineSimilarity(currentVector, vector);
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if (similarity > this.config.similarityThreshold) {
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similarities.push([id, similarity]);
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}
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}
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// Sort by similarity and return top candidates
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similarities.sort((a, b) => b[1] - a[1]);
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return similarities.slice(0, this.config.prefetchBatchSize).map(([id]) => id);
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}
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/**
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* Predict based on historical access patterns
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*/
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predictByAccessPattern(currentId) {
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const currentPattern = this.accessPatterns.get(currentId);
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if (!currentPattern || currentPattern.length < 2) {
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return [];
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}
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// Find similar access patterns
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const candidates = [];
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for (const [id, pattern] of this.accessPatterns.entries()) {
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if (id === currentId || pattern.length < 2)
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continue;
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const similarity = this.patternSimilarity(currentPattern, pattern);
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if (similarity > 0.5) {
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candidates.push([id, similarity]);
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}
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}
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candidates.sort((a, b) => b[1] - a[1]);
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return candidates.slice(0, this.config.prefetchBatchSize).map(([id]) => id);
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}
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/**
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* Hybrid prediction combining multiple strategies
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*/
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async hybridPrediction(currentId, currentItem) {
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const connectivityCandidates = this.predictByConnectivity(currentId, currentItem);
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const similarityCandidates = await this.predictBySimilarity(currentId, currentItem);
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const patternCandidates = this.predictByAccessPattern(currentId);
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// Weighted combination
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const candidateScores = new Map();
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// Connectivity gets highest weight (40%)
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connectivityCandidates.forEach((id, index) => {
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const score = (connectivityCandidates.length - index) / connectivityCandidates.length * 0.4;
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candidateScores.set(id, (candidateScores.get(id) || 0) + score);
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});
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// Similarity gets medium weight (35%)
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similarityCandidates.forEach((id, index) => {
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const score = (similarityCandidates.length - index) / similarityCandidates.length * 0.35;
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candidateScores.set(id, (candidateScores.get(id) || 0) + score);
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});
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// Pattern gets lower weight (25%)
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patternCandidates.forEach((id, index) => {
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const score = (patternCandidates.length - index) / patternCandidates.length * 0.25;
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candidateScores.set(id, (candidateScores.get(id) || 0) + score);
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});
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// Sort by combined score
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const sortedCandidates = Array.from(candidateScores.entries())
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.sort((a, b) => b[1] - a[1])
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.map(([id]) => id);
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return sortedCandidates.slice(0, this.config.prefetchBatchSize);
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}
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/**
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* Execute prefetch operation in background
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*/
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async executePrefetch(ids) {
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if (this.prefetchInProgress || !this.batchOperations) {
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return;
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}
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this.prefetchInProgress = true;
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try {
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const batchResult = await this.batchOperations.batchGetNodes(ids);
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// Cache prefetched items
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for (const [id, item] of batchResult.items) {
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const entry = {
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data: item,
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lastAccessed: Date.now(),
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accessCount: 0, // Prefetched items start with 0 access count
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expiresAt: Date.now() + this.config.warmCacheTTL,
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connectedNodes: this.extractConnectedNodes(item),
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predictionScore: 1 // Mark as prefetched
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};
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this.warmCache.set(id, entry);
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}
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this.stats.totalPrefetched += batchResult.items.size;
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}
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catch (error) {
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console.warn('Prefetch operation failed:', error);
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}
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finally {
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this.prefetchInProgress = false;
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}
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}
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/**
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* Load item from storage adapter
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*/
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async loadFromStorage(id) {
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if (!this.storageAdapter) {
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return null;
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}
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try {
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return await this.storageAdapter.get(id);
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}
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catch (error) {
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console.warn(`Failed to load ${id} from storage:`, error);
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return null;
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}
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}
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/**
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* Promote frequently accessed item to hot cache
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*/
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promoteToHotCache(id, entry) {
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// Remove from warm cache
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this.warmCache.delete(id);
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// Add to hot cache
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this.hotCache.set(id, entry);
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// Evict if necessary
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if (this.hotCache.size > this.config.hotCacheMaxSize) {
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this.evictFromHotCache();
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}
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}
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/**
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* Evict least recently used items from hot cache
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*/
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evictFromHotCache() {
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const threshold = Math.floor(this.config.hotCacheMaxSize * this.config.hotCacheEvictionThreshold);
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if (this.hotCache.size <= threshold) {
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return;
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}
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// Sort by last accessed time and access count
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const entries = Array.from(this.hotCache.entries())
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.sort((a, b) => {
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const scoreA = a[1].accessCount * 0.7 + (Date.now() - a[1].lastAccessed) * -0.3;
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const scoreB = b[1].accessCount * 0.7 + (Date.now() - b[1].lastAccessed) * -0.3;
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return scoreA - scoreB;
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});
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// Remove least valuable entries
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const toRemove = entries.slice(0, this.hotCache.size - threshold);
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for (const [id] of toRemove) {
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this.hotCache.delete(id);
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}
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}
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/**
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* Evict expired items from warm cache
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*/
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evictFromWarmCache() {
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const now = Date.now();
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const toRemove = [];
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for (const [id, entry] of this.warmCache.entries()) {
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if (this.isExpired(entry)) {
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toRemove.push(id);
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}
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}
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// Remove expired items
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||||
for (const id of toRemove) {
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this.warmCache.delete(id);
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this.vectorIndex.delete(id);
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}
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// If still over limit, remove LRU items
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if (this.warmCache.size > this.config.warmCacheMaxSize) {
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const entries = Array.from(this.warmCache.entries())
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.sort((a, b) => a[1].lastAccessed - b[1].lastAccessed);
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const excess = this.warmCache.size - this.config.warmCacheMaxSize;
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||||
for (let i = 0; i < excess; i++) {
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const [id] = entries[i];
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this.warmCache.delete(id);
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this.vectorIndex.delete(id);
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}
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||||
}
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}
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/**
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* Record access pattern for prediction
|
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*/
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recordAccess(id, timestamp) {
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if (!this.config.statisticsCollection) {
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return;
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}
|
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let pattern = this.accessPatterns.get(id);
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if (!pattern) {
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pattern = [];
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this.accessPatterns.set(id, pattern);
|
||||
}
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pattern.push(timestamp);
|
||||
// Keep only recent accesses (last 10)
|
||||
if (pattern.length > 10) {
|
||||
pattern.shift();
|
||||
}
|
||||
}
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||||
/**
|
||||
* Extract connected node IDs from HNSW item
|
||||
*/
|
||||
extractConnectedNodes(item) {
|
||||
const connected = new Set();
|
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if ('connections' in item && item.connections) {
|
||||
const connections = item.connections;
|
||||
for (const nodeIds of connections.values()) {
|
||||
nodeIds.forEach(id => connected.add(id));
|
||||
}
|
||||
}
|
||||
return connected;
|
||||
}
|
||||
/**
|
||||
* Check if cache entry is expired
|
||||
*/
|
||||
isExpired(entry) {
|
||||
return entry.expiresAt !== null && Date.now() > entry.expiresAt;
|
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}
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||||
/**
|
||||
* Calculate cosine similarity between vectors
|
||||
*/
|
||||
cosineSimilarity(a, b) {
|
||||
if (a.length !== b.length)
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return 0;
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let dotProduct = 0;
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||||
let normA = 0;
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||||
let normB = 0;
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||||
for (let i = 0; i < a.length; i++) {
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dotProduct += a[i] * b[i];
|
||||
normA += a[i] * a[i];
|
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normB += b[i] * b[i];
|
||||
}
|
||||
const magnitude = Math.sqrt(normA) * Math.sqrt(normB);
|
||||
return magnitude === 0 ? 0 : dotProduct / magnitude;
|
||||
}
|
||||
/**
|
||||
* Calculate pattern similarity between access patterns
|
||||
*/
|
||||
patternSimilarity(pattern1, pattern2) {
|
||||
const minLength = Math.min(pattern1.length, pattern2.length);
|
||||
if (minLength < 2)
|
||||
return 0;
|
||||
// Calculate intervals between accesses
|
||||
const intervals1 = pattern1.slice(1).map((t, i) => t - pattern1[i]);
|
||||
const intervals2 = pattern2.slice(1).map((t, i) => t - pattern2[i]);
|
||||
// Compare interval patterns
|
||||
let similarity = 0;
|
||||
const compareLength = Math.min(intervals1.length, intervals2.length);
|
||||
for (let i = 0; i < compareLength; i++) {
|
||||
const diff = Math.abs(intervals1[i] - intervals2[i]);
|
||||
const maxInterval = Math.max(intervals1[i], intervals2[i]);
|
||||
similarity += maxInterval === 0 ? 1 : 1 - (diff / maxInterval);
|
||||
}
|
||||
return compareLength === 0 ? 0 : similarity / compareLength;
|
||||
}
|
||||
/**
|
||||
* Start background optimization process
|
||||
*/
|
||||
startBackgroundOptimization() {
|
||||
setInterval(() => {
|
||||
this.runBackgroundOptimization();
|
||||
}, 60000); // Run every minute
|
||||
}
|
||||
/**
|
||||
* Run background optimization tasks
|
||||
*/
|
||||
runBackgroundOptimization() {
|
||||
// Clean up expired entries
|
||||
this.evictFromWarmCache();
|
||||
this.evictFromHotCache();
|
||||
// Clean up old access patterns
|
||||
const cutoff = Date.now() - 3600000; // 1 hour
|
||||
for (const [id, pattern] of this.accessPatterns.entries()) {
|
||||
const recentAccesses = pattern.filter(t => t > cutoff);
|
||||
if (recentAccesses.length === 0) {
|
||||
this.accessPatterns.delete(id);
|
||||
}
|
||||
else {
|
||||
this.accessPatterns.set(id, recentAccesses);
|
||||
}
|
||||
}
|
||||
this.stats.backgroundOptimizations++;
|
||||
}
|
||||
/**
|
||||
* Get cache statistics
|
||||
*/
|
||||
getStats() {
|
||||
return {
|
||||
...this.stats,
|
||||
hotCacheSize: this.hotCache.size,
|
||||
warmCacheSize: this.warmCache.size,
|
||||
prefetchQueueSize: this.prefetchQueue.size,
|
||||
accessPatternsTracked: this.accessPatterns.size
|
||||
};
|
||||
}
|
||||
/**
|
||||
* Clear all caches
|
||||
*/
|
||||
clear() {
|
||||
this.hotCache.clear();
|
||||
this.warmCache.clear();
|
||||
this.prefetchQueue.clear();
|
||||
this.accessPatterns.clear();
|
||||
this.vectorIndex.clear();
|
||||
}
|
||||
}
|
||||
//# sourceMappingURL=enhancedCacheManager.js.map
|
||||
Loading…
Add table
Add a link
Reference in a new issue