feat: implement unified metadata intelligence system
- Add cardinality tracking for all metadata fields with distribution analysis - Implement smart normalization for high-cardinality fields (timestamps, floats) - Add field statistics tracking (query counts, patterns, performance) - Integrate field discovery methods for query optimization - Fix UPDATE bug by passing old metadata to removeFromIndex - Track query patterns to optimize index strategies dynamically - Add getFieldStatistics, getFieldCardinality, getOptimalQueryPlan methods - Implement time bucketing for timestamp fields (1-minute precision) - Add float precision reduction for numeric fields (2 decimal places) This unifies metadata performance optimization with field discovery, providing a complete metadata intelligence system that self-optimizes based on usage patterns and data characteristics.
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2 changed files with 334 additions and 4 deletions
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@ -316,7 +316,7 @@ export class Brainy<T = any> {
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})
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// Update metadata index - remove old entry and add new one
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await this.metadataIndex.removeFromIndex(params.id)
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await this.metadataIndex.removeFromIndex(params.id, existing.metadata)
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await this.metadataIndex.addToIndex(params.id, updatedMetadata)
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})
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}
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@ -49,6 +49,26 @@ interface SortedFieldIndex {
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fieldType: 'number' | 'string' | 'date' | 'mixed'
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}
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// Cardinality tracking for optimization decisions
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interface CardinalityInfo {
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uniqueValues: number
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totalValues: number
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distribution: 'uniform' | 'skewed' | 'sparse'
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updateFrequency: number
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lastAnalyzed: number
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}
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// Field statistics for smart optimization
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interface FieldStats {
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cardinality: CardinalityInfo
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queryCount: number
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rangeQueryCount: number
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exactQueryCount: number
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avgQueryTime: number
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indexType: 'hash' | 'sorted' | 'both'
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normalizationStrategy?: 'none' | 'precision' | 'bucket'
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}
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export class MetadataIndexManager {
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private storage: StorageAdapter
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private config: Required<MetadataIndexConfig>
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@ -65,6 +85,16 @@ export class MetadataIndexManager {
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private sortedIndices = new Map<string, SortedFieldIndex>()
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private numericFields = new Set<string>() // Track which fields are numeric
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// Cardinality and field statistics tracking
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private fieldStats = new Map<string, FieldStats>()
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private cardinalityUpdateInterval = 100 // Update cardinality every N operations
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private operationCount = 0
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// Smart normalization thresholds
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private readonly HIGH_CARDINALITY_THRESHOLD = 1000
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private readonly TIMESTAMP_PRECISION_MS = 60000 // 1 minute buckets
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private readonly FLOAT_PRECISION = 2 // decimal places
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// Unified cache for coordinated memory management
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private unifiedCache: UnifiedCache
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@ -331,6 +361,112 @@ export class MetadataIndexManager {
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return result
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}
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/**
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* Update cardinality statistics for a field
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*/
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private updateCardinalityStats(field: string, value: any, operation: 'add' | 'remove'): void {
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// Initialize field stats if needed
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if (!this.fieldStats.has(field)) {
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this.fieldStats.set(field, {
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cardinality: {
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uniqueValues: 0,
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totalValues: 0,
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distribution: 'uniform',
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updateFrequency: 0,
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lastAnalyzed: Date.now()
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},
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queryCount: 0,
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rangeQueryCount: 0,
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exactQueryCount: 0,
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avgQueryTime: 0,
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indexType: 'hash'
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})
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}
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const stats = this.fieldStats.get(field)!
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const cardinality = stats.cardinality
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// Track unique values
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const fieldIndexKey = `${field}:${String(value)}`
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const entry = this.indexCache.get(fieldIndexKey)
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if (operation === 'add') {
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if (!entry || entry.ids.size === 1) {
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cardinality.uniqueValues++
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}
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cardinality.totalValues++
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} else if (operation === 'remove') {
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if (entry && entry.ids.size === 0) {
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cardinality.uniqueValues--
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}
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cardinality.totalValues = Math.max(0, cardinality.totalValues - 1)
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}
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// Update frequency tracking
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cardinality.updateFrequency++
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// Periodically analyze distribution
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if (++this.operationCount % this.cardinalityUpdateInterval === 0) {
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this.analyzeFieldDistribution(field)
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}
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// Determine optimal index type based on cardinality
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this.updateIndexStrategy(field, stats)
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}
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/**
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* Analyze field distribution for optimization
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*/
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private analyzeFieldDistribution(field: string): void {
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const stats = this.fieldStats.get(field)
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if (!stats) return
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const cardinality = stats.cardinality
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const ratio = cardinality.uniqueValues / Math.max(1, cardinality.totalValues)
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// Determine distribution type
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if (ratio > 0.9) {
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cardinality.distribution = 'sparse' // High uniqueness (like IDs, timestamps)
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} else if (ratio < 0.1) {
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cardinality.distribution = 'skewed' // Low uniqueness (like status, type)
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} else {
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cardinality.distribution = 'uniform' // Balanced distribution
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}
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cardinality.lastAnalyzed = Date.now()
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}
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/**
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* Update index strategy based on field statistics
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*/
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private updateIndexStrategy(field: string, stats: FieldStats): void {
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const isNumeric = this.numericFields.has(field)
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const hasHighCardinality = stats.cardinality.uniqueValues > this.HIGH_CARDINALITY_THRESHOLD
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const hasRangeQueries = stats.rangeQueryCount > stats.exactQueryCount * 0.3
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// Determine optimal index type
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if (isNumeric && hasRangeQueries) {
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stats.indexType = 'both' // Need both hash and sorted
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} else if (hasRangeQueries) {
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stats.indexType = 'sorted'
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} else {
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stats.indexType = 'hash'
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}
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// Determine normalization strategy for high cardinality fields
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if (hasHighCardinality) {
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if (field.toLowerCase().includes('time') || field.toLowerCase().includes('date')) {
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stats.normalizationStrategy = 'bucket' // Time bucketing
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} else if (isNumeric) {
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stats.normalizationStrategy = 'precision' // Reduce float precision
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} else {
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stats.normalizationStrategy = 'none' // Keep as-is for strings
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}
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} else {
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stats.normalizationStrategy = 'none'
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}
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}
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/**
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* Get IDs matching a range query
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@ -342,6 +478,12 @@ export class MetadataIndexManager {
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includeMin: boolean = true,
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includeMax: boolean = true
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): Promise<string[]> {
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// Track range query for field statistics
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if (this.fieldStats.has(field)) {
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const stats = this.fieldStats.get(field)!
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stats.rangeQueryCount++
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}
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// Ensure sorted index exists
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await this.ensureSortedIndex(field)
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@ -408,14 +550,35 @@ export class MetadataIndexManager {
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}
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/**
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* Normalize value for consistent indexing
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* Normalize value for consistent indexing with smart optimization
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*/
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private normalizeValue(value: any): string {
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private normalizeValue(value: any, field?: string): string {
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if (value === null || value === undefined) return '__NULL__'
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if (typeof value === 'boolean') return value ? '__TRUE__' : '__FALSE__'
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// Apply smart normalization based on field statistics
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if (field && this.fieldStats.has(field)) {
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const stats = this.fieldStats.get(field)!
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const strategy = stats.normalizationStrategy
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if (strategy === 'bucket' && typeof value === 'number') {
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// Time bucketing for timestamps
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if (field.toLowerCase().includes('time') || field.toLowerCase().includes('date')) {
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const bucketSize = this.TIMESTAMP_PRECISION_MS
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const bucketed = Math.floor(value / bucketSize) * bucketSize
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return bucketed.toString()
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}
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} else if (strategy === 'precision' && typeof value === 'number') {
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// Reduce float precision for high cardinality numeric fields
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const rounded = Math.round(value * Math.pow(10, this.FLOAT_PRECISION)) / Math.pow(10, this.FLOAT_PRECISION)
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return rounded.toString()
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}
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}
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// Default normalization
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if (typeof value === 'number') return value.toString()
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if (Array.isArray(value)) {
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const joined = value.map(v => this.normalizeValue(v)).join(',')
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const joined = value.map(v => this.normalizeValue(v, field)).join(',')
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// Hash very long array values to avoid filesystem limits
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if (joined.length > 100) {
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return this.hashValue(joined)
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@ -518,10 +681,16 @@ export class MetadataIndexManager {
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}
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// Add ID to entry
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const wasNew = entry.ids.size === 0
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entry.ids.add(id)
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entry.lastUpdated = Date.now()
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this.dirtyEntries.add(key)
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// Update cardinality statistics
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if (wasNew) {
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this.updateCardinalityStats(field, value, 'add')
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}
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// Incrementally update sorted index for this field
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if (!updatedFields.has(field)) {
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this.updateSortedIndexAdd(field, value, id)
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@ -616,10 +785,16 @@ export class MetadataIndexManager {
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}
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if (entry) {
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const hadId = entry.ids.has(id)
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entry.ids.delete(id)
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entry.lastUpdated = Date.now()
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this.dirtyEntries.add(key)
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// Update cardinality statistics
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if (hadId && entry.ids.size === 0) {
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this.updateCardinalityStats(field, value, 'remove')
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}
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// Incrementally update sorted index when removing
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this.updateSortedIndexRemove(field, value, id)
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@ -692,6 +867,12 @@ export class MetadataIndexManager {
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* Get IDs for a specific field-value combination with caching
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*/
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async getIds(field: string, value: any): Promise<string[]> {
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// Track exact query for field statistics
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if (this.fieldStats.has(field)) {
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const stats = this.fieldStats.get(field)!
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stats.exactQueryCount++
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}
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const key = this.getIndexKey(field, value)
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// Check metadata cache first
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@ -1538,4 +1719,153 @@ export class MetadataIndexManager {
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// Entry might not exist
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}
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}
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/**
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* Get field statistics for optimization and discovery
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*/
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async getFieldStatistics(): Promise<Map<string, FieldStats>> {
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// Initialize stats for fields we haven't seen yet
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for (const field of this.fieldIndexes.keys()) {
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if (!this.fieldStats.has(field)) {
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this.fieldStats.set(field, {
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cardinality: {
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uniqueValues: 0,
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totalValues: 0,
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distribution: 'uniform',
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updateFrequency: 0,
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lastAnalyzed: Date.now()
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},
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queryCount: 0,
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rangeQueryCount: 0,
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exactQueryCount: 0,
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avgQueryTime: 0,
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indexType: 'hash'
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})
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}
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}
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return new Map(this.fieldStats)
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}
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/**
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* Get field cardinality information
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*/
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async getFieldCardinality(field: string): Promise<CardinalityInfo | null> {
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const stats = this.fieldStats.get(field)
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return stats ? stats.cardinality : null
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}
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/**
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* Get all field names with their cardinality (for query optimization)
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*/
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async getFieldsWithCardinality(): Promise<Array<{ field: string; cardinality: number; distribution: string }>> {
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const fields: Array<{ field: string; cardinality: number; distribution: string }> = []
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for (const [field, stats] of this.fieldStats) {
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fields.push({
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field,
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cardinality: stats.cardinality.uniqueValues,
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distribution: stats.cardinality.distribution
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})
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}
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// Sort by cardinality (low cardinality fields are better for filtering)
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fields.sort((a, b) => a.cardinality - b.cardinality)
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return fields
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}
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/**
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* Get optimal query plan based on field statistics
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*/
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async getOptimalQueryPlan(filters: Record<string, any>): Promise<{
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strategy: 'exact' | 'range' | 'hybrid'
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fieldOrder: string[]
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estimatedCost: number
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}> {
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const fieldOrder: string[] = []
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let hasRangeQueries = false
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let totalEstimatedCost = 0
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// Analyze each filter
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for (const [field, value] of Object.entries(filters)) {
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const stats = this.fieldStats.get(field)
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if (!stats) continue
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// Check if this is a range query
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if (typeof value === 'object' && value !== null && !Array.isArray(value)) {
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hasRangeQueries = true
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}
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// Estimate cost based on cardinality
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const cardinality = stats.cardinality.uniqueValues
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const estimatedCost = Math.log2(Math.max(1, cardinality))
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totalEstimatedCost += estimatedCost
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fieldOrder.push(field)
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}
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// Sort fields by cardinality (process low cardinality first)
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fieldOrder.sort((a, b) => {
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const statsA = this.fieldStats.get(a)
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const statsB = this.fieldStats.get(b)
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if (!statsA || !statsB) return 0
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return statsA.cardinality.uniqueValues - statsB.cardinality.uniqueValues
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})
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return {
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strategy: hasRangeQueries ? 'hybrid' : 'exact',
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fieldOrder,
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estimatedCost: totalEstimatedCost
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}
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}
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/**
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* Export field statistics for analysis
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*/
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async exportFieldStats(): Promise<any> {
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const stats: any = {
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fields: {},
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summary: {
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totalFields: this.fieldStats.size,
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highCardinalityFields: 0,
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sparseFields: 0,
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skewedFields: 0,
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uniformFields: 0
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}
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}
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for (const [field, fieldStats] of this.fieldStats) {
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stats.fields[field] = {
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cardinality: fieldStats.cardinality,
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queryStats: {
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total: fieldStats.queryCount,
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exact: fieldStats.exactQueryCount,
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range: fieldStats.rangeQueryCount,
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avgTime: fieldStats.avgQueryTime
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},
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indexType: fieldStats.indexType,
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normalization: fieldStats.normalizationStrategy
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}
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// Update summary
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if (fieldStats.cardinality.uniqueValues > this.HIGH_CARDINALITY_THRESHOLD) {
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stats.summary.highCardinalityFields++
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}
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switch (fieldStats.cardinality.distribution) {
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case 'sparse':
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stats.summary.sparseFields++
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break
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case 'skewed':
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stats.summary.skewedFields++
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break
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case 'uniform':
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stats.summary.uniformFields++
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break
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}
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}
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return stats
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}
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}
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