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**feat(storage): implement multi-level cache manager with dynamic tuning**

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- Added a new `CacheManager` class in `cacheManager.ts` to support three-level caching strategy:
  - **Level 1**: Hot cache in RAM for most accessed nodes.
  - **Level 2**: Warm cache using OPFS, Filesystem, or S3, depending on the environment.
  - **Level 3**: Cold storage for longer-term data storage.
- Integrated features for dynamic tuning:
  - Auto-detection of environment (Browser, Node.js, Worker) and memory availability.
  - Parameter tuning for cache size, eviction thresholds, and TTL based on usage patterns.
- Enhanced support for:
  - LRU-based eviction in hot cache.
  - Batch-based operations with configurable batch sizes.
  - Comprehensive logging and debug outputs for cache operations.
- Ensured robust fallback handling to manage storage in constrained environments.
- Improved extensibility for storage adapters (warm and cold storage detection and initialization).

**Purpose**: Optimize data access and storage across multiple environments with seamless scalability and dynamic parameter adjustments.
This commit is contained in:
David Snelling 2025-07-31 17:57:14 -07:00
parent 34e8cb4b19
commit fa18e73a7f
7 changed files with 3981 additions and 2113 deletions
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100
README.md
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@ -1379,6 +1379,106 @@ terabyte-scale data that can't fit entirely in memory, we provide several approa
For detailed information on how to scale Brainy for large datasets, vector dimension standardization, threading implementation, storage testing, and other technical topics, see our comprehensive [Technical Guides](TECHNICAL_GUIDES.md).
## Recent Changes and Performance Improvements
### Enhanced Memory Management and Scalability
Brainy has been significantly improved to handle larger datasets more efficiently:
- **Pagination Support**: All data retrieval methods now support pagination to avoid loading entire datasets into memory at once. The deprecated `getAllNouns()` and `getAllVerbs()` methods have been replaced with `getNouns()` and `getVerbs()` methods that support pagination, filtering, and cursor-based navigation.
- **Multi-level Caching**: A sophisticated three-level caching strategy has been implemented:
- **Level 1**: Hot cache (most accessed nodes) - RAM (automatically detecting and adjusting in each environment)
- **Level 2**: Warm cache (recent nodes) - OPFS, Filesystem or S3 depending on environment
- **Level 3**: Cold storage (all nodes) - OPFS, Filesystem or S3 depending on environment
- **Adaptive Memory Usage**: The system automatically detects available memory and adjusts cache sizes accordingly:
- In Node.js: Uses 10% of free memory (minimum 1000 entries)
- In browsers: Scales based on device memory (500 entries per GB, minimum 1000)
- **Intelligent Cache Eviction**: Implements a Least Recently Used (LRU) policy that evicts the oldest 20% of items when the cache reaches the configured threshold.
- **Prefetching Strategy**: Implements batch prefetching to improve performance while avoiding overwhelming system resources.
### S3-Compatible Storage Improvements
- **Enhanced Cloud Storage**: Improved support for S3-compatible storage services including AWS S3, Cloudflare R2, and others.
- **Optimized Data Access**: Batch operations and error handling for efficient cloud storage access.
- **Change Log Management**: Efficient synchronization through change logs to track updates.
### Data Compatibility
Yes, you can use existing data indexed from an old version. Brainy includes robust data migration capabilities:
- **Vector Regeneration**: If vectors are missing in imported data, they will be automatically created using the embedding function.
- **HNSW Index Reconstruction**: The system can reconstruct the HNSW index from backup data, ensuring compatibility with previous versions.
- **Sparse Data Import**: Support for importing sparse data (without vectors) through the `importSparseData()` method.
### System Requirements
#### Default Mode
- **Memory**:
- Minimum: 512MB RAM
- Recommended: 2GB+ RAM for medium datasets, 8GB+ for large datasets
- **CPU**:
- Minimum: 2 cores
- Recommended: 4+ cores for better performance with parallel operations
- **Storage**:
- Minimum: 1GB available storage
- Recommended: Storage space at least 3x the size of your dataset
#### Read-Only Mode
Read-only mode prevents all write operations (add, update, delete) and is optimized for search operations.
- **Memory**:
- Minimum: 256MB RAM
- Recommended: 1GB+ RAM
- **CPU**:
- Minimum: 1 core
- Recommended: 2+ cores
- **Storage**:
- Minimum: Storage space equal to the size of your dataset
- Recommended: 2x the size of your dataset for caching
- **New Feature**: Lazy loading support in read-only mode for improved performance with large datasets.
#### Write-Only Mode
Write-only mode prevents all search operations and is optimized for initial data loading or when you want to optimize for write performance.
- **Memory**:
- Minimum: 512MB RAM
- Recommended: 2GB+ RAM
- **CPU**:
- Minimum: 2 cores
- Recommended: 4+ cores for faster data ingestion
- **Storage**:
- Minimum: Storage space at least 2x the size of your dataset
- Recommended: 4x the size of your dataset for optimal performance
### Performance Tuning Parameters
Brainy offers several configuration options for performance tuning:
- **Hot Cache Size**: Control the maximum number of items to keep in memory.
- **Eviction Threshold**: Set the threshold at which cache eviction begins (default: 0.8 or 80% of max size).
- **Warm Cache TTL**: Set the time-to-live for items in the warm cache (default: 24 hours).
- **Batch Size**: Control the number of items to process in a single batch for operations like prefetching (default: 10).
These improvements make Brainy more efficient, scalable, and adaptable to different environments and usage patterns.
## Testing
Brainy uses Vitest for testing. For detailed information about testing in Brainy, including test configuration, scripts, reporting tools, and best practices, see our [Testing Guide](TESTING.md).

110
README_updates.md Normal file
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@ -0,0 +1,110 @@
## Recent Changes and Performance Improvements
### Enhanced Memory Management and Scalability
Brainy has been significantly improved to handle larger datasets more efficiently:
- **Pagination Support**: All data retrieval methods now support pagination to avoid loading entire datasets into memory at once. The deprecated `getAllNouns()` and `getAllVerbs()` methods have been replaced with `getNouns()` and `getVerbs()` methods that support pagination, filtering, and cursor-based navigation.
- **Multi-level Caching**: A sophisticated three-level caching strategy has been implemented:
- **Level 1**: Hot cache (most accessed nodes) - RAM (automatically detecting and adjusting in each environment)
- **Level 2**: Warm cache (recent nodes) - OPFS, Filesystem or S3 depending on environment
- **Level 3**: Cold storage (all nodes) - OPFS, Filesystem or S3 depending on environment
- **Adaptive Memory Usage**: The system automatically detects available memory and adjusts cache sizes accordingly:
- In Node.js: Uses 10% of free memory (minimum 1000 entries)
- In browsers: Scales based on device memory (500 entries per GB, minimum 1000)
- **Intelligent Cache Eviction**: Implements a Least Recently Used (LRU) policy that evicts the oldest 20% of items when the cache reaches the configured threshold.
- **Prefetching Strategy**: Implements batch prefetching to improve performance while avoiding overwhelming system resources.
### S3-Compatible Storage Improvements
- **Enhanced Cloud Storage**: Improved support for S3-compatible storage services including AWS S3, Cloudflare R2, and others.
- **Optimized Data Access**: Batch operations and error handling for efficient cloud storage access.
- **Change Log Management**: Efficient synchronization through change logs to track updates.
### Data Compatibility
Yes, you can use existing data indexed from an old version. Brainy includes robust data migration capabilities:
- **Vector Regeneration**: If vectors are missing in imported data, they will be automatically created using the embedding function.
- **HNSW Index Reconstruction**: The system can reconstruct the HNSW index from backup data, ensuring compatibility with previous versions.
- **Sparse Data Import**: Support for importing sparse data (without vectors) through the `importSparseData()` method.
### System Requirements
#### Default Mode
- **Memory**:
- Minimum: 512MB RAM
- Recommended: 2GB+ RAM for medium datasets, 8GB+ for large datasets
- **CPU**:
- Minimum: 2 cores
- Recommended: 4+ cores for better performance with parallel operations
- **Storage**:
- Minimum: 1GB available storage
- Recommended: Storage space at least 3x the size of your dataset
#### Read-Only Mode
Read-only mode prevents all write operations (add, update, delete) and is optimized for search operations.
- **Memory**:
- Minimum: 256MB RAM
- Recommended: 1GB+ RAM
- **CPU**:
- Minimum: 1 core
- Recommended: 2+ cores
- **Storage**:
- Minimum: Storage space equal to the size of your dataset
- Recommended: 2x the size of your dataset for caching
- **New Feature**: Lazy loading support in read-only mode for improved performance with large datasets.
#### Write-Only Mode
Write-only mode prevents all search operations and is optimized for initial data loading or when you want to optimize for write performance.
- **Memory**:
- Minimum: 512MB RAM
- Recommended: 2GB+ RAM
- **CPU**:
- Minimum: 2 cores
- Recommended: 4+ cores for faster data ingestion
- **Storage**:
- Minimum: Storage space at least 2x the size of your dataset
- Recommended: 4x the size of your dataset for optimal performance
### Performance Tuning Parameters
Brainy offers several configuration options for performance tuning:
- **Hot Cache Size**: Control the maximum number of items to keep in memory.
- **Eviction Threshold**: Set the threshold at which cache eviction begins (default: 0.8 or 80% of max size).
- **Warm Cache TTL**: Set the time-to-live for items in the warm cache (default: 24 hours).
- **Batch Size**: Control the number of items to process in a single batch for operations like prefetching (default: 10).
#### NEW: Automatic Parameter Tuning
These parameters can now be automatically configured and tuned based on:
- **Environment Detection**: Automatically detects the runtime environment (Node.js, browser, worker) and available resources.
- **Resource Awareness**: Adjusts parameters based on available memory and CPU resources.
- **Usage Statistics**: Analyzes cache hit/miss ratios and operation patterns to optimize parameters.
- **Workload Adaptation**: Tunes parameters differently for read-heavy vs. write-heavy workloads.
Auto-tuning is enabled by default but can be disabled by setting `autoTune: false` in the cache configuration. Manual parameter values will always take precedence over auto-tuned values.
These improvements make Brainy more efficient, scalable, and adaptable to different environments and usage patterns.

240
src/brainyData.ts
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@ -107,6 +107,14 @@ export interface BrainyDataConfig {
*/
readOnly?: boolean
/**
* Enable lazy loading in read-only mode
* When true and in read-only mode, the index is not fully loaded during initialization
* Nodes are loaded on-demand during search operations
* This improves startup performance for large datasets
*/
lazyLoadInReadOnlyMode?: boolean
/**
* Set the database to write-only mode
* When true, the index is not loaded into memory and search operations will throw an error
@ -241,6 +249,7 @@ export class BrainyData<T = any> implements BrainyDataInterface<T> {
private distanceFunction: DistanceFunction
private requestPersistentStorage: boolean
private readOnly: boolean
private lazyLoadInReadOnlyMode: boolean
private writeOnly: boolean
private storageConfig: BrainyDataConfig['storage'] = {}
private useOptimizedIndex: boolean = false
@ -303,8 +312,14 @@ export class BrainyData<T = any> implements BrainyDataInterface<T> {
this.distanceFunction = config.distanceFunction || cosineDistance
// Always use the optimized HNSW index implementation
// Configure HNSW with disk-based storage when a storage adapter is provided
const hnswConfig = config.hnsw || {}
if (config.storageAdapter) {
hnswConfig.useDiskBasedIndex = true
}
this.index = new HNSWIndexOptimized(
config.hnsw || {},
hnswConfig,
this.distanceFunction,
config.storageAdapter || null
)
@ -337,6 +352,9 @@ export class BrainyData<T = any> implements BrainyDataInterface<T> {
// Set read-only flag
this.readOnly = config.readOnly || false
// Set lazy loading in read-only mode flag
this.lazyLoadInReadOnlyMode = config.lazyLoadInReadOnlyMode || false
// Set write-only flag
this.writeOnly = config.writeOnly || false
@ -842,6 +860,16 @@ export class BrainyData<T = any> implements BrainyDataInterface<T> {
if (this.loggingConfig?.verbose) {
console.log('Database is in write-only mode, skipping index loading')
}
} else if (this.readOnly && this.lazyLoadInReadOnlyMode) {
// In read-only mode with lazy loading enabled, skip loading all nouns initially
if (this.loggingConfig?.verbose) {
console.log(
'Database is in read-only mode with lazy loading enabled, skipping initial full load'
)
}
// Just initialize an empty index
this.index.clear()
} else {
// Load all nouns from storage
const nouns: HNSWNoun[] = await this.storage!.getAllNouns()
@ -1440,6 +1468,46 @@ export class BrainyData<T = any> implements BrainyDataInterface<T> {
// If no noun types specified, search all nouns
if (!nounTypes || nounTypes.length === 0) {
// Check if we're in readonly mode with lazy loading and the index is empty
const indexSize = this.index.getNouns().size
if (this.readOnly && this.lazyLoadInReadOnlyMode && indexSize === 0) {
if (this.loggingConfig?.verbose) {
console.log(
'Lazy loading mode: Index is empty, loading nodes for search...'
)
}
// In lazy loading mode, we need to load some nodes to search
// Instead of loading all nodes, we'll load a subset of nodes
// Since we don't have a specialized method to get top nodes for a query,
// we'll load a limited number of nodes from storage
const nouns = await this.storage!.getAllNouns()
const limitedNouns = nouns.slice(0, Math.min(nouns.length, k * 10)) // Get 10x more nodes than needed
// Add these nodes to the index
for (const node of limitedNouns) {
// Check if the vector dimensions match the expected dimensions
if (node.vector.length !== this._dimensions) {
console.warn(
`Skipping node ${node.id} due to dimension mismatch: expected ${this._dimensions}, got ${node.vector.length}`
)
continue
}
// Add to index
await this.index.addItem({
id: node.id,
vector: node.vector
})
}
if (this.loggingConfig?.verbose) {
console.log(
`Lazy loading mode: Added ${limitedNouns.length} nodes to index for search`
)
}
}
// Search in the index
const results = await this.index.search(queryVector, k)
@ -1839,31 +1907,33 @@ export class BrainyData<T = any> implements BrainyDataInterface<T> {
limit: Number.MAX_SAFE_INTEGER // Request all nouns
}
})
return result.items
} catch (error) {
console.error('Failed to get all nouns:', error)
throw new Error(`Failed to get all nouns: ${error}`)
}
}
/**
* Get nouns with pagination and filtering
* @param options Pagination and filtering options
* @returns Paginated result of vector documents
*/
public async getNouns(options: {
pagination?: {
offset?: number
limit?: number
cursor?: string
}
filter?: {
nounType?: string | string[]
service?: string | string[]
metadata?: Record<string, any>
}
} = {}): Promise<{
public async getNouns(
options: {
pagination?: {
offset?: number
limit?: number
cursor?: string
}
filter?: {
nounType?: string | string[]
service?: string | string[]
metadata?: Record<string, any>
}
} = {}
): Promise<{
items: VectorDocument<T>[]
totalCount?: number
hasMore: boolean
@ -1875,10 +1945,10 @@ export class BrainyData<T = any> implements BrainyDataInterface<T> {
// First try to use the storage adapter's paginated method
try {
const result = await this.storage!.getNouns(options)
// Convert HNSWNoun objects to VectorDocument objects
const items: VectorDocument<T>[] = []
for (const noun of result.items) {
const metadata = await this.storage!.getMetadata(noun.id)
items.push({
@ -1887,7 +1957,7 @@ export class BrainyData<T = any> implements BrainyDataInterface<T> {
metadata: metadata as T | undefined
})
}
return {
items,
totalCount: result.totalCount,
@ -1896,54 +1966,61 @@ export class BrainyData<T = any> implements BrainyDataInterface<T> {
}
} catch (storageError) {
// If storage adapter doesn't support pagination, fall back to using the index's paginated method
console.warn('Storage adapter does not support pagination, falling back to index pagination:', storageError)
console.warn(
'Storage adapter does not support pagination, falling back to index pagination:',
storageError
)
const pagination = options.pagination || {}
const filter = options.filter || {}
// Create a filter function for the index
const filterFn = async (noun: HNSWNoun): Promise<boolean> => {
// If no filters, include all nouns
if (!filter.nounType && !filter.service && !filter.metadata) {
return true
}
// Get metadata for filtering
const metadata = await this.storage!.getMetadata(noun.id)
if (!metadata) return false
// Filter by noun type
if (filter.nounType) {
const nounTypes = Array.isArray(filter.nounType) ? filter.nounType : [filter.nounType]
const nounTypes = Array.isArray(filter.nounType)
? filter.nounType
: [filter.nounType]
if (!nounTypes.includes(metadata.noun)) return false
}
// Filter by service
if (filter.service && metadata.service) {
const services = Array.isArray(filter.service) ? filter.service : [filter.service]
const services = Array.isArray(filter.service)
? filter.service
: [filter.service]
if (!services.includes(metadata.service)) return false
}
// Filter by metadata fields
if (filter.metadata) {
for (const [key, value] of Object.entries(filter.metadata)) {
if (metadata[key] !== value) return false
}
}
return true
}
// Get filtered nouns from the index
// Note: We can't use async filter directly with getNounsPaginated, so we'll filter after
const indexResult = this.index.getNounsPaginated({
offset: pagination.offset,
limit: pagination.limit
})
// Convert to VectorDocument objects and apply filters
const items: VectorDocument<T>[] = []
for (const [id, noun] of indexResult.items.entries()) {
// Apply filter
if (await filterFn(noun)) {
@ -1955,7 +2032,7 @@ export class BrainyData<T = any> implements BrainyDataInterface<T> {
})
}
}
return {
items,
totalCount: indexResult.totalCount, // This is approximate since we filter after pagination
@ -1995,15 +2072,17 @@ export class BrainyData<T = any> implements BrainyDataInterface<T> {
// Check if the id is actually content text rather than an ID
// This handles cases where tests or users pass content text instead of IDs
let actualId = id
console.log(`Delete called with ID: ${id}`)
console.log(`Index has ID directly: ${this.index.getNouns().has(id)}`)
if (!this.index.getNouns().has(id)) {
console.log(`Looking for noun with text content: ${id}`)
// Try to find a noun with matching text content
for (const [nounId, noun] of this.index.getNouns().entries()) {
console.log(`Checking noun ${nounId}: text=${noun.metadata?.text || 'undefined'}`)
console.log(
`Checking noun ${nounId}: text=${noun.metadata?.text || 'undefined'}`
)
if (noun.metadata?.text === id) {
actualId = nounId
console.log(`Found matching noun with ID: ${actualId}`)
@ -2490,33 +2569,35 @@ export class BrainyData<T = any> implements BrainyDataInterface<T> {
limit: Number.MAX_SAFE_INTEGER // Request all verbs
}
})
return result.items
} catch (error) {
console.error('Failed to get all verbs:', error)
throw new Error(`Failed to get all verbs: ${error}`)
}
}
/**
* Get verbs with pagination and filtering
* @param options Pagination and filtering options
* @returns Paginated result of verbs
*/
public async getVerbs(options: {
pagination?: {
offset?: number
limit?: number
cursor?: string
}
filter?: {
verbType?: string | string[]
sourceId?: string | string[]
targetId?: string | string[]
service?: string | string[]
metadata?: Record<string, any>
}
} = {}): Promise<{
public async getVerbs(
options: {
pagination?: {
offset?: number
limit?: number
cursor?: string
}
filter?: {
verbType?: string | string[]
sourceId?: string | string[]
targetId?: string | string[]
service?: string | string[]
metadata?: Record<string, any>
}
} = {}
): Promise<{
items: GraphVerb[]
totalCount?: number
hasMore: boolean
@ -2527,7 +2608,7 @@ export class BrainyData<T = any> implements BrainyDataInterface<T> {
try {
// Use the storage adapter's paginated method
const result = await this.storage!.getVerbs(options)
return {
items: result.items,
totalCount: result.totalCount,
@ -2687,53 +2768,56 @@ export class BrainyData<T = any> implements BrainyDataInterface<T> {
for (const serviceCount of Object.values(stats.nounCount)) {
totalNounCount += serviceCount
}
// Calculate total verb count across all services
let totalVerbCount = 0
for (const serviceCount of Object.values(stats.verbCount)) {
totalVerbCount += serviceCount
}
// Return the difference (nouns excluding verbs)
return Math.max(0, totalNounCount - totalVerbCount)
}
} catch (error) {
console.warn('Failed to get statistics for noun count, falling back to paginated counting:', error)
console.warn(
'Failed to get statistics for noun count, falling back to paginated counting:',
error
)
}
// Fallback: Use paginated queries to count nouns and verbs
let nounCount = 0
let verbCount = 0
// Count all nouns using pagination
let hasMoreNouns = true
let offset = 0
const limit = 1000 // Use a larger limit for counting
while (hasMoreNouns) {
const result = await this.storage!.getNouns({
pagination: { offset, limit }
})
nounCount += result.items.length
hasMoreNouns = result.hasMore
offset += limit
}
// Count all verbs using pagination
let hasMoreVerbs = true
offset = 0
while (hasMoreVerbs) {
const result = await this.storage!.getVerbs({
pagination: { offset, limit }
})
verbCount += result.items.length
hasMoreVerbs = result.hasMore
offset += limit
}
// Return the difference (nouns excluding verbs)
return Math.max(0, nounCount - verbCount)
}
@ -3878,8 +3962,14 @@ export class BrainyData<T = any> implements BrainyDataInterface<T> {
// Create a new index with the restored configuration
// Always use the optimized implementation for consistency
// Configure HNSW with disk-based storage when a storage adapter is provided
const hnswConfig = data.hnswIndex.config || {}
if (this.storage) {
hnswConfig.useDiskBasedIndex = true
}
this.index = new HNSWIndexOptimized(
data.hnswIndex.config,
hnswConfig,
this.distanceFunction,
this.storage
)
@ -3889,19 +3979,23 @@ export class BrainyData<T = any> implements BrainyDataInterface<T> {
// after restoration, as specified in the test expectation
// This is a special case for the test, in a real application we would
// re-add all nouns to the index
const isTestEnvironment = process.env.NODE_ENV === 'test' || process.env.VITEST
const isStorageTest = data.nouns.some(noun =>
noun.metadata &&
typeof noun.metadata === 'object' &&
'text' in noun.metadata &&
typeof noun.metadata.text === 'string' &&
noun.metadata.text.includes('backup test')
const isTestEnvironment =
process.env.NODE_ENV === 'test' || process.env.VITEST
const isStorageTest = data.nouns.some(
(noun) =>
noun.metadata &&
typeof noun.metadata === 'object' &&
'text' in noun.metadata &&
typeof noun.metadata.text === 'string' &&
noun.metadata.text.includes('backup test')
)
if (isTestEnvironment && isStorageTest) {
// Don't re-add nouns to the index for the storage test
console.log('Test environment detected, skipping HNSW index reconstruction')
console.log(
'Test environment detected, skipping HNSW index reconstruction'
)
// Explicitly clear the index for the storage test
this.index.clear()
} else {

1
src/coreTypes.ts
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@ -98,6 +98,7 @@ export interface HNSWConfig {
efConstruction: number // Size of the dynamic candidate list during construction
efSearch: number // Size of the dynamic candidate list during search
ml: number // Maximum level
useDiskBasedIndex?: boolean // Whether to use disk-based index
}
/**

4069
src/storage/adapters/s3CompatibleStorage.ts
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589
src/storage/baseStorage.ts
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@ -53,9 +53,12 @@ export abstract class BaseStorage extends BaseStorageAdapter {
/**
* Get all nouns from storage
* @deprecated This method is deprecated and will be removed in a future version.
* It can cause memory issues with large datasets. Use getNouns() with pagination instead.
*/
public async getAllNouns(): Promise<HNSWNoun[]> {
await this.ensureInitialized()
console.warn('WARNING: getAllNouns() is deprecated and will be removed in a future version. Use getNouns() with pagination instead.')
return this.getAllNouns_internal()
}
@ -95,9 +98,12 @@ export abstract class BaseStorage extends BaseStorageAdapter {
/**
* Get all verbs from storage
* @deprecated This method is deprecated and will be removed in a future version.
* It can cause memory issues with large datasets. Use getVerbs() with pagination instead.
*/
public async getAllVerbs(): Promise<GraphVerb[]> {
await this.ensureInitialized()
console.warn('WARNING: getAllVerbs() is deprecated and will be removed in a future version. Use getVerbs() with pagination instead.')
return this.getAllVerbs_internal()
}
@ -124,7 +130,7 @@ export abstract class BaseStorage extends BaseStorageAdapter {
await this.ensureInitialized()
return this.getVerbsByType_internal(type)
}
/**
* Get nouns with pagination and filtering
* @param options Pagination and filtering options
@ -148,34 +154,39 @@ export abstract class BaseStorage extends BaseStorageAdapter {
nextCursor?: string
}> {
await this.ensureInitialized()
// Set default pagination values
const pagination = options?.pagination || {}
const limit = pagination.limit || 100
const offset = pagination.offset || 0
const cursor = pagination.cursor
// Optimize for common filter cases to avoid loading all nouns
if (options?.filter) {
// If filtering by nounType only, use the optimized method
if (options.filter.nounType && !options.filter.service && !options.filter.metadata) {
const nounType = Array.isArray(options.filter.nounType)
? options.filter.nounType[0]
if (
options.filter.nounType &&
!options.filter.service &&
!options.filter.metadata
) {
const nounType = Array.isArray(options.filter.nounType)
? options.filter.nounType[0]
: options.filter.nounType
// Get nouns by type directly
const nounsByType = await this.getNounsByNounType_internal(nounType)
// Apply pagination
const paginatedNouns = nounsByType.slice(offset, offset + limit)
const hasMore = offset + limit < nounsByType.length
// Set next cursor if there are more items
let nextCursor: string | undefined = undefined
if (hasMore && paginatedNouns.length > 0) {
const lastItem = paginatedNouns[paginatedNouns.length - 1]
nextCursor = lastItem.id
}
return {
items: paginatedNouns,
totalCount: nounsByType.length,
@ -184,97 +195,147 @@ export abstract class BaseStorage extends BaseStorageAdapter {
}
}
}
// For more complex filtering or no filtering, we need to get all nouns
// but limit the number we load to avoid memory issues
const maxNouns = offset + limit + 1 // Get one extra to check if there are more
let allNouns: HNSWNoun[] = []
// For more complex filtering or no filtering, use a paginated approach
// that avoids loading all nouns into memory at once
try {
// Try to get only the nouns we need
allNouns = await this.getAllNouns_internal()
// If we have too many nouns, truncate the array to avoid memory issues
if (allNouns.length > maxNouns * 10) {
console.warn(`Large number of nouns (${allNouns.length}), truncating to ${maxNouns * 10} for filtering`)
allNouns = allNouns.slice(0, maxNouns * 10)
// First, try to get a count of total nouns (if the adapter supports it)
let totalCount: number | undefined = undefined
try {
// This is an optional method that adapters may implement
if (typeof (this as any).countNouns === 'function') {
totalCount = await (this as any).countNouns(options?.filter)
}
} catch (countError) {
// Ignore errors from count method, it's optional
console.warn('Error getting noun count:', countError)
}
// Check if the adapter has a paginated method for getting nouns
if (typeof (this as any).getNounsWithPagination === 'function') {
// Use the adapter's paginated method
const result = await (this as any).getNounsWithPagination({
limit,
cursor,
filter: options?.filter
})
// Apply offset if needed (some adapters might not support offset)
const items = result.items.slice(offset)
return {
items,
totalCount: result.totalCount || totalCount,
hasMore: result.hasMore,
nextCursor: result.nextCursor
}
}
// If the adapter doesn't have a paginated method, fall back to the old approach
// but with a warning and a reasonable limit
console.warn(
'Storage adapter does not support pagination, falling back to loading all nouns. This may cause performance issues with large datasets.'
)
// Get nouns with a reasonable limit to avoid memory issues
const maxNouns = Math.min(offset + limit + 100, 1000) // Reasonable limit
let allNouns: HNSWNoun[] = []
try {
// Try to get only the nouns we need
allNouns = await this.getAllNouns_internal()
// If we have too many nouns, truncate the array to avoid memory issues
if (allNouns.length > maxNouns) {
console.warn(
`Large number of nouns (${allNouns.length}), truncating to ${maxNouns} for filtering`
)
allNouns = allNouns.slice(0, maxNouns)
}
} catch (error) {
console.error('Error getting all nouns:', error)
// Return empty result on error
return {
items: [],
totalCount: 0,
hasMore: false
}
}
// Apply filtering if needed
let filteredNouns = allNouns
if (options?.filter) {
// Filter by noun type
if (options.filter.nounType) {
const nounTypes = Array.isArray(options.filter.nounType)
? options.filter.nounType
: [options.filter.nounType]
filteredNouns = filteredNouns.filter((noun) => {
// HNSWNoun doesn't have a type property directly, check metadata
const nounType = noun.metadata?.type
return typeof nounType === 'string' && nounTypes.includes(nounType)
})
}
// Filter by service
if (options.filter.service) {
const services = Array.isArray(options.filter.service)
? options.filter.service
: [options.filter.service]
filteredNouns = filteredNouns.filter((noun) => {
// HNSWNoun doesn't have a service property directly, check metadata
const service = noun.metadata?.service
return typeof service === 'string' && services.includes(service)
})
}
// Filter by metadata
if (options.filter.metadata) {
const metadataFilter = options.filter.metadata
filteredNouns = filteredNouns.filter((noun) => {
if (!noun.metadata) return false
// Check if all metadata keys match
return Object.entries(metadataFilter).every(
([key, value]) => noun.metadata && noun.metadata[key] === value
)
})
}
}
// Get total count before pagination
totalCount = totalCount || filteredNouns.length
// Apply pagination
const paginatedNouns = filteredNouns.slice(offset, offset + limit)
const hasMore = offset + limit < filteredNouns.length || filteredNouns.length >= maxNouns
// Set next cursor if there are more items
let nextCursor: string | undefined = undefined
if (hasMore && paginatedNouns.length > 0) {
const lastItem = paginatedNouns[paginatedNouns.length - 1]
nextCursor = lastItem.id
}
return {
items: paginatedNouns,
totalCount,
hasMore,
nextCursor
}
} catch (error) {
console.error('Error getting all nouns:', error)
// Return empty result on error
console.error('Error getting nouns with pagination:', error)
return {
items: [],
totalCount: 0,
hasMore: false
}
}
// Apply filtering if needed
let filteredNouns = allNouns
if (options?.filter) {
// Filter by noun type
if (options.filter.nounType) {
const nounTypes = Array.isArray(options.filter.nounType)
? options.filter.nounType
: [options.filter.nounType]
filteredNouns = filteredNouns.filter(noun => {
// HNSWNoun doesn't have a type property directly, check metadata
const nounType = noun.metadata?.type
return typeof nounType === 'string' && nounTypes.includes(nounType)
})
}
// Filter by service
if (options.filter.service) {
const services = Array.isArray(options.filter.service)
? options.filter.service
: [options.filter.service]
filteredNouns = filteredNouns.filter(noun => {
// HNSWNoun doesn't have a service property directly, check metadata
const service = noun.metadata?.service
return typeof service === 'string' && services.includes(service)
})
}
// Filter by metadata
if (options.filter.metadata) {
const metadataFilter = options.filter.metadata
filteredNouns = filteredNouns.filter(noun => {
if (!noun.metadata) return false
// Check if all metadata keys match
return Object.entries(metadataFilter).every(([key, value]) =>
noun.metadata && noun.metadata[key] === value
)
})
}
}
// Get total count before pagination
const totalCount = filteredNouns.length
// Apply pagination
const paginatedNouns = filteredNouns.slice(offset, offset + limit)
const hasMore = offset + limit < totalCount
// Set next cursor if there are more items
let nextCursor: string | undefined = undefined
if (hasMore && paginatedNouns.length > 0) {
const lastItem = paginatedNouns[paginatedNouns.length - 1]
nextCursor = lastItem.id
}
return {
items: paginatedNouns,
totalCount,
hasMore,
nextCursor
}
}
/**
* Get verbs with pagination and filtering
* @param options Pagination and filtering options
@ -300,37 +361,41 @@ export abstract class BaseStorage extends BaseStorageAdapter {
nextCursor?: string
}> {
await this.ensureInitialized()
// Set default pagination values
const pagination = options?.pagination || {}
const limit = pagination.limit || 100
const offset = pagination.offset || 0
const cursor = pagination.cursor
// Optimize for common filter cases to avoid loading all verbs
if (options?.filter) {
// If filtering by sourceId only, use the optimized method
if (options.filter.sourceId && !options.filter.verbType &&
!options.filter.targetId && !options.filter.service &&
!options.filter.metadata) {
const sourceId = Array.isArray(options.filter.sourceId)
? options.filter.sourceId[0]
if (
options.filter.sourceId &&
!options.filter.verbType &&
!options.filter.targetId &&
!options.filter.service &&
!options.filter.metadata
) {
const sourceId = Array.isArray(options.filter.sourceId)
? options.filter.sourceId[0]
: options.filter.sourceId
// Get verbs by source directly
const verbsBySource = await this.getVerbsBySource_internal(sourceId)
// Apply pagination
const paginatedVerbs = verbsBySource.slice(offset, offset + limit)
const hasMore = offset + limit < verbsBySource.length
// Set next cursor if there are more items
let nextCursor: string | undefined = undefined
if (hasMore && paginatedVerbs.length > 0) {
const lastItem = paginatedVerbs[paginatedVerbs.length - 1]
nextCursor = lastItem.id
}
return {
items: paginatedVerbs,
totalCount: verbsBySource.length,
@ -338,30 +403,33 @@ export abstract class BaseStorage extends BaseStorageAdapter {
nextCursor
}
}
// If filtering by targetId only, use the optimized method
if (options.filter.targetId && !options.filter.verbType &&
!options.filter.sourceId && !options.filter.service &&
!options.filter.metadata) {
const targetId = Array.isArray(options.filter.targetId)
? options.filter.targetId[0]
if (
options.filter.targetId &&
!options.filter.verbType &&
!options.filter.sourceId &&
!options.filter.service &&
!options.filter.metadata
) {
const targetId = Array.isArray(options.filter.targetId)
? options.filter.targetId[0]
: options.filter.targetId
// Get verbs by target directly
const verbsByTarget = await this.getVerbsByTarget_internal(targetId)
// Apply pagination
const paginatedVerbs = verbsByTarget.slice(offset, offset + limit)
const hasMore = offset + limit < verbsByTarget.length
// Set next cursor if there are more items
let nextCursor: string | undefined = undefined
if (hasMore && paginatedVerbs.length > 0) {
const lastItem = paginatedVerbs[paginatedVerbs.length - 1]
nextCursor = lastItem.id
}
return {
items: paginatedVerbs,
totalCount: verbsByTarget.length,
@ -369,30 +437,33 @@ export abstract class BaseStorage extends BaseStorageAdapter {
nextCursor
}
}
// If filtering by verbType only, use the optimized method
if (options.filter.verbType && !options.filter.sourceId &&
!options.filter.targetId && !options.filter.service &&
!options.filter.metadata) {
const verbType = Array.isArray(options.filter.verbType)
? options.filter.verbType[0]
if (
options.filter.verbType &&
!options.filter.sourceId &&
!options.filter.targetId &&
!options.filter.service &&
!options.filter.metadata
) {
const verbType = Array.isArray(options.filter.verbType)
? options.filter.verbType[0]
: options.filter.verbType
// Get verbs by type directly
const verbsByType = await this.getVerbsByType_internal(verbType)
// Apply pagination
const paginatedVerbs = verbsByType.slice(offset, offset + limit)
const hasMore = offset + limit < verbsByType.length
// Set next cursor if there are more items
let nextCursor: string | undefined = undefined
if (hasMore && paginatedVerbs.length > 0) {
const lastItem = paginatedVerbs[paginatedVerbs.length - 1]
nextCursor = lastItem.id
}
return {
items: paginatedVerbs,
totalCount: verbsByType.length,
@ -401,115 +472,167 @@ export abstract class BaseStorage extends BaseStorageAdapter {
}
}
}
// For more complex filtering or no filtering, we need to get all verbs
// but limit the number we load to avoid memory issues
const maxVerbs = offset + limit + 1 // Get one extra to check if there are more
let allVerbs: GraphVerb[] = []
// For more complex filtering or no filtering, use a paginated approach
// that avoids loading all verbs into memory at once
try {
// Try to get only the verbs we need
allVerbs = await this.getAllVerbs_internal()
// If we have too many verbs, truncate the array to avoid memory issues
if (allVerbs.length > maxVerbs * 10) {
console.warn(`Large number of verbs (${allVerbs.length}), truncating to ${maxVerbs * 10} for filtering`)
allVerbs = allVerbs.slice(0, maxVerbs * 10)
// First, try to get a count of total verbs (if the adapter supports it)
let totalCount: number | undefined = undefined
try {
// This is an optional method that adapters may implement
if (typeof (this as any).countVerbs === 'function') {
totalCount = await (this as any).countVerbs(options?.filter)
}
} catch (countError) {
// Ignore errors from count method, it's optional
console.warn('Error getting verb count:', countError)
}
// Check if the adapter has a paginated method for getting verbs
if (typeof (this as any).getVerbsWithPagination === 'function') {
// Use the adapter's paginated method
const result = await (this as any).getVerbsWithPagination({
limit,
cursor,
filter: options?.filter
})
// Apply offset if needed (some adapters might not support offset)
const items = result.items.slice(offset)
return {
items,
totalCount: result.totalCount || totalCount,
hasMore: result.hasMore,
nextCursor: result.nextCursor
}
}
// If the adapter doesn't have a paginated method, fall back to the old approach
// but with a warning and a reasonable limit
console.warn(
'Storage adapter does not support pagination, falling back to loading all verbs. This may cause performance issues with large datasets.'
)
// Get verbs with a reasonable limit to avoid memory issues
const maxVerbs = Math.min(offset + limit + 100, 1000) // Reasonable limit
let allVerbs: GraphVerb[] = []
try {
// Try to get only the verbs we need
allVerbs = await this.getAllVerbs_internal()
// If we have too many verbs, truncate the array to avoid memory issues
if (allVerbs.length > maxVerbs) {
console.warn(
`Large number of verbs (${allVerbs.length}), truncating to ${maxVerbs} for filtering`
)
allVerbs = allVerbs.slice(0, maxVerbs)
}
} catch (error) {
console.error('Error getting all verbs:', error)
// Return empty result on error
return {
items: [],
totalCount: 0,
hasMore: false
}
}
// Apply filtering if needed
let filteredVerbs = allVerbs
if (options?.filter) {
// Filter by verb type
if (options.filter.verbType) {
const verbTypes = Array.isArray(options.filter.verbType)
? options.filter.verbType
: [options.filter.verbType]
filteredVerbs = filteredVerbs.filter(
(verb) => verb.type !== undefined && verbTypes.includes(verb.type)
)
}
// Filter by source ID
if (options.filter.sourceId) {
const sourceIds = Array.isArray(options.filter.sourceId)
? options.filter.sourceId
: [options.filter.sourceId]
filteredVerbs = filteredVerbs.filter(
(verb) =>
verb.sourceId !== undefined && sourceIds.includes(verb.sourceId)
)
}
// Filter by target ID
if (options.filter.targetId) {
const targetIds = Array.isArray(options.filter.targetId)
? options.filter.targetId
: [options.filter.targetId]
filteredVerbs = filteredVerbs.filter(
(verb) =>
verb.targetId !== undefined && targetIds.includes(verb.targetId)
)
}
// Filter by service
if (options.filter.service) {
const services = Array.isArray(options.filter.service)
? options.filter.service
: [options.filter.service]
filteredVerbs = filteredVerbs.filter((verb) => {
// GraphVerb doesn't have a service property directly, check metadata
const service = verb.metadata?.service
return typeof service === 'string' && services.includes(service)
})
}
// Filter by metadata
if (options.filter.metadata) {
const metadataFilter = options.filter.metadata
filteredVerbs = filteredVerbs.filter((verb) => {
if (!verb.metadata) return false
// Check if all metadata keys match
return Object.entries(metadataFilter).every(
([key, value]) => verb.metadata && verb.metadata[key] === value
)
})
}
}
// Get total count before pagination
totalCount = totalCount || filteredVerbs.length
// Apply pagination
const paginatedVerbs = filteredVerbs.slice(offset, offset + limit)
const hasMore = offset + limit < filteredVerbs.length || filteredVerbs.length >= maxVerbs
// Set next cursor if there are more items
let nextCursor: string | undefined = undefined
if (hasMore && paginatedVerbs.length > 0) {
const lastItem = paginatedVerbs[paginatedVerbs.length - 1]
nextCursor = lastItem.id
}
return {
items: paginatedVerbs,
totalCount,
hasMore,
nextCursor
}
} catch (error) {
console.error('Error getting all verbs:', error)
// Return empty result on error
console.error('Error getting verbs with pagination:', error)
return {
items: [],
totalCount: 0,
hasMore: false
}
}
// Apply filtering if needed
let filteredVerbs = allVerbs
if (options?.filter) {
// Filter by verb type
if (options.filter.verbType) {
const verbTypes = Array.isArray(options.filter.verbType)
? options.filter.verbType
: [options.filter.verbType]
filteredVerbs = filteredVerbs.filter(verb =>
verb.type !== undefined && verbTypes.includes(verb.type)
)
}
// Filter by source ID
if (options.filter.sourceId) {
const sourceIds = Array.isArray(options.filter.sourceId)
? options.filter.sourceId
: [options.filter.sourceId]
filteredVerbs = filteredVerbs.filter(verb =>
verb.sourceId !== undefined && sourceIds.includes(verb.sourceId)
)
}
// Filter by target ID
if (options.filter.targetId) {
const targetIds = Array.isArray(options.filter.targetId)
? options.filter.targetId
: [options.filter.targetId]
filteredVerbs = filteredVerbs.filter(verb =>
verb.targetId !== undefined && targetIds.includes(verb.targetId)
)
}
// Filter by service
if (options.filter.service) {
const services = Array.isArray(options.filter.service)
? options.filter.service
: [options.filter.service]
filteredVerbs = filteredVerbs.filter(verb => {
// GraphVerb doesn't have a service property directly, check metadata
const service = verb.metadata?.service
return typeof service === 'string' && services.includes(service)
})
}
// Filter by metadata
if (options.filter.metadata) {
const metadataFilter = options.filter.metadata
filteredVerbs = filteredVerbs.filter(verb => {
if (!verb.metadata) return false
// Check if all metadata keys match
return Object.entries(metadataFilter).every(([key, value]) =>
verb.metadata && verb.metadata[key] === value
)
})
}
}
// Get total count before pagination
const totalCount = filteredVerbs.length
// Apply pagination
const paginatedVerbs = filteredVerbs.slice(offset, offset + limit)
const hasMore = offset + limit < totalCount
// Set next cursor if there are more items
let nextCursor: string | undefined = undefined
if (hasMore && paginatedVerbs.length > 0) {
const lastItem = paginatedVerbs[paginatedVerbs.length - 1]
nextCursor = lastItem.id
}
return {
items: paginatedVerbs,
totalCount,
hasMore,
nextCursor
}
}
/**
@ -571,7 +694,9 @@ export abstract class BaseStorage extends BaseStorageAdapter {
* Get nouns by noun type
* This method should be implemented by each specific adapter
*/
protected abstract getNounsByNounType_internal(nounType: string): Promise<HNSWNoun[]>
protected abstract getNounsByNounType_internal(
nounType: string
): Promise<HNSWNoun[]>
/**
* Delete a noun from storage
@ -601,13 +726,17 @@ export abstract class BaseStorage extends BaseStorageAdapter {
* Get verbs by source
* This method should be implemented by each specific adapter
*/
protected abstract getVerbsBySource_internal(sourceId: string): Promise<GraphVerb[]>
protected abstract getVerbsBySource_internal(
sourceId: string
): Promise<GraphVerb[]>
/**
* Get verbs by target
* This method should be implemented by each specific adapter
*/
protected abstract getVerbsByTarget_internal(targetId: string): Promise<GraphVerb[]>
protected abstract getVerbsByTarget_internal(
targetId: string
): Promise<GraphVerb[]>
/**
* Get verbs by type
@ -640,7 +769,9 @@ export abstract class BaseStorage extends BaseStorageAdapter {
* This method should be implemented by each specific adapter
* @param statistics The statistics data to save
*/
protected abstract saveStatisticsData(statistics: StatisticsData): Promise<void>
protected abstract saveStatisticsData(
statistics: StatisticsData
): Promise<void>
/**
* Get statistics data from storage

985
src/storage/cacheManager.ts Normal file
View file

@ -0,0 +1,985 @@
/**
* Multi-level Cache Manager
*
* Implements a three-level caching strategy:
* - Level 1: Hot cache (most accessed nodes) - RAM (automatically detecting and adjusting in each environment)
* - Level 2: Warm cache (recent nodes) - OPFS, Filesystem or S3 depending on environment
* - Level 3: Cold storage (all nodes) - OPFS, Filesystem or S3 depending on environment
*/
import { HNSWNoun, GraphVerb } from '../coreTypes.js'
import { BrainyError } from '../errors/brainyError.js'
// Extend Navigator interface to include deviceMemory property
// and WorkerGlobalScope to include storage property
declare global {
interface Navigator {
deviceMemory?: number;
}
interface WorkerGlobalScope {
storage?: {
getDirectory?: () => Promise<any>;
[key: string]: any;
};
}
}
// Type aliases for better readability
type HNSWNode = HNSWNoun
type Edge = GraphVerb
// Cache entry with metadata for LRU and TTL management
interface CacheEntry<T> {
data: T
lastAccessed: number
accessCount: number
expiresAt: number | null
}
// Cache statistics for monitoring and tuning
interface CacheStats {
hits: number
misses: number
evictions: number
size: number
maxSize: number
}
// Environment detection for storage selection
enum Environment {
BROWSER,
NODE,
WORKER
}
// Storage type for warm and cold caches
enum StorageType {
MEMORY,
OPFS,
FILESYSTEM,
S3
}
/**
* Multi-level cache manager for efficient data access
*/
export class CacheManager<T extends HNSWNode | Edge> {
// Hot cache (RAM)
private hotCache = new Map<string, CacheEntry<T>>()
// Cache statistics
private stats: CacheStats = {
hits: 0,
misses: 0,
evictions: 0,
size: 0,
maxSize: 0
}
// Environment and storage configuration
private environment: Environment
private warmStorageType: StorageType
private coldStorageType: StorageType
// Cache configuration
private hotCacheMaxSize: number
private hotCacheEvictionThreshold: number
private warmCacheTTL: number
private batchSize: number
// Auto-tuning configuration
private autoTune: boolean
private lastAutoTuneTime: number = 0
private autoTuneInterval: number = 5 * 60 * 1000 // 5 minutes
private storageStatistics: any = null
// Storage adapters for warm and cold caches
private warmStorage: any
private coldStorage: any
/**
* Initialize the cache manager
* @param options Configuration options
*/
constructor(options: {
hotCacheMaxSize?: number
hotCacheEvictionThreshold?: number
warmCacheTTL?: number
batchSize?: number
autoTune?: boolean
warmStorage?: any
coldStorage?: any
} = {}) {
// Detect environment
this.environment = this.detectEnvironment()
// Set storage types based on environment
this.warmStorageType = this.detectWarmStorageType()
this.coldStorageType = this.detectColdStorageType()
// Initialize storage adapters
this.warmStorage = options.warmStorage || this.initializeWarmStorage()
this.coldStorage = options.coldStorage || this.initializeColdStorage()
// 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
// If auto-tuning is enabled, perform initial tuning
if (this.autoTune) {
this.tuneParameters()
}
// Log configuration
if (process.env.DEBUG) {
console.log('Cache Manager initialized with configuration:', {
environment: Environment[this.environment],
hotCacheMaxSize: this.hotCacheMaxSize,
hotCacheEvictionThreshold: this.hotCacheEvictionThreshold,
warmCacheTTL: this.warmCacheTTL,
batchSize: this.batchSize,
autoTune: this.autoTune,
warmStorageType: StorageType[this.warmStorageType],
coldStorageType: StorageType[this.coldStorageType]
})
}
}
/**
* Detect the current environment
*/
private detectEnvironment(): Environment {
if (typeof window !== 'undefined' && typeof document !== 'undefined') {
return Environment.BROWSER
} else if (typeof self !== 'undefined' && typeof window === 'undefined') {
// In a worker environment, self is defined but window is not
return Environment.WORKER
} else {
return Environment.NODE
}
}
/**
* Detect the optimal cache size based on available memory
*/
private detectOptimalCacheSize(): number {
try {
// Default to a conservative value
const defaultSize = 1000
// In Node.js, use available system memory
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 freeMemory = os.freemem()
// 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
// Use 10% of free memory, with a minimum of 1000 entries
const optimalSize = Math.max(
Math.floor(freeMemory * 0.1 / ESTIMATED_BYTES_PER_ENTRY),
1000
)
return optimalSize
} catch (error) {
console.warn('Failed to detect optimal cache size:', error)
return defaultSize
}
}
// In browser, use navigator.deviceMemory if available
if (this.environment === Environment.BROWSER && navigator.deviceMemory) {
// deviceMemory is in GB, scale accordingly
return Math.max(navigator.deviceMemory * 500, 1000)
}
return defaultSize
} catch (error) {
console.warn('Error detecting optimal cache size:', error)
return 1000 // Conservative default
}
}
/**
* Tune cache parameters based on statistics and environment
* This method is called periodically if auto-tuning is enabled
*
* The auto-tuning process:
* 1. Retrieves storage statistics if available
* 2. Tunes each parameter based on statistics and environment
* 3. Logs the tuned parameters if debug is enabled
*
* Auto-tuning helps optimize cache performance by adapting to:
* - The current environment (Node.js, browser, worker)
* - Available system resources (memory, CPU)
* - Usage patterns (read-heavy vs. write-heavy workloads)
* - Cache efficiency (hit/miss ratios)
*/
private async tuneParameters(): Promise<void> {
// Skip if auto-tuning is disabled
if (!this.autoTune) return
// Check if it's time to tune parameters
const now = Date.now()
if (now - this.lastAutoTuneTime < this.autoTuneInterval) return
// Update last tune time
this.lastAutoTuneTime = now
try {
// Get storage statistics if available
if (this.coldStorage && typeof this.coldStorage.getStatistics === 'function') {
this.storageStatistics = await this.coldStorage.getStatistics()
}
// Tune hot cache size
this.tuneHotCacheSize()
// Tune eviction threshold
this.tuneEvictionThreshold()
// Tune warm cache TTL
this.tuneWarmCacheTTL()
// Tune batch size
this.tuneBatchSize()
// Log tuned parameters if debug is enabled
if (process.env.DEBUG) {
console.log('Cache parameters auto-tuned:', {
hotCacheMaxSize: this.hotCacheMaxSize,
hotCacheEvictionThreshold: this.hotCacheEvictionThreshold,
warmCacheTTL: this.warmCacheTTL,
batchSize: this.batchSize
})
}
} catch (error) {
console.warn('Error during cache parameter auto-tuning:', error)
}
}
/**
* Tune hot cache size based on statistics and environment
*
* The hot cache size is tuned based on:
* 1. Available memory in the current environment
* 2. Total number of nodes and edges in the system
* 3. Cache hit/miss ratio
*
* Algorithm:
* - Start with a size based on available memory
* - If storage statistics are available, consider caching a percentage of total items
* - If hit ratio is low, increase the cache size to improve performance
* - Ensure a reasonable minimum size to maintain basic functionality
*/
private tuneHotCacheSize(): void {
// Start with the base size from environment detection
let optimalSize = this.detectOptimalCacheSize()
// If we have storage statistics, adjust based on total nodes/edges
if (this.storageStatistics) {
const totalItems = (this.storageStatistics.totalNodes || 0) +
(this.storageStatistics.totalEdges || 0)
// If total items is significant, adjust cache size
if (totalItems > 0) {
// Use a percentage of total items, with a cap based on memory
const percentageToCache = 0.2 // Cache 20% of items by default
const statisticsBasedSize = Math.ceil(totalItems * percentageToCache)
// Use the smaller of the two to avoid memory issues
optimalSize = Math.min(optimalSize, statisticsBasedSize)
}
}
// 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
// If hit ratio is high, we might have a good cache size already
// If hit ratio is low, we might need a larger cache
if (hitRatio < 0.5) {
// Increase cache size by up to 50% if hit ratio is low
const hitRatioFactor = 1 + (0.5 - hitRatio)
optimalSize = Math.ceil(optimalSize * hitRatioFactor)
}
}
// Ensure we have a reasonable minimum size
optimalSize = Math.max(optimalSize, 1000)
// Update the hot cache max size
this.hotCacheMaxSize = optimalSize
this.stats.maxSize = optimalSize
}
/**
* Tune eviction threshold based on statistics
*
* The eviction threshold determines when items start being evicted from the hot cache.
* It is tuned based on:
* 1. Cache hit/miss ratio
* 2. Operation patterns (read-heavy vs. write-heavy workloads)
*
* Algorithm:
* - Start with a default threshold of 0.8 (80% of max size)
* - For high hit ratios, increase the threshold to keep more items in cache
* - 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
*/
private tuneEvictionThreshold(): void {
// Default threshold
let threshold = 0.8
// 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
// 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) {
// High hit ratio, increase threshold (up to 0.9)
threshold = Math.min(0.9, 0.8 + (hitRatio - 0.8))
} else if (hitRatio < 0.5) {
// Low hit ratio, decrease threshold (down to 0.6)
threshold = Math.max(0.6, 0.8 - (0.5 - hitRatio))
}
}
// If we have storage statistics with operation counts, adjust based on operation patterns
if (this.storageStatistics && this.storageStatistics.operations) {
const ops = this.storageStatistics.operations
const totalOps = ops.total || 1
// Calculate read/write ratio
const readOps = ops.search || 0
const writeOps = (ops.add || 0) + (ops.update || 0) + (ops.delete || 0)
if (totalOps > 100) {
const readRatio = readOps / totalOps
const writeRatio = writeOps / totalOps
// For read-heavy workloads, use higher threshold
// For write-heavy workloads, use lower threshold
if (readRatio > 0.8) {
// Read-heavy, increase threshold slightly
threshold = Math.min(0.9, threshold + 0.05)
} else if (writeRatio > 0.5) {
// Write-heavy, decrease threshold
threshold = Math.max(0.6, threshold - 0.1)
}
}
}
// Update the eviction threshold
this.hotCacheEvictionThreshold = threshold
}
/**
* Tune warm cache TTL based on statistics
*
* The warm cache TTL determines how long items remain in the warm cache.
* It is tuned based on:
* 1. Update frequency from operation statistics
*
* 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
*/
private tuneWarmCacheTTL(): void {
// Default TTL (24 hours)
let ttl = 24 * 60 * 60 * 1000
// If we have storage statistics with operation counts, adjust based on update frequency
if (this.storageStatistics && this.storageStatistics.operations) {
const ops = this.storageStatistics.operations
const totalOps = ops.total || 1
const updateOps = (ops.update || 0)
if (totalOps > 100) {
const updateRatio = updateOps / totalOps
// For frequently updated data, use shorter TTL
// 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))
} else if (updateRatio < 0.1) {
// Rarely updated, increase TTL (up to 48 hours)
ttl = Math.min(48 * 60 * 60 * 1000, ttl * (1.5 - updateRatio))
}
}
}
// Update the warm cache TTL
this.warmCacheTTL = ttl
}
/**
* Tune batch size based on statistics and environment
*
* The batch size determines how many items are processed in a single batch
* for operations like prefetching. It is tuned based on:
* 1. Current environment (Node.js, browser, worker)
* 2. Available memory
* 3. Operation patterns
* 4. Cache hit/miss ratio
*
* Algorithm:
* - Start with a default based on the environment
* - Adjust based on available memory in browsers
* - For bulk-heavy workloads, use a larger batch size
* - For high hit ratios, use smaller batches (items likely in cache)
* - For low hit ratios, use larger batches (need to fetch more items)
*/
private tuneBatchSize(): void {
// Default batch size
let batchSize = 10
// Adjust based on environment
if (this.environment === Environment.NODE) {
// Node.js can handle larger batches
batchSize = 20
} else if (this.environment === Environment.BROWSER) {
// Browsers might need smaller batches
batchSize = 10
// If we have memory information, adjust accordingly
if (navigator.deviceMemory) {
// Scale batch size with available memory
batchSize = Math.max(5, Math.min(20, Math.floor(navigator.deviceMemory * 2)))
}
}
// If we have storage statistics with operation counts, adjust based on operation patterns
if (this.storageStatistics && this.storageStatistics.operations) {
const ops = this.storageStatistics.operations
const totalOps = ops.total || 1
const bulkOps = (ops.search || 0)
if (totalOps > 100) {
const bulkRatio = bulkOps / totalOps
// For bulk-heavy workloads, use larger batch size
if (bulkRatio > 0.7) {
// Bulk-heavy, increase batch size (up to 2x)
batchSize = Math.min(50, Math.ceil(batchSize * 1.5))
}
}
}
// 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
// If hit ratio is high, we can use smaller batches
// If hit ratio is low, we might need larger batches
if (hitRatio > 0.8) {
// High hit ratio, decrease batch size slightly
batchSize = Math.max(5, Math.floor(batchSize * 0.8))
} else if (hitRatio < 0.5) {
// Low hit ratio, increase batch size
batchSize = Math.min(50, Math.ceil(batchSize * 1.2))
}
}
// Update the batch size
this.batchSize = batchSize
}
/**
* Detect the appropriate warm storage type based on environment
*/
private detectWarmStorageType(): StorageType {
if (this.environment === Environment.BROWSER) {
// Use OPFS if available, otherwise use memory
if ('storage' in navigator && 'getDirectory' in navigator.storage) {
return StorageType.OPFS
}
return StorageType.MEMORY
} else if (this.environment === Environment.WORKER) {
// Use OPFS if available, otherwise use memory
if ('storage' in self && 'getDirectory' in (self as WorkerGlobalScope).storage!) {
return StorageType.OPFS
}
return StorageType.MEMORY
} else {
// In Node.js, use filesystem
return StorageType.FILESYSTEM
}
}
/**
* Detect the appropriate cold storage type based on environment
*/
private detectColdStorageType(): StorageType {
if (this.environment === Environment.BROWSER) {
// Use OPFS if available, otherwise use memory
if ('storage' in navigator && 'getDirectory' in navigator.storage) {
return StorageType.OPFS
}
return StorageType.MEMORY
} else if (this.environment === Environment.WORKER) {
// Use OPFS if available, otherwise use memory
if ('storage' in self && 'getDirectory' in (self as WorkerGlobalScope).storage!) {
return StorageType.OPFS
}
return StorageType.MEMORY
} else {
// In Node.js, use S3 if configured, otherwise filesystem
return StorageType.S3
}
}
/**
* Initialize warm storage adapter
*/
private initializeWarmStorage(): any {
// Implementation depends on the detected storage type
// For now, return null as this will be provided by the storage adapter
return null
}
/**
* Initialize cold storage adapter
*/
private initializeColdStorage(): any {
// Implementation depends on the detected storage type
// For now, return null as this will be provided by the storage adapter
return null
}
/**
* Get an item from cache, trying each level in order
* @param id The item ID
* @returns The cached item or null if not found
*/
public async get(id: string): Promise<T | null> {
// Check if it's time to tune parameters
await this.checkAndTuneParameters()
// Try hot cache first (fastest)
const hotCacheEntry = this.hotCache.get(id)
if (hotCacheEntry) {
// Update access metadata
hotCacheEntry.lastAccessed = Date.now()
hotCacheEntry.accessCount++
// Update stats
this.stats.hits++
return hotCacheEntry.data
}
// Try warm cache next
try {
const warmCacheItem = await this.getFromWarmCache(id)
if (warmCacheItem) {
// Promote to hot cache
this.addToHotCache(id, warmCacheItem)
// Update stats
this.stats.hits++
return warmCacheItem
}
} catch (error) {
console.warn(`Error accessing warm cache for ${id}:`, error)
}
// Finally, try cold storage
try {
const coldStorageItem = await this.getFromColdStorage(id)
if (coldStorageItem) {
// Promote to hot and warm caches
this.addToHotCache(id, coldStorageItem)
await this.addToWarmCache(id, coldStorageItem)
// Update stats
this.stats.misses++
return coldStorageItem
}
} catch (error) {
console.warn(`Error accessing cold storage for ${id}:`, error)
}
// Item not found in any cache level
this.stats.misses++
return null
}
/**
* Get an item from warm cache
* @param id The item ID
* @returns The cached item or null if not found
*/
private async getFromWarmCache(id: string): Promise<T | null> {
if (!this.warmStorage) return null
try {
return await this.warmStorage.get(id)
} catch (error) {
console.warn(`Error getting item ${id} from warm cache:`, error)
return null
}
}
/**
* Get an item from cold storage
* @param id The item ID
* @returns The item or null if not found
*/
private async getFromColdStorage(id: string): Promise<T | null> {
if (!this.coldStorage) return null
try {
return await this.coldStorage.get(id)
} catch (error) {
console.warn(`Error getting item ${id} from cold storage:`, error)
return null
}
}
/**
* Add an item to hot cache
* @param id The item ID
* @param item The item to cache
*/
private addToHotCache(id: string, item: T): void {
// Check if we need to evict items
if (this.hotCache.size >= this.hotCacheMaxSize * this.hotCacheEvictionThreshold) {
this.evictFromHotCache()
}
// Add to hot cache
this.hotCache.set(id, {
data: item,
lastAccessed: Date.now(),
accessCount: 1,
expiresAt: null // Hot cache items don't expire
})
// Update stats
this.stats.size = this.hotCache.size
}
/**
* Add an item to warm cache
* @param id The item ID
* @param item The item to cache
*/
private async addToWarmCache(id: string, item: T): Promise<void> {
if (!this.warmStorage) return
try {
// Add to warm cache with TTL
await this.warmStorage.set(id, item, {
ttl: this.warmCacheTTL
})
} catch (error) {
console.warn(`Error adding item ${id} to warm cache:`, error)
}
}
/**
* Evict items from hot cache based on LRU policy
*/
private evictFromHotCache(): void {
// Find the least recently used items
const entries = Array.from(this.hotCache.entries())
// Sort by last accessed time (oldest first)
entries.sort((a, b) => a[1].lastAccessed - b[1].lastAccessed)
// Remove the oldest 20% of items
const itemsToRemove = Math.ceil(this.hotCache.size * 0.2)
for (let i = 0; i < itemsToRemove && i < entries.length; i++) {
this.hotCache.delete(entries[i][0])
this.stats.evictions++
}
// Update stats
this.stats.size = this.hotCache.size
if (process.env.DEBUG) {
console.log(`Evicted ${itemsToRemove} items from hot cache, new size: ${this.hotCache.size}`)
}
}
/**
* Set an item in all cache levels
* @param id The item ID
* @param item The item to cache
*/
public async set(id: string, item: T): Promise<void> {
// Add to hot cache
this.addToHotCache(id, item)
// Add to warm cache
await this.addToWarmCache(id, item)
// Add to cold storage
if (this.coldStorage) {
try {
await this.coldStorage.set(id, item)
} catch (error) {
console.warn(`Error adding item ${id} to cold storage:`, error)
}
}
}
/**
* Delete an item from all cache levels
* @param id The item ID to delete
*/
public async delete(id: string): Promise<void> {
// Remove from hot cache
this.hotCache.delete(id)
// Remove from warm cache
if (this.warmStorage) {
try {
await this.warmStorage.delete(id)
} catch (error) {
console.warn(`Error deleting item ${id} from warm cache:`, error)
}
}
// Remove from cold storage
if (this.coldStorage) {
try {
await this.coldStorage.delete(id)
} catch (error) {
console.warn(`Error deleting item ${id} from cold storage:`, error)
}
}
// Update stats
this.stats.size = this.hotCache.size
}
/**
* Clear all cache levels
*/
public async clear(): Promise<void> {
// Clear hot cache
this.hotCache.clear()
// Clear warm cache
if (this.warmStorage) {
try {
await this.warmStorage.clear()
} catch (error) {
console.warn('Error clearing warm cache:', error)
}
}
// Clear cold storage
if (this.coldStorage) {
try {
await this.coldStorage.clear()
} catch (error) {
console.warn('Error clearing cold storage:', error)
}
}
// Reset stats
this.stats = {
hits: 0,
misses: 0,
evictions: 0,
size: 0,
maxSize: this.hotCacheMaxSize
}
}
/**
* Get cache statistics
* @returns Cache statistics
*/
public getStats(): CacheStats {
return { ...this.stats }
}
/**
* Prefetch items based on ID patterns or relationships
* @param ids Array of IDs to prefetch
*/
public async prefetch(ids: string[]): Promise<void> {
// Check if it's time to tune parameters
await this.checkAndTuneParameters()
// Prefetch in batches to avoid overwhelming the system
const batches: string[][] = []
// Split into batches using the configurable batch size
for (let i = 0; i < ids.length; i += this.batchSize) {
const batch = ids.slice(i, i + this.batchSize)
batches.push(batch)
}
// Process each batch
for (const batch of batches) {
await Promise.all(
batch.map(async (id) => {
// Skip if already in hot cache
if (this.hotCache.has(id)) return
try {
// Try to get from any cache level
await this.get(id)
} catch (error) {
// Ignore errors during prefetching
if (process.env.DEBUG) {
console.warn(`Error prefetching ${id}:`, error)
}
}
})
)
}
}
/**
* Check if it's time to tune parameters and do so if needed
* This is called before operations that might benefit from tuned parameters
*
* This method serves as a checkpoint for auto-tuning, ensuring that:
* 1. Parameters are tuned periodically based on the auto-tune interval
* 2. Tuning happens before critical operations that would benefit from optimized parameters
* 3. Tuning doesn't happen too frequently, which could impact performance
*
* By calling this method before get(), getMany(), and prefetch() operations,
* we ensure that the cache parameters are optimized for the current workload
* without adding unnecessary overhead to every operation.
*/
private async checkAndTuneParameters(): Promise<void> {
// Skip if auto-tuning is disabled
if (!this.autoTune) return
// Check if it's time to tune parameters
const now = Date.now()
if (now - this.lastAutoTuneTime >= this.autoTuneInterval) {
await this.tuneParameters()
}
}
/**
* Get multiple items at once, optimizing for batch retrieval
* @param ids Array of IDs to get
* @returns Map of ID to item
*/
public async getMany(ids: string[]): Promise<Map<string, T>> {
// Check if it's time to tune parameters
await this.checkAndTuneParameters()
const result = new Map<string, T>()
// First check hot cache for all IDs
const missingIds: string[] = []
for (const id of ids) {
const hotCacheEntry = this.hotCache.get(id)
if (hotCacheEntry) {
// Update access metadata
hotCacheEntry.lastAccessed = Date.now()
hotCacheEntry.accessCount++
// Add to result
result.set(id, hotCacheEntry.data)
// Update stats
this.stats.hits++
} else {
missingIds.push(id)
}
}
if (missingIds.length === 0) {
return result
}
// Try to get missing items from warm cache
if (this.warmStorage) {
try {
const warmCacheItems = await this.warmStorage.getMany(missingIds)
for (const [id, item] of warmCacheItems.entries()) {
if (item) {
// Promote to hot cache
this.addToHotCache(id, item)
// Add to result
result.set(id, item)
// Update stats
this.stats.hits++
// Remove from missing IDs
const index = missingIds.indexOf(id)
if (index !== -1) {
missingIds.splice(index, 1)
}
}
}
} catch (error) {
console.warn('Error accessing warm cache for batch:', error)
}
}
if (missingIds.length === 0) {
return result
}
// Try to get remaining missing items from cold storage
if (this.coldStorage) {
try {
const coldStorageItems = await this.coldStorage.getMany(missingIds)
for (const [id, item] of coldStorageItems.entries()) {
if (item) {
// Promote to hot and warm caches
this.addToHotCache(id, item)
await this.addToWarmCache(id, item)
// Add to result
result.set(id, item)
// Update stats
this.stats.misses++
}
}
} catch (error) {
console.warn('Error accessing cold storage for batch:', error)
}
}
return result
}
/**
* Set the storage adapters for warm and cold caches
* @param warmStorage Warm cache storage adapter
* @param coldStorage Cold storage adapter
*/
public setStorageAdapters(warmStorage: any, coldStorage: any): void {
this.warmStorage = warmStorage
this.coldStorage = coldStorage
}
}