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**feat(docs): add comprehensive cache configuration guide and enhance adaptive tuning**

Browse source 
- Added `cache-configuration.md` under `docs/guides`:
  - Detailed multi-level cache system (hot, warm, cold) overview.
  - Explained new adaptive tuning capabilities:
    - Memory-based adjustments across Node.js, Browser, and Worker environments.
    - Dynamic sizing for read-heavy/write-heavy workloads.
    - Environment-specific configurations for optimal caching.
  - Included best practices for large datasets, memory-constrained and read-only environments.
  - Added monitoring and advanced manual tuning instructions.
- Modified `cacheManager.ts`:
  - Introduced `environmentConfig` for tailored per-environment cache settings.
  - Enhanced auto-tuning with support for dynamic memory detection and cache hit/miss ratio.
  - Added fine-grained tuning for eviction thresholds, TTLs, and batch sizes based on workload characteristics.
  - Improved adaptive tuning with async memory detection and detailed cache statistics tracking.

**Purpose**: Provide developers with detailed guidance and dynamic tools for optimizing Brainy's cache system, ensuring better performance across diverse environments and workloads.
This commit is contained in:
David Snelling 2025-08-01 11:47:34 -07:00
parent 6ca18e3d99
commit 69f8b999ea
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234
docs/guides/cache-configuration.md Normal file
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@ -0,0 +1,234 @@
# Brainy Cache Configuration Guide
This guide explains how to configure and optimize Brainy's cache system for different environments and use cases.
## Cache System Overview
Brainy uses a multi-level cache system to optimize performance:
1. **Hot Cache**: In-memory cache for frequently accessed items
2. **Warm Cache**: Secondary cache with longer retention but slower access
3. **Cold Storage**: Persistent storage for all data
## New Features
### Dynamic Memory Detection
Brainy now includes a sophisticated memory detection mechanism that works across all JavaScript environments:
- **Node.js**: Uses dynamic import of the `os` module to get actual system memory
- **Browser**: Uses `performance.memory` or `navigator.deviceMemory` APIs
- **Worker**: Uses available memory APIs or conservative defaults
```javascript
// The cache will automatically detect available memory
const brainy = new BrainyData();
```
### Environment-Specific Configuration
You can now specify different cache configurations for each environment:
```javascript
const brainy = new BrainyData({
cacheOptions: {
environmentConfig: {
// Node.js specific settings
node: {
hotCacheMaxSize: 10000,
hotCacheEvictionThreshold: 0.85,
warmCacheTTL: 48 * 60 * 60 * 1000, // 48 hours
batchSize: 50
},
// Browser specific settings
browser: {
hotCacheMaxSize: 5000,
hotCacheEvictionThreshold: 0.8,
warmCacheTTL: 24 * 60 * 60 * 1000, // 24 hours
batchSize: 20
},
// Worker specific settings
worker: {
hotCacheMaxSize: 3000,
hotCacheEvictionThreshold: 0.75,
warmCacheTTL: 12 * 60 * 60 * 1000, // 12 hours
batchSize: 15
}
}
}
});
```
### Adaptive Cache Tuning
The cache system now includes improved adaptive tuning that automatically adjusts based on:
1. Available memory in the current environment
2. Cache hit/miss ratios
3. Access patterns (read-heavy vs. write-heavy)
4. Dataset size and characteristics
5. Storage type (S3, filesystem, memory)
The adaptive tuning system will:
- Increase cache sizes for read-only workloads
- Optimize batch sizes based on network conditions
- Adjust eviction thresholds based on memory pressure
- Tune warm cache TTL based on update frequency
```javascript
// Enable auto-tuning (on by default)
const brainy = new BrainyData({
cacheOptions: {
autoTune: true
}
});
// Disable auto-tuning if needed
const brainy = new BrainyData({
cacheOptions: {
autoTune: false
}
});
```
## Best Practices
### For Large Datasets
When working with large datasets (>100K items):
```javascript
const brainy = new BrainyData({
cacheOptions: {
// For Node.js environments with large datasets
environmentConfig: {
node: {
hotCacheMaxSize: 50000,
batchSize: 100
}
}
}
});
```
### For Memory-Constrained Environments
For environments with limited memory:
```javascript
const brainy = new BrainyData({
cacheOptions: {
// Conservative settings for memory-constrained environments
hotCacheMaxSize: 1000,
hotCacheEvictionThreshold: 0.7, // Evict earlier
warmCacheTTL: 6 * 60 * 60 * 1000, // 6 hours
batchSize: 5
}
});
```
### For Read-Only Applications
For read-only applications where data doesn't change:
```javascript
const brainy = new BrainyData({
readOnly: true,
cacheOptions: {
// More aggressive caching for read-only data
hotCacheEvictionThreshold: 0.9,
warmCacheTTL: 72 * 60 * 60 * 1000 // 72 hours
}
});
```
## Advanced Configuration
### Manual Cache Size Calculation
If you want to manually calculate the optimal cache size:
```javascript
// Get memory information
async function getMemoryInfo() {
if (typeof window === 'undefined') {
// Node.js
const os = await import('os');
return {
totalMemory: os.totalmem(),
freeMemory: os.freemem()
};
} else if (navigator.deviceMemory) {
// Browser with deviceMemory API
const totalMemory = navigator.deviceMemory * 1024 * 1024 * 1024;
return {
totalMemory,
freeMemory: totalMemory * 0.5 // Estimate
};
}
// Default fallback
return {
totalMemory: 8 * 1024 * 1024 * 1024, // 8GB
freeMemory: 4 * 1024 * 1024 * 1024 // 4GB
};
}
// Calculate optimal cache size
async function calculateOptimalCacheSize() {
const memoryInfo = await getMemoryInfo();
const BYTES_PER_ENTRY = 1024; // Estimate 1KB per entry
const memoryPercentage = 0.1; // Use 10% of free memory
return Math.max(
Math.floor(memoryInfo.freeMemory * memoryPercentage / BYTES_PER_ENTRY),
1000 // Minimum size
);
}
// Use the calculated size
async function initializeBrainy() {
const optimalSize = await calculateOptimalCacheSize();
const brainy = new BrainyData({
cacheOptions: {
hotCacheMaxSize: optimalSize
}
});
return brainy;
}
```
## Monitoring Cache Performance
You can monitor cache performance to fine-tune your settings:
```javascript
// Get cache statistics
const stats = brainy.getCacheStats();
console.log('Cache Statistics:', {
hotCacheSize: stats.hotCacheSize,
hotCacheHits: stats.hotCacheHits,
hotCacheMisses: stats.hotCacheMisses,
warmCacheSize: stats.warmCacheSize,
warmCacheHits: stats.warmCacheHits,
warmCacheMisses: stats.warmCacheMisses
});
// Calculate hit ratios
const hotHitRatio = stats.hotCacheHits / (stats.hotCacheHits + stats.hotCacheMisses || 1);
const warmHitRatio = stats.warmCacheHits / (stats.warmCacheHits + stats.warmCacheMisses || 1);
console.log('Hit Ratios:', {
hotHitRatio: hotHitRatio.toFixed(2),
warmHitRatio: warmHitRatio.toFixed(2)
});
```
## Conclusion
Brainy's enhanced cache system now provides better performance across all JavaScript environments with minimal configuration. The adaptive tuning system will automatically optimize cache parameters based on your specific workload and environment.
For most applications, the default settings with auto-tuning enabled will provide excellent performance. For specialized use cases, use the environment-specific configuration options to fine-tune the cache behavior.

453
src/storage/cacheManager.ts
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@ -44,6 +44,12 @@ interface CacheStats {
evictions: number
size: number
maxSize: number
hotCacheSize: number
warmCacheSize: number
hotCacheHits: number
hotCacheMisses: number
warmCacheHits: number
warmCacheMisses: number
}
// Environment detection for storage selection
@ -75,7 +81,13 @@ export class CacheManager<T extends HNSWNode | Edge> {
misses: 0,
evictions: 0,
size: 0,
maxSize: 0
maxSize: 0,
hotCacheSize: 0,
warmCacheSize: 0,
hotCacheHits: 0,
hotCacheMisses: 0,
warmCacheHits: 0,
warmCacheMisses: 0
}
// Environment and storage configuration
@ -109,6 +121,32 @@ export class CacheManager<T extends HNSWNode | Edge> {
warmStorage?: any
coldStorage?: any
readOnly?: boolean
environmentConfig?: {
node?: {
hotCacheMaxSize?: number
hotCacheEvictionThreshold?: number
warmCacheTTL?: number
batchSize?: number
},
browser?: {
hotCacheMaxSize?: number
hotCacheEvictionThreshold?: number
warmCacheTTL?: number
batchSize?: number
},
worker?: {
hotCacheMaxSize?: number
hotCacheEvictionThreshold?: number
warmCacheTTL?: number
batchSize?: number
},
[key: string]: {
hotCacheMaxSize?: number
hotCacheEvictionThreshold?: number
warmCacheTTL?: number
batchSize?: number
} | undefined
}
}
/**
@ -124,6 +162,32 @@ export class CacheManager<T extends HNSWNode | Edge> {
warmStorage?: any
coldStorage?: any
readOnly?: boolean
environmentConfig?: {
node?: {
hotCacheMaxSize?: number
hotCacheEvictionThreshold?: number
warmCacheTTL?: number
batchSize?: number
},
browser?: {
hotCacheMaxSize?: number
hotCacheEvictionThreshold?: number
warmCacheTTL?: number
batchSize?: number
},
worker?: {
hotCacheMaxSize?: number
hotCacheEvictionThreshold?: number
warmCacheTTL?: number
batchSize?: number
},
[key: string]: {
hotCacheMaxSize?: number
hotCacheEvictionThreshold?: number
warmCacheTTL?: number
batchSize?: number
} | undefined
}
} = {}) {
// Store options for later reference
this.options = options
@ -142,11 +206,14 @@ export class CacheManager<T extends HNSWNode | Edge> {
// Set auto-tuning flag
this.autoTune = options.autoTune !== undefined ? options.autoTune : true
// Set default values or use provided values
this.hotCacheMaxSize = options.hotCacheMaxSize || this.detectOptimalCacheSize()
this.hotCacheEvictionThreshold = options.hotCacheEvictionThreshold || 0.8
this.warmCacheTTL = options.warmCacheTTL || 24 * 60 * 60 * 1000 // 24 hours
this.batchSize = options.batchSize || 10
// Get environment-specific configuration if available
const envConfig = options.environmentConfig?.[Environment[this.environment].toLowerCase()]
// Set default values or use environment-specific values or global values
this.hotCacheMaxSize = envConfig?.hotCacheMaxSize || options.hotCacheMaxSize || this.detectOptimalCacheSize()
this.hotCacheEvictionThreshold = envConfig?.hotCacheEvictionThreshold || options.hotCacheEvictionThreshold || 0.8
this.warmCacheTTL = envConfig?.warmCacheTTL || options.warmCacheTTL || 24 * 60 * 60 * 1000 // 24 hours
this.batchSize = envConfig?.batchSize || options.batchSize || 10
// If auto-tuning is enabled, perform initial tuning
if (this.autoTune) {
@ -209,14 +276,13 @@ export class CacheManager<T extends HNSWNode | Edge> {
// In Node.js, use available system memory with enhanced allocation
if (this.environment === Environment.NODE) {
try {
// Use dynamic import to avoid ESLint warning
const getOS = () => {
// eslint-disable-next-line @typescript-eslint/no-var-requires
return require('os')
}
const os = getOS()
const totalMemory = os.totalmem()
const freeMemory = os.freemem()
// For ES module compatibility, we'll use a fixed default value
// since we can't use dynamic imports in a synchronous function
// Use conservative defaults that don't require OS module
// These values are reasonable for most systems
const estimatedTotalMemory = 8 * 1024 * 1024 * 1024 // Assume 8GB total
const estimatedFreeMemory = 4 * 1024 * 1024 * 1024 // Assume 4GB free
// Estimate average entry size (in bytes)
// This is a conservative estimate for complex objects with vectors
@ -241,7 +307,7 @@ export class CacheManager<T extends HNSWNode | Edge> {
// Calculate optimal size based on adjusted percentage
const optimalSize = Math.max(
Math.floor(freeMemory * memoryPercentage / ESTIMATED_BYTES_PER_ENTRY),
Math.floor(estimatedFreeMemory * memoryPercentage / ESTIMATED_BYTES_PER_ENTRY),
1000
)
@ -307,6 +373,167 @@ export class CacheManager<T extends HNSWNode | Edge> {
}
}
/**
* Async version of detectOptimalCacheSize that uses dynamic imports
* to access system information in Node.js environments
*
* This method provides more accurate memory detection by using
* the OS module's dynamic import in Node.js environments
*/
private async detectOptimalCacheSizeAsync(): Promise<number> {
try {
// Default to a conservative value
const defaultSize = 1000
// Get the total dataset size if available
const totalItems = this.storageStatistics ?
(this.storageStatistics.totalNodes || 0) + (this.storageStatistics.totalEdges || 0) : 0
// Determine if we're dealing with a large dataset (>100K items)
const isLargeDataset = totalItems > 100000
// Check if we're in read-only mode (from parent BrainyData instance)
const isReadOnly = this.options?.readOnly || false
// Get memory information based on environment
const memoryInfo = await this.detectAvailableMemory()
// If memory detection failed, use the synchronous method
if (!memoryInfo) {
return this.detectOptimalCacheSize()
}
// Estimate average entry size (in bytes)
// This is a conservative estimate for complex objects with vectors
const ESTIMATED_BYTES_PER_ENTRY = 1024 // 1KB per entry
// Base memory percentage - 10% by default
let memoryPercentage = 0.1
// Adjust based on operating mode and dataset size
if (isReadOnly) {
// In read-only mode, we can use more memory for caching
memoryPercentage = 0.25 // 25% of free memory
// For large datasets in read-only mode, be even more aggressive
if (isLargeDataset) {
memoryPercentage = 0.4 // 40% of free memory
}
} else if (isLargeDataset) {
// For large datasets in normal mode, increase slightly
memoryPercentage = 0.15 // 15% of free memory
}
// Calculate optimal size based on adjusted percentage
const optimalSize = Math.max(
Math.floor(memoryInfo.freeMemory * memoryPercentage / ESTIMATED_BYTES_PER_ENTRY),
1000
)
// If we know the total dataset size, cap at a reasonable percentage
if (totalItems > 0) {
// In read-only mode, we can cache a larger percentage
const maxPercentage = isReadOnly ? 0.5 : 0.3
const maxItems = Math.ceil(totalItems * maxPercentage)
// Return the smaller of the two to avoid excessive memory usage
return Math.min(optimalSize, maxItems)
}
return optimalSize
} catch (error) {
console.warn('Error detecting optimal cache size asynchronously:', error)
return 1000 // Conservative default
}
}
/**
* Detects available memory across different environments
*
* This method uses different techniques to detect memory in:
* - Node.js: Uses the OS module with dynamic import
* - Browser: Uses performance.memory or navigator.deviceMemory
* - Worker: Uses performance.memory if available
*
* @returns An object with totalMemory and freeMemory in bytes, or null if detection fails
*/
private async detectAvailableMemory(): Promise<{ totalMemory: number, freeMemory: number } | null> {
try {
// Node.js environment
if (this.environment === Environment.NODE) {
try {
// Use dynamic import for OS module
const os = await import('os')
// Get actual system memory information
const totalMemory = os.totalmem()
const freeMemory = os.freemem()
return { totalMemory, freeMemory }
} catch (error) {
console.warn('Failed to detect memory in Node.js environment:', error)
}
}
// Browser environment
if (this.environment === Environment.BROWSER) {
// Try using performance.memory (Chrome only)
if (performance && (performance as any).memory) {
const memoryInfo = (performance as any).memory
// jsHeapSizeLimit is the maximum size of the heap
// totalJSHeapSize is the currently allocated heap size
// usedJSHeapSize is the amount of heap currently being used
const totalMemory = memoryInfo.jsHeapSizeLimit || 0
const usedMemory = memoryInfo.usedJSHeapSize || 0
const freeMemory = Math.max(totalMemory - usedMemory, 0)
return { totalMemory, freeMemory }
}
// Try using navigator.deviceMemory as fallback
if (navigator.deviceMemory) {
// deviceMemory is in GB, convert to bytes
const totalMemory = navigator.deviceMemory * 1024 * 1024 * 1024
// Assume 50% is free
const freeMemory = totalMemory * 0.5
return { totalMemory, freeMemory }
}
}
// Worker environment
if (this.environment === Environment.WORKER) {
// Try using performance.memory if available (Chrome workers)
if (performance && (performance as any).memory) {
const memoryInfo = (performance as any).memory
const totalMemory = memoryInfo.jsHeapSizeLimit || 0
const usedMemory = memoryInfo.usedJSHeapSize || 0
const freeMemory = Math.max(totalMemory - usedMemory, 0)
return { totalMemory, freeMemory }
}
// For workers, use a conservative estimate
// Assume 2GB total memory with 1GB free
return {
totalMemory: 2 * 1024 * 1024 * 1024,
freeMemory: 1 * 1024 * 1024 * 1024
}
}
// If all detection methods fail, use conservative defaults
return {
totalMemory: 8 * 1024 * 1024 * 1024, // Assume 8GB total
freeMemory: 4 * 1024 * 1024 * 1024 // Assume 4GB free
}
} catch (error) {
console.warn('Memory detection failed:', error)
return null
}
}
/**
* Tune cache parameters based on statistics and environment
* This method is called periodically if auto-tuning is enabled
@ -339,17 +566,20 @@ export class CacheManager<T extends HNSWNode | Edge> {
this.storageStatistics = await this.coldStorage.getStatistics()
}
// Tune hot cache size
this.tuneHotCacheSize()
// Get cache statistics for adaptive tuning
const cacheStats = this.getStats()
// Tune eviction threshold
this.tuneEvictionThreshold()
// Use the async version of tuneHotCacheSize which uses detectOptimalCacheSizeAsync
await this.tuneHotCacheSize()
// Tune warm cache TTL
this.tuneWarmCacheTTL()
// Tune eviction threshold based on hit/miss ratio
this.tuneEvictionThreshold(cacheStats)
// Tune batch size
this.tuneBatchSize()
// Tune warm cache TTL based on access patterns
this.tuneWarmCacheTTL(cacheStats)
// Tune batch size based on access patterns and storage type
this.tuneBatchSize(cacheStats)
// Log tuned parameters if debug is enabled
if (process.env.DEBUG) {
@ -357,7 +587,15 @@ export class CacheManager<T extends HNSWNode | Edge> {
hotCacheMaxSize: this.hotCacheMaxSize,
hotCacheEvictionThreshold: this.hotCacheEvictionThreshold,
warmCacheTTL: this.warmCacheTTL,
batchSize: this.batchSize
batchSize: this.batchSize,
cacheStats: {
hotCacheSize: cacheStats.hotCacheSize,
warmCacheSize: cacheStats.warmCacheSize,
hotCacheHits: cacheStats.hotCacheHits,
hotCacheMisses: cacheStats.hotCacheMisses,
warmCacheHits: cacheStats.warmCacheHits,
warmCacheMisses: cacheStats.warmCacheMisses
}
})
}
} catch (error) {
@ -382,9 +620,9 @@ export class CacheManager<T extends HNSWNode | Edge> {
* - For read-only mode, prioritize cache size over eviction speed
* - Dynamically adjust based on hit/miss ratio and query patterns
*/
private tuneHotCacheSize(): void {
// Start with the base size from environment detection
let optimalSize = this.detectOptimalCacheSize()
private async tuneHotCacheSize(): Promise<void> {
// Use the async version to get more accurate memory information
let optimalSize = await this.detectOptimalCacheSizeAsync()
// Check if we're in read-only mode
const isReadOnly = this.options?.readOnly || false
@ -511,6 +749,7 @@ export class CacheManager<T extends HNSWNode | Edge> {
* It is tuned based on:
* 1. Cache hit/miss ratio
* 2. Operation patterns (read-heavy vs. write-heavy workloads)
* 3. Memory pressure and available resources
*
* Algorithm:
* - Start with a default threshold of 0.8 (80% of max size)
@ -518,24 +757,30 @@ export class CacheManager<T extends HNSWNode | Edge> {
* - For low hit ratios, decrease the threshold to evict items more aggressively
* - For read-heavy workloads, use a higher threshold
* - For write-heavy workloads, use a lower threshold
* - Under memory pressure, use a lower threshold to conserve resources
*
* @param cacheStats Optional cache statistics for more adaptive tuning
*/
private tuneEvictionThreshold(): void {
private tuneEvictionThreshold(cacheStats?: CacheStats): void {
// Default threshold
let threshold = 0.8
// Use provided cache stats or internal stats
const stats = cacheStats || this.getStats()
// Adjust based on hit/miss ratio if we have enough data
const totalAccesses = this.stats.hits + this.stats.misses
if (totalAccesses > 100) {
const hitRatio = this.stats.hits / totalAccesses
const totalHotAccesses = stats.hotCacheHits + stats.hotCacheMisses
if (totalHotAccesses > 100) {
const hotHitRatio = stats.hotCacheHits / totalHotAccesses
// If hit ratio is high, we can use a higher threshold
// If hit ratio is low, we should use a lower threshold to evict more aggressively
if (hitRatio > 0.8) {
if (hotHitRatio > 0.8) {
// High hit ratio, increase threshold (up to 0.9)
threshold = Math.min(0.9, 0.8 + (hitRatio - 0.8))
} else if (hitRatio < 0.5) {
threshold = Math.min(0.9, 0.8 + (hotHitRatio - 0.8) * 0.5)
} else if (hotHitRatio < 0.5) {
// Low hit ratio, decrease threshold (down to 0.6)
threshold = Math.max(0.6, 0.8 - (0.5 - hitRatio))
threshold = Math.max(0.6, 0.8 - (0.5 - hotHitRatio) * 0.5)
}
}
@ -564,6 +809,24 @@ export class CacheManager<T extends HNSWNode | Edge> {
}
}
// Check memory pressure - if hot cache is growing too fast relative to hits,
// reduce the threshold to conserve memory
if (stats.hotCacheSize > 0 && totalHotAccesses > 0) {
const sizeToAccessRatio = stats.hotCacheSize / totalHotAccesses
// If the ratio is high, it means we're caching a lot but not getting many hits
if (sizeToAccessRatio > 10) {
// Reduce threshold more aggressively under high memory pressure
threshold = Math.max(0.5, threshold - 0.1)
}
}
// If we're in read-only mode, we can be more aggressive with caching
const isReadOnly = this.options?.readOnly || false
if (isReadOnly) {
threshold = Math.min(0.95, threshold + 0.05)
}
// Update the eviction threshold
this.hotCacheEvictionThreshold = threshold
}
@ -574,16 +837,43 @@ export class CacheManager<T extends HNSWNode | Edge> {
* The warm cache TTL determines how long items remain in the warm cache.
* It is tuned based on:
* 1. Update frequency from operation statistics
* 2. Warm cache hit/miss ratio
* 3. Access patterns and frequency
* 4. Available storage resources
*
* Algorithm:
* - Start with a default TTL of 24 hours
* - For frequently updated data, use a shorter TTL
* - For rarely updated data, use a longer TTL
* - For frequently accessed data, use a longer TTL
* - For rarely accessed data, use a shorter TTL
* - Under storage pressure, use a shorter TTL
*
* @param cacheStats Optional cache statistics for more adaptive tuning
*/
private tuneWarmCacheTTL(): void {
private tuneWarmCacheTTL(cacheStats?: CacheStats): void {
// Default TTL (24 hours)
let ttl = 24 * 60 * 60 * 1000
// Use provided cache stats or internal stats
const stats = cacheStats || this.getStats()
// Adjust based on warm cache hit/miss ratio if we have enough data
const totalWarmAccesses = stats.warmCacheHits + stats.warmCacheMisses
if (totalWarmAccesses > 50) {
const warmHitRatio = stats.warmCacheHits / totalWarmAccesses
// If warm cache hit ratio is high, items in warm cache are useful
// so we should keep them longer
if (warmHitRatio > 0.7) {
// High hit ratio, increase TTL (up to 36 hours)
ttl = Math.min(36 * 60 * 60 * 1000, ttl * (1 + (warmHitRatio - 0.7)))
} else if (warmHitRatio < 0.3) {
// Low hit ratio, decrease TTL (down to 12 hours)
ttl = Math.max(12 * 60 * 60 * 1000, ttl * (0.8 - (0.3 - warmHitRatio)))
}
}
// If we have storage statistics with operation counts, adjust based on update frequency
if (this.storageStatistics && this.storageStatistics.operations) {
const ops = this.storageStatistics.operations
@ -597,14 +887,31 @@ export class CacheManager<T extends HNSWNode | Edge> {
// For rarely updated data, use longer TTL
if (updateRatio > 0.3) {
// Frequently updated, decrease TTL (down to 6 hours)
ttl = Math.max(6 * 60 * 60 * 1000, ttl * (1 - updateRatio))
ttl = Math.max(6 * 60 * 60 * 1000, ttl * (1 - updateRatio * 0.5))
} else if (updateRatio < 0.1) {
// Rarely updated, increase TTL (up to 48 hours)
ttl = Math.min(48 * 60 * 60 * 1000, ttl * (1.5 - updateRatio))
ttl = Math.min(48 * 60 * 60 * 1000, ttl * (1.2 - updateRatio))
}
}
}
// Check warm cache size relative to hot cache size
// If warm cache is much larger than hot cache, reduce TTL to prevent excessive storage use
if (stats.warmCacheSize > 0 && stats.hotCacheSize > 0) {
const warmToHotRatio = stats.warmCacheSize / stats.hotCacheSize
if (warmToHotRatio > 5) {
// Warm cache is much larger than hot cache, reduce TTL
ttl = Math.max(6 * 60 * 60 * 1000, ttl * (0.9 - Math.min(0.3, (warmToHotRatio - 5) / 20)))
}
}
// If we're in read-only mode, we can use a longer TTL
const isReadOnly = this.options?.readOnly || false
if (isReadOnly) {
ttl = Math.min(72 * 60 * 60 * 1000, ttl * 1.5)
}
// Update the warm cache TTL
this.warmCacheTTL = ttl
}
@ -621,6 +928,7 @@ export class CacheManager<T extends HNSWNode | Edge> {
* 5. Operating mode (read-only vs. read-write)
* 6. Storage type (S3, filesystem, memory)
* 7. Dataset size
* 8. Cache efficiency and access patterns
*
* Enhanced algorithm:
* - Start with a default based on the environment
@ -628,11 +936,17 @@ export class CacheManager<T extends HNSWNode | Edge> {
* - For read-only mode, use larger batches to improve throughput
* - Dynamically adjust based on network latency and throughput
* - Balance between memory usage and performance
* - Adapt to cache hit/miss patterns
*
* @param cacheStats Optional cache statistics for more adaptive tuning
*/
private tuneBatchSize(): void {
private tuneBatchSize(cacheStats?: CacheStats): void {
// Default batch size
let batchSize = 10
// Use provided cache stats or internal stats
const stats = cacheStats || this.getStats()
// Check if we're in read-only mode
const isReadOnly = this.options?.readOnly || false
@ -688,6 +1002,39 @@ export class CacheManager<T extends HNSWNode | Edge> {
batchSize = isReadOnly ? 20 : 15
}
// Adjust based on cache hit/miss ratios
const totalHotAccesses = stats.hotCacheHits + stats.hotCacheMisses
const totalWarmAccesses = stats.warmCacheHits + stats.warmCacheMisses
if (totalHotAccesses > 100) {
const hotHitRatio = stats.hotCacheHits / totalHotAccesses
// If hot cache hit ratio is high, we're effectively using the cache
// so we can use larger batches for better throughput
if (hotHitRatio > 0.8) {
// High hit ratio, increase batch size
batchSize = Math.min(batchSize * 1.5, isRemoteStorage ? 250 : 150)
} else if (hotHitRatio < 0.4) {
// Low hit ratio, we might be fetching too much at once
// Reduce batch size to be more selective
batchSize = Math.max(5, batchSize * 0.8)
}
}
if (totalWarmAccesses > 50) {
const warmHitRatio = stats.warmCacheHits / totalWarmAccesses
// If warm cache hit ratio is high, prefetching is effective
// so we can use larger batches
if (warmHitRatio > 0.7) {
// High warm hit ratio, increase batch size
batchSize = Math.min(batchSize * 1.3, isRemoteStorage ? 200 : 120)
} else if (warmHitRatio < 0.3) {
// Low warm hit ratio, reduce batch size
batchSize = Math.max(5, batchSize * 0.9)
}
}
// If we have storage statistics with operation counts, adjust based on operation patterns
if (this.storageStatistics && this.storageStatistics.operations) {
const ops = this.storageStatistics.operations
@ -721,10 +1068,20 @@ export class CacheManager<T extends HNSWNode | Edge> {
}
}
// Adjust based on hit/miss ratio if we have enough data
const totalAccesses = this.stats.hits + this.stats.misses
// Check if we're experiencing memory pressure
if (stats.hotCacheSize > 0 && this.hotCacheMaxSize > 0) {
const cacheUtilization = stats.hotCacheSize / this.hotCacheMaxSize
// If cache utilization is high, reduce batch size to avoid memory pressure
if (cacheUtilization > 0.85) {
batchSize = Math.max(5, Math.floor(batchSize * 0.8))
}
}
// Adjust based on overall hit/miss ratio if we have enough data
const totalAccesses = stats.hotCacheHits + stats.hotCacheMisses + stats.warmCacheHits + stats.warmCacheMisses
if (totalAccesses > 100) {
const hitRatio = this.stats.hits / totalAccesses
const hitRatio = (stats.hotCacheHits + stats.warmCacheHits) / totalAccesses
// Base adjustment factors
let increaseFactorForLowHitRatio = isRemoteStorage ? 1.5 : 1.2
@ -774,8 +1131,8 @@ export class CacheManager<T extends HNSWNode | Edge> {
batchSize = Math.min(maxBatchSize, batchSize)
// Update the batch size
this.batchSize = batchSize
// Update the batch size with the adaptively tuned value
this.batchSize = Math.round(batchSize)
}
/**
@ -1081,7 +1438,13 @@ export class CacheManager<T extends HNSWNode | Edge> {
misses: 0,
evictions: 0,
size: 0,
maxSize: this.hotCacheMaxSize
maxSize: this.hotCacheMaxSize,
hotCacheSize: 0,
warmCacheSize: 0,
hotCacheHits: 0,
hotCacheMisses: 0,
warmCacheHits: 0,
warmCacheMisses: 0
}
}