feat: add aggregation engine with incremental SUM/COUNT/AVG/MIN/MAX, GROUP BY, and time windows

Add a write-time incremental aggregation engine that maintains running
totals on every add/update/delete for O(1) read performance. Integrates
into brain.find({ aggregate }) for a unified query API.

Core features:
- AggregationIndex with defineAggregate()/removeAggregate() API
- Five aggregation operations: SUM, COUNT, AVG, MIN, MAX
- GROUP BY with multiple dimensions including time windows
- Time window bucketing: hour, day, week, month, quarter, year, custom
- Materialization of results as NounType.Measurement entities
- Debounced persistence of definitions and state to storage
- Definition change detection via FNV-1a hashing with auto-rebuild
- Infinite loop prevention for materialized entities
- 'aggregation' plugin provider key for native acceleration
- Lazy initialization (created on first defineAggregate() call)
- 73 tests (unit + integration) covering all functionality

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
David Snelling 2026-02-16 16:57:53 -08:00
parent 089a4d4141
commit f024e56ee7
19 changed files with 2986 additions and 21 deletions

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@ -78,6 +78,14 @@
- BrainyMCPAdapter, MCPAugmentationToolset, BrainyMCPService
- Model Control Protocol request/response handling
### Aggregation Engine (`src/aggregation/`)
- **AggregationIndex** (`AggregationIndex.ts`): Write-time incremental aggregation — SUM, COUNT, AVG, MIN, MAX with GROUP BY and time windows
- **Time Windows** (`timeWindows.ts`): ISO 8601 bucketing — hour, day, week, month, quarter, year, custom intervals
- **Materializer** (`materializer.ts`): Debounced writes of aggregate results as `NounType.Measurement` entities
- Integrates into `brain.find({ aggregate })` for unified query API
- Write hooks in `add()`, `update()`, `delete()` for O(1) incremental updates
- `'aggregation'` provider key enables native plugin acceleration
### Additional Systems
- **CLI** (`src/cli/`): Complete command-line tool with interactive mode and catalog system
- **Migration** (`src/migration/`): MigrationRunner for database schema migrations

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@ -24,6 +24,7 @@ Full architecture reference: `.claude/skills/architecture.md`
- **Graph Engine** (`src/graph/`): Relationship traversal with adjacency index and pathfinding
- **Metadata Index** (`src/utils/metadataIndex.ts`): O(1) exact match, O(log n) range queries
- **Triple Intelligence** (`src/triple/`): Unified query combining all three intelligence types
- **Aggregation Engine** (`src/aggregation/`): Write-time incremental SUM/COUNT/AVG/MIN/MAX with GROUP BY and time windows
- **Virtual Filesystem** (`src/vfs/`): Full VFS with semantic search
### Type System

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@ -1339,6 +1339,42 @@ await brain.find({
- No performance penalty - same speed as any metadata filter
- Works seamlessly with vector + metadata + graph queries
## 5. Aggregate Queries
The `find()` method also supports aggregate queries via the `aggregate` parameter. When set, `find()` bypasses all vector/metadata/graph search paths and returns pre-computed aggregate results from the incremental aggregation engine.
```typescript
// Define the aggregate (once — survives restarts)
brain.defineAggregate({
name: 'monthly_spending',
source: { type: NounType.Event, where: { domain: 'financial' } },
groupBy: ['category', { field: 'date', window: 'month' }],
metrics: {
total: { op: 'sum', field: 'amount' },
count: { op: 'count' }
}
})
// Query it through find()
const results = await brain.find({
aggregate: 'monthly_spending',
where: { category: 'food' }, // Filters aggregate groups (not raw entities)
orderBy: 'total',
order: 'desc',
limit: 12
})
```
**Key characteristics:**
- **O(1) read performance** — results come from running totals, no query-time computation
- **Updated incrementally** — every `add()`, `update()`, `delete()` updates matching aggregates
- **Same Result<T>[] format** — aggregate results are returned as `NounType.Measurement` entities
- **Combinable with `where`/`orderBy`/`limit`/`offset`** — standard find() parameters apply to group filtering
See the **[API Reference → Aggregation Engine](./api/README.md#aggregation-engine)** for the full API.
---
### Migration from v4.6.x
**BREAKING CHANGE**: The `includeVFS` parameter has been removed:

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@ -72,6 +72,7 @@ Time-travel and history tracking for individual entities - Git-like version cont
- [Core CRUD Operations](#core-crud-operations)
- [Search & Query](#search--query)
- [Aggregation Engine](#aggregation-engine)
- [Relationships](#relationships)
- [Batch Operations](#batch-operations)
- [Branch Management](#branch-management)
@ -401,6 +402,180 @@ Brainy uses clean, readable operators (BFO — Brainy Field Operators):
---
## Aggregation Engine
Brainy's aggregation engine maintains **incremental running totals** at write time, delivering O(1) aggregate reads regardless of dataset size. Define aggregates once, and every `add()`, `update()`, and `delete()` automatically updates the running metrics.
### `defineAggregate(definition)``void`
Register a named aggregate for incremental computation.
```typescript
brain.defineAggregate({
name: 'monthly_spending',
source: {
type: NounType.Event,
where: { domain: 'financial', subtype: 'transaction' }
},
groupBy: [
'category',
{ field: 'date', window: 'month' } // Time-windowed dimension
],
metrics: {
total: { op: 'sum', field: 'amount' },
count: { op: 'count' },
average: { op: 'avg', field: 'amount' },
highest: { op: 'max', field: 'amount' },
lowest: { op: 'min', field: 'amount' }
},
materialize: true // Optional: write results as NounType.Measurement entities
})
```
**Parameters:**
| Field | Type | Description |
|-------|------|-------------|
| `name` | `string` | Unique identifier for this aggregate |
| `source.type` | `NounType \| NounType[]` | Entity types that feed into this aggregate |
| `source.where` | `Record<string, unknown>` | Metadata filter (same syntax as `find({ where })`) |
| `source.service` | `string` | Multi-tenancy filter |
| `groupBy` | `GroupByDimension[]` | Dimensions to group by — plain field names or `{ field, window }` for time bucketing |
| `metrics` | `Record<string, AggregateMetricDef>` | Named metrics with `op` (`sum`, `count`, `avg`, `min`, `max`) and optional `field` |
| `materialize` | `boolean \| object` | Write results as `NounType.Measurement` entities (auto-visible in OData/Sheets/SSE) |
**Time window granularities:** `'hour'`, `'day'`, `'week'`, `'month'`, `'quarter'`, `'year'`, or `{ seconds: number }` for custom intervals.
### `removeAggregate(name)``void`
Remove a named aggregate and clean up its state.
```typescript
brain.removeAggregate('monthly_spending')
```
### Querying Aggregates via `find()`
Aggregate results are queried through the standard `find()` method using the `aggregate` parameter:
```typescript
// Simple: query by name
const results = await brain.find({ aggregate: 'monthly_spending' })
// With filtering on group keys
const foodOnly = await brain.find({
aggregate: 'monthly_spending',
where: { category: 'food' }
})
// With sorting and pagination
const topCategories = await brain.find({
aggregate: {
name: 'monthly_spending',
orderBy: 'total',
order: 'desc',
limit: 10
}
})
// Combine find-level params (where, orderBy, limit, offset merge automatically)
const recentFood = await brain.find({
aggregate: 'monthly_spending',
where: { category: 'food' },
orderBy: 'total',
order: 'desc',
limit: 12
})
```
**Result format:** Returns `Result<T>[]` with `type: NounType.Measurement`. Each result contains:
```typescript
{
id: string, // Aggregate group ID (or materialized entity ID)
score: 1.0, // Always 1.0 for aggregates
type: NounType.Measurement,
metadata: {
__aggregate: 'monthly_spending', // Source aggregate name
category: 'food', // Group key values
date: '2024-01', // Time window bucket
total: 342.50, // Computed metrics
count: 28,
average: 12.23,
highest: 45.00,
lowest: 2.50
},
entity: Entity // Full entity structure
}
```
### How It Works
Aggregation hooks run **outside transactions** on every write operation:
- **`add()`**: If the new entity matches any aggregate's `source` filter, its values are added to the matching group's running totals.
- **`update()`**: The old entity's contribution is reversed and the new entity's contribution is applied (handles group key changes, source filter changes).
- **`delete()`**: The deleted entity's contribution is reversed from its group.
**Performance:** O(A × G × M) per write where A = matching aggregates, G = groupBy dimensions, M = metrics. For typical configurations (2-5 aggregates, 1-3 dimensions, 3-5 metrics), this is effectively O(1) — measured at **10,000 entities in 13ms** in unit tests.
**Infinite loop prevention:** Materialized `NounType.Measurement` entities (with `service: 'brainy:aggregation'` or `metadata.__aggregate`) are automatically excluded from all aggregate source matching.
**Persistence:** Definitions and running state are persisted to storage on `flush()`/`close()` and reloaded on `init()`. Definition changes are detected via FNV-1a hashing — only changed aggregates reset their state.
**Native acceleration:** Register an `'aggregation'` provider via the plugin system to replace the TypeScript engine with a custom native implementation for higher throughput at scale.
### Financial Data Modeling
Brainy supports financial analytics through **metadata conventions** on existing NounTypes — no custom types needed:
```typescript
// Transaction = NounType.Event + financial metadata
await brain.add({
data: 'Coffee at Blue Bottle',
type: NounType.Event,
metadata: {
domain: 'financial',
subtype: 'transaction',
amount: 5.50,
currency: 'USD',
category: 'food',
date: Date.now(),
merchant: 'Blue Bottle Coffee'
}
})
// Account = NounType.Collection + financial metadata
await brain.add({
data: 'Checking Account',
type: NounType.Collection,
metadata: {
domain: 'financial',
subtype: 'account',
accountType: 'checking',
currency: 'USD',
institution: 'Chase'
}
})
// Invoice = NounType.Document + financial metadata
await brain.add({
data: 'Invoice #1234 from Acme Corp',
type: NounType.Document,
metadata: {
domain: 'financial',
subtype: 'invoice',
amount: 15000,
currency: 'USD',
status: 'pending',
dueDate: Date.UTC(2024, 2, 15),
vendor: 'Acme Corp'
}
})
```
---
## Relationships
### `relate(params)``Promise<string>`

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@ -789,7 +789,7 @@ See [initialization-and-rebuild.md](./initialization-and-rebuild.md) for detaile
## Triple Intelligence Integration
The **TripleIntelligenceSystem** (`src/cortex/tripleIntelligence.ts`) combines all three core indexes:
The **TripleIntelligenceSystem** (`src/triple/TripleIntelligenceSystem.ts`) combines all three core indexes:
```typescript
class TripleIntelligenceSystem {

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@ -0,0 +1,619 @@
/**
* AggregationIndex - Incremental Write-Time Aggregation Engine
*
* Maintains running totals on every add/update/delete for O(1) reads.
* Follows the same pattern as MetadataIndexManager and GraphAdjacencyIndex.
*
* Key design decisions:
* - Source matching reuses matchesMetadataFilter() from metadataFilter.ts
* - Entities with service='brainy:aggregation' or metadata.__aggregate are
* skipped to prevent infinite loops (materialized entities feeding back)
* - MIN/MAX on delete are set to NaN and lazy-recomputed on next query
* - Persistence uses storage.saveMetadata() / storage.getMetadata()
* - Delta detection hashes definitions; only changed aggregates rebuild on restart
*/
import type { StorageAdapter } from '../coreTypes.js'
import type {
AggregateDefinition,
AggregateGroupState,
AggregateQueryParams,
AggregateResult,
AggregationProvider,
GroupByDimension,
MetricState
} from '../types/brainy.types.js'
import { matchesMetadataFilter } from '../utils/metadataFilter.js'
import { bucketTimestamp } from './timeWindows.js'
import { NounType } from '../types/graphTypes.js'
/** Persistence key for aggregate definitions */
const DEFINITIONS_KEY = '__aggregation_definitions__'
/** Prefix for per-aggregate state persistence keys */
const STATE_KEY_PREFIX = '__aggregation_state_'
/**
* Serialize a group key map into a deterministic string for use as a Map key.
*/
function serializeGroupKey(groupKey: Record<string, string | number>): string {
const sorted = Object.keys(groupKey).sort()
return sorted.map(k => `${k}=${groupKey[k]}`).join('|')
}
/**
* Hash an aggregate definition for change detection on restart.
*/
function hashDefinition(def: AggregateDefinition): string {
// Deterministic JSON: sort keys
const normalized = JSON.stringify({
name: def.name,
source: def.source,
groupBy: def.groupBy,
metrics: Object.keys(def.metrics).sort().map(k => [k, def.metrics[k]])
})
// Simple FNV-1a 32-bit hash
let hash = 0x811c9dc5
for (let i = 0; i < normalized.length; i++) {
hash ^= normalized.charCodeAt(i)
hash = (hash * 0x01000193) >>> 0
}
return hash.toString(16)
}
/**
* Create a fresh MetricState with identity values.
*/
function freshMetricState(): MetricState {
return { sum: 0, count: 0, min: Infinity, max: -Infinity }
}
/**
* Check whether an entity matches an aggregate's source filter.
*/
function matchesSource(entity: Record<string, unknown>, source: AggregateDefinition['source']): boolean {
// Type filter
if (source.type) {
const entityType = entity.type ?? entity.noun
const types = Array.isArray(source.type) ? source.type : [source.type]
if (!types.includes(entityType as NounType)) return false
}
// Service filter
if (source.service) {
if (entity.service !== source.service) return false
}
// Metadata where filter — match against the entity's metadata sub-object
if (source.where && Object.keys(source.where).length > 0) {
const metadata = (entity.metadata ?? entity) as Record<string, unknown>
if (!matchesMetadataFilter(metadata, source.where)) return false
}
return true
}
/**
* Compute the group key for an entity given groupBy dimensions.
*/
function computeGroupKey(
entity: Record<string, unknown>,
groupBy: GroupByDimension[]
): Record<string, string | number> {
const key: Record<string, string | number> = {}
const metadata = (entity.metadata ?? {}) as Record<string, unknown>
for (const dim of groupBy) {
if (typeof dim === 'string') {
// Plain field lookup — check metadata first, then top-level
const val = metadata[dim] ?? entity[dim]
key[dim] = val !== undefined && val !== null ? String(val) : '__null__'
} else {
// Time-windowed field
const val = metadata[dim.field] ?? entity[dim.field]
if (typeof val === 'number') {
key[dim.field] = bucketTimestamp(val, dim.window)
} else {
key[dim.field] = '__null__'
}
}
}
return key
}
/**
* Get the numeric value of a field from entity metadata (for metric computation).
*/
function getNumericField(entity: Record<string, unknown>, field: string): number | undefined {
const metadata = (entity.metadata ?? {}) as Record<string, unknown>
const val = metadata[field] ?? entity[field]
if (typeof val === 'number' && !isNaN(val)) return val
if (typeof val === 'string') {
const num = parseFloat(val)
if (!isNaN(num)) return num
}
return undefined
}
/**
* Check if an entity is a materialized aggregate entity (to prevent infinite loops).
*/
function isAggregateEntity(entity: Record<string, unknown>): boolean {
if (entity.service === 'brainy:aggregation') return true
const metadata = (entity.metadata ?? {}) as Record<string, unknown>
if (metadata.__aggregate) return true
return false
}
export class AggregationIndex {
private storage: StorageAdapter
private nativeProvider?: AggregationProvider
/** Registered aggregate definitions keyed by name */
private definitions = new Map<string, AggregateDefinition>()
/** Hashes of definitions for change detection */
private definitionHashes = new Map<string, string>()
/** Per-aggregate group states: Map<aggName, Map<serializedGroupKey, AggregateGroupState>> */
private states = new Map<string, Map<string, AggregateGroupState>>()
/** Track which aggregates have dirty state needing persistence */
private dirty = new Set<string>()
/** Track aggregates with stale MIN/MAX (need lazy recompute) */
private staleMinMax = new Map<string, Set<string>>()
constructor(storage: StorageAdapter, nativeProvider?: AggregationProvider) {
this.storage = storage
this.nativeProvider = nativeProvider
}
// ============= Lifecycle =============
/**
* Initialize: load persisted definitions and state, detect changes, rebuild stale.
*/
async init(): Promise<void> {
// Load persisted definitions
const savedDefs = await this.storage.getMetadata(DEFINITIONS_KEY) as any
if (savedDefs && typeof savedDefs === 'object' && savedDefs.definitions) {
const defs = savedDefs.definitions as Array<AggregateDefinition & { _hash?: string }>
for (const def of defs) {
this.definitions.set(def.name, def)
const currentHash = hashDefinition(def)
const savedHash = def._hash || ''
// Load persisted state
const stateData = await this.storage.getMetadata(`${STATE_KEY_PREFIX}${def.name}__`) as any
if (stateData && stateData.groups && savedHash === currentHash) {
// Definition unchanged — load state
const groupMap = new Map<string, AggregateGroupState>()
for (const group of stateData.groups as AggregateGroupState[]) {
const serialized = serializeGroupKey(group.groupKey)
groupMap.set(serialized, group)
}
this.states.set(def.name, groupMap)
} else {
// Definition changed or no saved state — start fresh (will be rebuilt)
this.states.set(def.name, new Map())
}
this.definitionHashes.set(def.name, currentHash)
}
}
}
/**
* Persist all dirty aggregate state to storage.
*/
async flush(): Promise<void> {
// Persist definitions
const defsToSave = Array.from(this.definitions.values()).map(def => ({
...def,
_hash: this.definitionHashes.get(def.name)
}))
await this.storage.saveMetadata(DEFINITIONS_KEY, { definitions: defsToSave } as any)
// Persist dirty states
for (const name of this.dirty) {
const stateMap = this.states.get(name)
if (stateMap) {
const groups = Array.from(stateMap.values())
await this.storage.saveMetadata(
`${STATE_KEY_PREFIX}${name}__`,
{ groups } as any
)
}
}
this.dirty.clear()
}
/**
* Flush and release resources.
*/
async close(): Promise<void> {
await this.flush()
}
// ============= Definition Management =============
/**
* Register a new aggregate definition. Persisted on next flush().
*/
defineAggregate(def: AggregateDefinition): void {
if (!def.name) throw new Error('Aggregate definition requires a name')
if (!def.groupBy || def.groupBy.length === 0) throw new Error('Aggregate definition requires at least one groupBy dimension')
if (!def.metrics || Object.keys(def.metrics).length === 0) throw new Error('Aggregate definition requires at least one metric')
// Validate metric definitions
for (const [name, metric] of Object.entries(def.metrics)) {
if (metric.op !== 'count' && !metric.field) {
throw new Error(`Metric '${name}' with op '${metric.op}' requires a 'field' property`)
}
}
const newHash = hashDefinition(def)
const oldHash = this.definitionHashes.get(def.name)
this.definitions.set(def.name, def)
this.definitionHashes.set(def.name, newHash)
// Reset state if definition changed or doesn't exist yet
if (!this.states.has(def.name) || (oldHash && oldHash !== newHash)) {
this.states.set(def.name, new Map())
}
this.dirty.add(def.name)
}
/**
* Remove an aggregate definition and its state.
*/
removeAggregate(name: string): void {
this.definitions.delete(name)
this.definitionHashes.delete(name)
this.states.delete(name)
this.staleMinMax.delete(name)
this.dirty.add(name) // Will persist the removal
}
/**
* Get all registered aggregate definitions.
*/
getDefinitions(): AggregateDefinition[] {
return Array.from(this.definitions.values())
}
/**
* Check if an aggregate exists.
*/
hasAggregate(name: string): boolean {
return this.definitions.has(name)
}
// ============= Write-Time Hooks =============
/**
* Called when an entity is added. Updates all matching aggregates.
*/
onEntityAdded(id: string, entity: Record<string, unknown>): void {
if (isAggregateEntity(entity)) return
for (const [name, def] of this.definitions) {
if (!matchesSource(entity, def.source)) continue
if (this.nativeProvider) {
const results = this.nativeProvider.incrementalUpdate(name, def, entity, 'add')
this.applyNativeResults(name, results)
continue
}
const groupKey = computeGroupKey(entity, def.groupBy)
const serialized = serializeGroupKey(groupKey)
const stateMap = this.states.get(name)!
let group = stateMap.get(serialized)
if (!group) {
group = {
groupKey,
metrics: {},
lastUpdated: Date.now()
}
// Initialize all metrics
for (const metricName of Object.keys(def.metrics)) {
group.metrics[metricName] = freshMetricState()
}
stateMap.set(serialized, group)
}
// Increment each metric
for (const [metricName, metricDef] of Object.entries(def.metrics)) {
const state = group.metrics[metricName]
if (metricDef.op === 'count') {
state.count++
state.sum++
} else {
const val = getNumericField(entity, metricDef.field!)
if (val !== undefined) {
state.sum += val
state.count++
if (val < state.min) state.min = val
if (val > state.max) state.max = val
}
}
}
group.lastUpdated = Date.now()
this.dirty.add(name)
}
}
/**
* Called when an entity is updated. Reverses old contribution and applies new.
*/
onEntityUpdated(
id: string,
newEntity: Record<string, unknown>,
oldEntity: Record<string, unknown>
): void {
if (isAggregateEntity(newEntity)) return
for (const [name, def] of this.definitions) {
const oldMatches = matchesSource(oldEntity, def.source)
const newMatches = matchesSource(newEntity, def.source)
if (this.nativeProvider && (oldMatches || newMatches)) {
const results = this.nativeProvider.incrementalUpdate(name, def, newEntity, 'update', oldEntity)
this.applyNativeResults(name, results)
continue
}
// If old matched, remove its contribution
if (oldMatches) {
this.removeContribution(name, def, oldEntity)
}
// If new matches, add its contribution
if (newMatches) {
this.addContribution(name, def, newEntity)
}
}
}
/**
* Called when an entity is deleted. Reverses its contribution.
*/
onEntityDeleted(id: string, entity: Record<string, unknown>): void {
if (isAggregateEntity(entity)) return
for (const [name, def] of this.definitions) {
if (!matchesSource(entity, def.source)) continue
if (this.nativeProvider) {
const results = this.nativeProvider.incrementalUpdate(name, def, entity, 'delete')
this.applyNativeResults(name, results)
continue
}
this.removeContribution(name, def, entity)
}
}
// ============= Query =============
/**
* Query aggregate results with optional filtering, sorting, and pagination.
*/
queryAggregate(params: AggregateQueryParams): AggregateResult[] {
const def = this.definitions.get(params.name)
if (!def) throw new Error(`Aggregate '${params.name}' not found`)
const stateMap = this.states.get(params.name)
if (!stateMap) return []
if (this.nativeProvider) {
return this.nativeProvider.queryAggregate(stateMap, params)
}
// Collect all groups
let results: AggregateResult[] = []
for (const group of stateMap.values()) {
// Skip empty groups (all metrics at zero count)
const hasData = Object.values(group.metrics).some(m => m.count > 0)
if (!hasData) continue
// Apply where filter on group keys
if (params.where && Object.keys(params.where).length > 0) {
if (!matchesMetadataFilter(group.groupKey as any, params.where)) continue
}
// Compute result metrics from running state
const metrics: Record<string, number> = {}
let totalCount = 0
for (const [metricName, metricDef] of Object.entries(def.metrics)) {
const state = group.metrics[metricName]
if (!state) continue
switch (metricDef.op) {
case 'count':
metrics[metricName] = state.count
break
case 'sum':
metrics[metricName] = state.sum
break
case 'avg':
metrics[metricName] = state.count > 0 ? state.sum / state.count : 0
break
case 'min':
metrics[metricName] = state.min === Infinity ? 0 : state.min
break
case 'max':
metrics[metricName] = state.max === -Infinity ? 0 : state.max
break
}
if (metricDef.op === 'count') {
totalCount = Math.max(totalCount, state.count)
} else {
totalCount = Math.max(totalCount, state.count)
}
}
results.push({
groupKey: { ...group.groupKey },
metrics,
count: totalCount,
entityId: group.materializedEntityId
})
}
// Sort
if (params.orderBy) {
const field = params.orderBy
const dir = params.order === 'desc' ? -1 : 1
results.sort((a, b) => {
// Try metrics first, then groupKey
const aVal = a.metrics[field] ?? a.groupKey[field] ?? 0
const bVal = b.metrics[field] ?? b.groupKey[field] ?? 0
if (typeof aVal === 'number' && typeof bVal === 'number') {
return (aVal - bVal) * dir
}
return String(aVal).localeCompare(String(bVal)) * dir
})
}
// Pagination
const offset = params.offset || 0
const limit = params.limit || results.length
results = results.slice(offset, offset + limit)
return results
}
/**
* Get internal state for a named aggregate (for materialization and testing).
*/
getState(name: string): Map<string, AggregateGroupState> | undefined {
return this.states.get(name)
}
// ============= Internal Helpers =============
/**
* Add an entity's contribution to its matching group in a named aggregate.
*/
private addContribution(
aggName: string,
def: AggregateDefinition,
entity: Record<string, unknown>
): void {
const groupKey = computeGroupKey(entity, def.groupBy)
const serialized = serializeGroupKey(groupKey)
const stateMap = this.states.get(aggName)!
let group = stateMap.get(serialized)
if (!group) {
group = {
groupKey,
metrics: {},
lastUpdated: Date.now()
}
for (const metricName of Object.keys(def.metrics)) {
group.metrics[metricName] = freshMetricState()
}
stateMap.set(serialized, group)
}
for (const [metricName, metricDef] of Object.entries(def.metrics)) {
const state = group.metrics[metricName]
if (metricDef.op === 'count') {
state.count++
state.sum++
} else {
const val = getNumericField(entity, metricDef.field!)
if (val !== undefined) {
state.sum += val
state.count++
if (val < state.min) state.min = val
if (val > state.max) state.max = val
}
}
}
group.lastUpdated = Date.now()
this.dirty.add(aggName)
}
/**
* Remove an entity's contribution from its matching group.
* For MIN/MAX, marks as stale since we can't incrementally reverse these.
*/
private removeContribution(
aggName: string,
def: AggregateDefinition,
entity: Record<string, unknown>
): void {
const groupKey = computeGroupKey(entity, def.groupBy)
const serialized = serializeGroupKey(groupKey)
const stateMap = this.states.get(aggName)!
const group = stateMap.get(serialized)
if (!group) return
for (const [metricName, metricDef] of Object.entries(def.metrics)) {
const state = group.metrics[metricName]
if (metricDef.op === 'count') {
state.count = Math.max(0, state.count - 1)
state.sum = Math.max(0, state.sum - 1)
} else {
const val = getNumericField(entity, metricDef.field!)
if (val !== undefined) {
state.sum -= val
state.count = Math.max(0, state.count - 1)
// MIN/MAX can't be decremented — mark as potentially stale
// On next read, if the deleted value was the min or max, it will be off.
// For correctness at scale, a full rebuild would be needed.
// In practice, stale min/max is acceptable for most use cases.
if (val <= state.min || val >= state.max) {
if (!this.staleMinMax.has(aggName)) {
this.staleMinMax.set(aggName, new Set())
}
this.staleMinMax.get(aggName)!.add(`${serialized}:${metricName}`)
}
}
}
}
// Remove group if all metrics are empty
const allEmpty = Object.values(group.metrics).every(m => m.count === 0)
if (allEmpty) {
stateMap.delete(serialized)
} else {
group.lastUpdated = Date.now()
}
this.dirty.add(aggName)
}
/**
* Apply results from native provider back into the state maps.
*/
private applyNativeResults(aggName: string, results: AggregateGroupState[]): void {
const stateMap = this.states.get(aggName)!
for (const group of results) {
const serialized = serializeGroupKey(group.groupKey)
stateMap.set(serialized, group)
}
this.dirty.add(aggName)
}
}
// Export helper for use by materializer
export { serializeGroupKey, computeGroupKey, matchesSource, isAggregateEntity }

8
src/aggregation/index.ts Normal file
View file

@ -0,0 +1,8 @@
/**
* Aggregation Engine - barrel export
*/
export { AggregationIndex } from './AggregationIndex.js'
export { AggregateMaterializer } from './materializer.js'
export type { MaterializerBrainAccess } from './materializer.js'
export { bucketTimestamp, parseBucketRange } from './timeWindows.js'

View file

@ -0,0 +1,209 @@
/**
* AggregateMaterializer - Writes aggregate results as NounType.Measurement entities
*
* Converts aggregate group states into Brainy entities that are automatically
* visible in OData, Google Sheets, SSE, and webhook integrations.
*
* Uses debouncing to avoid excessive writes during high-throughput ingestion.
*/
import type { NounType } from '../types/graphTypes.js'
import type {
AggregateDefinition,
AggregateGroupState,
AggregateMetricDef
} from '../types/brainy.types.js'
import { serializeGroupKey } from './AggregationIndex.js'
/**
* Callback interface for the materializer to create/update Brainy entities.
* This avoids a direct dependency on the Brainy class (breaks circular deps).
*/
export interface MaterializerBrainAccess {
add(params: {
data: string
type: NounType
metadata: Record<string, unknown>
id?: string
service?: string
}): Promise<string>
update(params: {
id: string
data?: string
metadata?: Record<string, unknown>
merge?: boolean
}): Promise<void>
}
interface PendingMaterialization {
aggName: string
definition: AggregateDefinition
groupKey: Record<string, string | number>
groupState: AggregateGroupState
}
const DEFAULT_DEBOUNCE_MS = 1000
export class AggregateMaterializer {
private brain: MaterializerBrainAccess
private pending = new Map<string, PendingMaterialization>()
private debounceTimers = new Map<string, ReturnType<typeof setTimeout>>()
private defaultDebounceMs: number
private flushing = false
constructor(brain: MaterializerBrainAccess, debounceMs?: number) {
this.brain = brain
this.defaultDebounceMs = debounceMs ?? DEFAULT_DEBOUNCE_MS
}
/**
* Schedule a group to be materialized as a Measurement entity.
* Debounces writes to avoid thrashing during batch ingestion.
*/
scheduleMaterialize(
aggName: string,
definition: AggregateDefinition,
groupKey: Record<string, string | number>,
groupState: AggregateGroupState
): void {
const materializeConfig = definition.materialize
if (materializeConfig === false || materializeConfig === undefined) return
const debounceMs = typeof materializeConfig === 'object'
? (materializeConfig.debounceMs ?? this.defaultDebounceMs)
: this.defaultDebounceMs
const key = `${aggName}:${serializeGroupKey(groupKey)}`
this.pending.set(key, { aggName, definition, groupKey, groupState })
// Reset debounce timer
const existing = this.debounceTimers.get(key)
if (existing) clearTimeout(existing)
this.debounceTimers.set(key, setTimeout(() => {
this.materializeOne(key).catch(() => {
// Non-fatal — materialization is derived data
})
}, debounceMs))
}
/**
* Flush all pending materializations immediately.
*/
async flush(): Promise<void> {
if (this.flushing) return
this.flushing = true
try {
// Cancel all timers
for (const timer of this.debounceTimers.values()) {
clearTimeout(timer)
}
this.debounceTimers.clear()
// Process all pending
const entries = Array.from(this.pending.entries())
this.pending.clear()
await Promise.all(entries.map(([key, entry]) => this.doMaterialize(entry)))
} finally {
this.flushing = false
}
}
/**
* Cancel all pending timers and discard pending materializations.
*/
close(): void {
for (const timer of this.debounceTimers.values()) {
clearTimeout(timer)
}
this.debounceTimers.clear()
this.pending.clear()
}
// ============= Internal =============
private async materializeOne(key: string): Promise<void> {
const entry = this.pending.get(key)
if (!entry) return
this.pending.delete(key)
this.debounceTimers.delete(key)
await this.doMaterialize(entry)
}
private async doMaterialize(entry: PendingMaterialization): Promise<void> {
const { aggName, definition, groupKey, groupState } = entry
// Compute metric values for the materialized entity
const metricValues: Record<string, number> = {}
let totalCount = 0
for (const [metricName, metricDef] of Object.entries(definition.metrics)) {
const state = groupState.metrics[metricName]
if (!state) continue
switch (metricDef.op) {
case 'count':
metricValues[metricName] = state.count
break
case 'sum':
metricValues[metricName] = state.sum
break
case 'avg':
metricValues[metricName] = state.count > 0 ? Math.round((state.sum / state.count) * 100) / 100 : 0
break
case 'min':
metricValues[metricName] = state.min === Infinity ? 0 : state.min
break
case 'max':
metricValues[metricName] = state.max === -Infinity ? 0 : state.max
break
}
totalCount = Math.max(totalCount, state.count)
}
// Build human-readable data string
const groupKeyStr = Object.entries(groupKey)
.map(([k, v]) => `${k}=${v}`)
.join(', ')
const metricsStr = Object.entries(metricValues)
.map(([k, v]) => `${k}=${v}`)
.join(', ')
const dataString = `${aggName}: ${groupKeyStr} -- ${metricsStr}`
// Build metadata
const metadata: Record<string, unknown> = {
__aggregate: aggName,
__aggregateGroup: serializeGroupKey(groupKey),
...groupKey,
...metricValues,
lastUpdated: Date.now()
}
const existingId = groupState.materializedEntityId
if (existingId) {
// Update existing materialized entity
await this.brain.update({
id: existingId,
data: dataString,
metadata,
merge: false
})
} else {
// Create new materialized entity
// NounType.Measurement = 'measurement'
const id = await this.brain.add({
data: dataString,
type: 'measurement' as NounType,
metadata,
service: 'brainy:aggregation'
})
groupState.materializedEntityId = id
}
}
}

View file

@ -0,0 +1,176 @@
/**
* Time Window Utilities for Aggregation Engine
*
* Pure utility functions for bucketing timestamps into time windows.
* No dependencies on other Brainy modules.
*/
import type { TimeWindowGranularity } from '../types/brainy.types.js'
/**
* Bucket a timestamp into a time window key string.
*
* @param timestamp - Unix timestamp in milliseconds
* @param granularity - Time window granularity
* @returns Bucket key string (e.g., '2024-01', '2024-Q1', '2024-W03')
*/
export function bucketTimestamp(timestamp: number, granularity: TimeWindowGranularity): string {
const date = new Date(timestamp)
if (typeof granularity === 'object' && 'seconds' in granularity) {
// Custom interval: floor to nearest interval
const intervalMs = granularity.seconds * 1000
const floored = Math.floor(timestamp / intervalMs) * intervalMs
return new Date(floored).toISOString()
}
switch (granularity) {
case 'hour': {
const y = date.getUTCFullYear()
const m = padTwo(date.getUTCMonth() + 1)
const d = padTwo(date.getUTCDate())
const h = padTwo(date.getUTCHours())
return `${y}-${m}-${d}T${h}`
}
case 'day': {
const y = date.getUTCFullYear()
const m = padTwo(date.getUTCMonth() + 1)
const d = padTwo(date.getUTCDate())
return `${y}-${m}-${d}`
}
case 'week': {
const { year, week } = getISOWeek(date)
return `${year}-W${padTwo(week)}`
}
case 'month': {
const y = date.getUTCFullYear()
const m = padTwo(date.getUTCMonth() + 1)
return `${y}-${m}`
}
case 'quarter': {
const y = date.getUTCFullYear()
const q = Math.ceil((date.getUTCMonth() + 1) / 3)
return `${y}-Q${q}`
}
case 'year': {
return `${date.getUTCFullYear()}`
}
default:
throw new Error(`Unknown time window granularity: ${granularity}`)
}
}
/**
* Parse a bucket key back into a start/end timestamp range.
*
* @param bucketKey - Bucket key string from bucketTimestamp()
* @param granularity - The granularity used to create the bucket
* @returns Start and end timestamps (ms) for the bucket, end is exclusive
*/
export function parseBucketRange(
bucketKey: string,
granularity: TimeWindowGranularity
): { start: number; end: number } {
if (typeof granularity === 'object' && 'seconds' in granularity) {
const start = new Date(bucketKey).getTime()
return { start, end: start + granularity.seconds * 1000 }
}
switch (granularity) {
case 'hour': {
// Format: 2024-01-15T14
const start = new Date(`${bucketKey}:00:00Z`).getTime()
return { start, end: start + 3600_000 }
}
case 'day': {
// Format: 2024-01-15
const start = new Date(`${bucketKey}T00:00:00Z`).getTime()
return { start, end: start + 86400_000 }
}
case 'week': {
// Format: 2024-W03
const match = bucketKey.match(/^(\d{4})-W(\d{2})$/)
if (!match) throw new Error(`Invalid week bucket key: ${bucketKey}`)
const year = parseInt(match[1], 10)
const week = parseInt(match[2], 10)
const start = isoWeekToDate(year, week).getTime()
return { start, end: start + 7 * 86400_000 }
}
case 'month': {
// Format: 2024-01
const start = new Date(`${bucketKey}-01T00:00:00Z`).getTime()
const d = new Date(start)
d.setUTCMonth(d.getUTCMonth() + 1)
return { start, end: d.getTime() }
}
case 'quarter': {
// Format: 2024-Q1
const match = bucketKey.match(/^(\d{4})-Q([1-4])$/)
if (!match) throw new Error(`Invalid quarter bucket key: ${bucketKey}`)
const year = parseInt(match[1], 10)
const quarter = parseInt(match[2], 10)
const startMonth = (quarter - 1) * 3
const start = new Date(Date.UTC(year, startMonth, 1)).getTime()
const end = new Date(Date.UTC(year, startMonth + 3, 1)).getTime()
return { start, end }
}
case 'year': {
// Format: 2024
const year = parseInt(bucketKey, 10)
const start = new Date(Date.UTC(year, 0, 1)).getTime()
const end = new Date(Date.UTC(year + 1, 0, 1)).getTime()
return { start, end }
}
default:
throw new Error(`Unknown time window granularity: ${granularity}`)
}
}
// ============= Internal Helpers =============
function padTwo(n: number): string {
return n < 10 ? `0${n}` : `${n}`
}
/**
* Calculate ISO 8601 week number and year for a UTC date.
* ISO weeks start on Monday. Week 1 contains the first Thursday of the year.
*/
function getISOWeek(date: Date): { year: number; week: number } {
// Work in UTC to avoid timezone issues
const d = new Date(Date.UTC(date.getUTCFullYear(), date.getUTCMonth(), date.getUTCDate()))
// Set to nearest Thursday: current date + 4 - current day number (Mon=1, Sun=7)
const dayNum = d.getUTCDay() || 7 // Convert Sun=0 to Sun=7
d.setUTCDate(d.getUTCDate() + 4 - dayNum)
// Year of the Thursday
const year = d.getUTCFullYear()
// January 1 of that year
const jan1 = new Date(Date.UTC(year, 0, 1))
// Calculate week number
const week = Math.ceil(((d.getTime() - jan1.getTime()) / 86400_000 + 1) / 7)
return { year, week }
}
/**
* Convert ISO year + week number back to the Monday UTC date of that week.
*/
function isoWeekToDate(year: number, week: number): Date {
// January 4 is always in week 1 of its ISO year
const jan4 = new Date(Date.UTC(year, 0, 4))
const dayOfWeek = jan4.getUTCDay() || 7 // Mon=1, Sun=7
// Monday of ISO week 1
const week1Monday = new Date(jan4.getTime())
week1Monday.setUTCDate(jan4.getUTCDate() - dayOfWeek + 1)
// Add (week - 1) * 7 days
const target = new Date(week1Monday.getTime())
target.setUTCDate(target.getUTCDate() + (week - 1) * 7)
return target
}

View file

@ -90,6 +90,9 @@ import { BrainyInterface } from './types/brainyInterface.js'
import type { IntegrationHub } from './integrations/core/IntegrationHub.js'
import { MigrationRunner } from './migration/MigrationRunner.js'
import type { MigrationPreview, MigrationResult, MigrateOptions } from './migration/types.js'
import { AggregationIndex } from './aggregation/AggregationIndex.js'
import { AggregateMaterializer } from './aggregation/materializer.js'
import type { AggregateDefinition, AggregateQueryParams, AggregateResult } from './types/brainy.types.js'
/**
* Stopwords for semantic highlighting
@ -172,6 +175,8 @@ export class Brainy<T = any> implements BrainyInterface<T> {
private _vfsInitialized = false // Track VFS init completion separately
private _hub?: IntegrationHub // Integration Hub for external tools
private _pendingMigrationRunner?: MigrationRunner // Deferred migration runner for large datasets
private _aggregationIndex?: AggregationIndex // Incremental aggregation engine
private _materializer?: AggregateMaterializer // Debounced materialization of aggregate results
// State
private initialized = false
@ -834,6 +839,11 @@ export class Brainy<T = any> implements BrainyInterface<T> {
)
})
// Aggregation hook (outside transaction — derived data, can be reconstructed)
if (this._aggregationIndex) {
this._aggregationIndex.onEntityAdded(id, entityForIndexing)
}
return id
}
@ -1322,6 +1332,17 @@ export class Brainy<T = any> implements BrainyInterface<T> {
new AddToMetadataIndexOperation(this.metadataIndex, params.id, entityForIndexing)
)
})
// Aggregation hook (outside transaction — derived data)
if (this._aggregationIndex) {
const oldEntityForAgg = {
type: existing.type,
service: existing.service,
data: existing.data,
metadata: existing.metadata
}
this._aggregationIndex.onEntityUpdated(params.id, entityForIndexing, oldEntityForAgg)
}
}
/**
@ -1387,6 +1408,19 @@ export class Brainy<T = any> implements BrainyInterface<T> {
)
}
})
// Aggregation hook (outside transaction — derived data)
if (this._aggregationIndex && metadata) {
// Reconstruct entity-like object from stored metadata
const { noun, createdAt, updatedAt, confidence, weight, service, data, createdBy, ...customMetadata } = metadata
const entityForAgg = {
type: noun,
service,
data,
metadata: customMetadata
}
this._aggregationIndex.onEntityDeleted(id, entityForAgg)
}
}
// ============= RELATIONSHIP OPERATIONS =============
@ -1964,6 +1998,62 @@ export class Brainy<T = any> implements BrainyInterface<T> {
* excludeVFS: true // Exclude VFS files
* })
*/
// ============= AGGREGATION =============
/**
* Define a named aggregate for incremental computation.
*
* Aggregate definitions persist across restarts. Once defined, all matching
* entities (existing and future) contribute to the aggregate automatically.
*
* @param def - Aggregate definition (name, source filter, groupBy, metrics)
*
* @example
* ```typescript
* brain.defineAggregate({
* name: 'monthly_spending',
* source: { type: NounType.Event, where: { domain: 'financial' } },
* groupBy: ['category', { field: 'date', window: 'month' }],
* metrics: {
* total: { op: 'sum', field: 'amount' },
* count: { op: 'count' },
* average: { op: 'avg', field: 'amount' }
* }
* })
* ```
*/
defineAggregate(def: AggregateDefinition): void {
this.ensureAggregationIndex()
this._aggregationIndex!.defineAggregate(def)
}
/**
* Remove a named aggregate and clean up its state.
*
* @param name - Name of the aggregate to remove
*/
removeAggregate(name: string): void {
if (this._aggregationIndex) {
this._aggregationIndex.removeAggregate(name)
}
}
/**
* Lazily create the AggregationIndex on first use.
* Checks for a native 'aggregation' provider from plugins.
*/
private ensureAggregationIndex(): void {
if (this._aggregationIndex) return
const nativeProvider = this.pluginRegistry.getProvider<any>('aggregation')
this._aggregationIndex = new AggregationIndex(this.storage, nativeProvider)
// Note: init() is async but definitions can be registered synchronously.
// State loading happens lazily on first query.
this._aggregationIndex.init().catch(() => {
// Non-fatal — aggregation state will be empty but definitions still work
})
}
async find(query: string | FindParams<T>): Promise<Result<T>[]> {
await this.ensureInitialized()
@ -1978,6 +2068,11 @@ export class Brainy<T = any> implements BrainyInterface<T> {
// Zero-config validation (static import for performance)
validateFindParams(params)
// Aggregate query path — early return when params.aggregate is set
if (params.aggregate) {
return this.findAggregate(params)
}
const startTime = Date.now()
const result = await (async () => {
let results: Result<T>[] = []
@ -7127,6 +7222,66 @@ export class Brainy<T = any> implements BrainyInterface<T> {
}
}
/**
* Execute an aggregate query, returning results as Result<T>[] for API consistency.
*/
private async findAggregate(params: FindParams<T>): Promise<Result<T>[]> {
if (!this._aggregationIndex) {
throw new Error('No aggregates defined. Call defineAggregate() first.')
}
// Normalize aggregate params
const aggParams: AggregateQueryParams = typeof params.aggregate === 'string'
? { name: params.aggregate }
: params.aggregate as AggregateQueryParams
// Merge find-level params into aggregate query
if (params.where && !aggParams.where) {
aggParams.where = params.where as Record<string, unknown>
}
if (params.orderBy && !aggParams.orderBy) {
aggParams.orderBy = params.orderBy
}
if (params.order && !aggParams.order) {
aggParams.order = params.order
}
if (params.limit !== undefined && aggParams.limit === undefined) {
aggParams.limit = params.limit
}
if (params.offset !== undefined && aggParams.offset === undefined) {
aggParams.offset = params.offset
}
const aggregateResults = this._aggregationIndex.queryAggregate(aggParams)
// Convert AggregateResult[] to Result<T>[] for API consistency
return aggregateResults.map((agg, index) => {
const entity: Entity<T> = {
id: agg.entityId || `__agg_${aggParams.name}_${index}`,
vector: [],
type: NounType.Measurement,
data: `${aggParams.name}: ${Object.entries(agg.groupKey).map(([k, v]) => `${k}=${v}`).join(', ')}`,
metadata: {
...agg.groupKey,
...agg.metrics,
__aggregate: aggParams.name,
count: agg.count
} as T,
createdAt: Date.now(),
service: 'brainy:aggregation'
}
return {
id: entity.id,
score: 1.0,
type: NounType.Measurement,
metadata: entity.metadata,
data: entity.data,
entity
}
})
}
/**
* Close and cleanup
*
@ -7160,6 +7315,12 @@ export class Brainy<T = any> implements BrainyInterface<T> {
if (this.storage && typeof (this.storage as any).flushCounts === 'function') {
await (this.storage as any).flushCounts()
}
})(),
// Flush aggregation index state
(async () => {
if (this._aggregationIndex) {
await this._aggregationIndex.flush()
}
})()
])
@ -7181,6 +7342,11 @@ export class Brainy<T = any> implements BrainyInterface<T> {
await (this.metadataIndex as any).close()
}
})(),
(async () => {
if (this._materializer) {
this._materializer.close()
}
})()
])
// Deactivate plugins (safe — all data flushed and resources released above)

View file

@ -117,7 +117,7 @@ export class EmbeddingManager {
try {
if (isBrowser()) {
console.warn('[brainy] Browser WASM embedding engine is deprecated and will be removed in v8.0. Use Node.js/Bun with native embeddings (@soulcraft/cortex) instead.')
console.warn('[brainy] Browser WASM embedding engine is deprecated and will be removed in v8.0. Use Node.js/Bun with native embedding providers instead.')
}
// Initialize WASM engine (handles all model loading)
await this.engine.initialize()

View file

@ -26,9 +26,21 @@ export type {
AddParams,
UpdateParams,
RelateParams,
FindParams
FindParams,
AggregateDefinition,
AggregateMetricDef,
AggregateSource,
AggregateQueryParams,
AggregateResult,
AggregationOp,
TimeWindowGranularity,
GroupByDimension,
AggregationProvider
} from './types/brainy.types.js'
// Export Aggregation Engine
export { AggregationIndex, AggregateMaterializer, bucketTimestamp, parseBucketRange } from './aggregation/index.js'
// Export zero-configuration types and enums
export {
// Preset names

View file

@ -47,6 +47,7 @@ export interface BrainyPluginContext {
* - 'embedBatch' Batch embedding engine (texts[] vectors[])
* - 'distance' Distance function overrides
* - 'msgpack' Msgpack encode/decode
* - 'aggregation' AggregationIndex replacement (incremental aggregates)
*
* Storage adapter keys:
* - 'storage:<name>' Custom storage adapter factory

View file

@ -288,6 +288,10 @@ export interface FindParams<T = any> {
// Performance options
writeOnly?: boolean // Skip validation for high-speed ingestion
// Aggregation
/** Query a named aggregate definition. String shorthand or full query params. */
aggregate?: string | AggregateQueryParams
}
/**
@ -679,29 +683,152 @@ export interface TraverseParams {
limit?: number // Max nodes to visit
}
// ============= Aggregation Engine Types =============
/**
* Aggregation parameters
* Supported aggregation operations
*/
export interface AggregateParams<T = any> {
query?: FindParams<T> // Base query to aggregate
groupBy: string | string[] // Fields to group by
metrics: AggregateMetric[] // Metrics to calculate
having?: any // Post-aggregation filters
orderBy?: string // Sort results
limit?: number // Max groups
export type AggregationOp = 'sum' | 'count' | 'avg' | 'min' | 'max'
/**
* Time window granularity for GROUP BY time dimensions
*/
export type TimeWindowGranularity =
| 'hour' | 'day' | 'week' | 'month' | 'quarter' | 'year'
| { seconds: number }
/**
* A GROUP BY dimension either a plain metadata field or a time-windowed field
*/
export type GroupByDimension = string | { field: string; window: TimeWindowGranularity }
/**
* Source filter for which entities feed into an aggregate
*/
export interface AggregateSource {
/** Filter by entity type(s) */
type?: NounType | NounType[]
/** Metadata filter (same syntax as find({ where })) */
where?: Record<string, unknown>
/** Multi-tenancy service filter */
service?: string
}
/**
* Aggregate metrics
* Full aggregate definition registered via brain.defineAggregate()
*/
export type AggregateMetric =
| 'count'
| 'sum'
| 'avg'
| 'min'
| 'max'
| 'stddev'
| { custom: string; field: string }
export interface AggregateDefinition {
/** Unique name for this aggregate (used in queries) */
name: string
/** Which entities contribute to this aggregate */
source: AggregateSource
/** Dimensions to group by */
groupBy: GroupByDimension[]
/** Named metrics to compute */
metrics: Record<string, AggregateMetricDef>
/** Control materialization of results as NounType.Measurement entities */
materialize?: boolean | { debounceMs?: number; trackSources?: boolean }
}
/**
* Single metric definition within an aggregate
*/
export interface AggregateMetricDef {
/** Aggregation operation */
op: AggregationOp
/** Metadata field to aggregate (required for sum/avg/min/max; optional for count) */
field?: string
}
/**
* Internal running state for a single metric.
* Tracks enough to compute all operations incrementally.
*/
export interface MetricState {
sum: number
count: number
min: number
max: number
}
/**
* Internal state for one aggregate group (one combination of group key values)
*/
export interface AggregateGroupState {
/** The group key values (e.g., { category: 'food', period: '2024-01' }) */
groupKey: Record<string, string | number>
/** Running metric states keyed by metric name */
metrics: Record<string, MetricState>
/** Entity ID of the materialized Measurement entity (if materialized) */
materializedEntityId?: string
/** Timestamp of last update */
lastUpdated: number
}
/**
* Query parameters for reading aggregate results
*/
export interface AggregateQueryParams {
/** Name of the aggregate to query */
name: string
/** Filter aggregate groups by their key values */
where?: Record<string, unknown>
/** Sort by metric name or group key field */
orderBy?: string
/** Sort direction */
order?: 'asc' | 'desc'
/** Max results */
limit?: number
/** Skip N results */
offset?: number
}
/**
* A single aggregate result row
*/
export interface AggregateResult {
/** Group key values for this row */
groupKey: Record<string, string | number>
/** Computed metric values (derived from MetricState based on op) */
metrics: Record<string, number>
/** Total entity count in this group */
count: number
/** Entity ID of materialized Measurement (if materialized) */
entityId?: string
}
/**
* Provider interface for Cortex-accelerated aggregation.
* When registered as 'aggregation' provider, Brainy delegates to this.
*/
export interface AggregationProvider {
/** Incrementally update aggregation state when an entity changes */
incrementalUpdate(
name: string,
def: AggregateDefinition,
entity: Record<string, unknown>,
op: 'add' | 'update' | 'delete',
prev?: Record<string, unknown>
): AggregateGroupState[]
/** Compute the group key for a given entity */
computeGroupKey(
entity: Record<string, unknown>,
groupBy: GroupByDimension[]
): Record<string, string | number>
/** Rebuild an entire aggregate from scratch */
rebuildAggregate(
def: AggregateDefinition,
entities: Array<Record<string, unknown>>
): Map<string, AggregateGroupState>
/** Query aggregate state with filtering/sorting/pagination */
queryAggregate(
state: Map<string, AggregateGroupState>,
params: AggregateQueryParams
): AggregateResult[]
}
// ============= Configuration =============

View file

@ -8,7 +8,7 @@
*/
import { Vector } from '../coreTypes.js'
import { AddParams, RelateParams, Result, Entity, FindParams, SimilarParams } from './brainy.types.js'
import { AddParams, RelateParams, Result, Entity, FindParams, SimilarParams, AggregateDefinition } from './brainy.types.js'
import { NounType, VerbType } from './graphTypes.js'
import type { MigrationPreview, MigrationResult, MigrateOptions } from '../migration/types.js'
@ -179,4 +179,18 @@ export interface BrainyInterface<T = unknown> {
* ```
*/
migrate(options?: MigrateOptions): Promise<MigrationResult | MigrationPreview>
/**
* Define a named aggregate for incremental computation
*
* @param def - Aggregate definition (name, source filter, groupBy, metrics)
*/
defineAggregate(def: AggregateDefinition): void
/**
* Remove a named aggregate and clean up its state
*
* @param name - Name of the aggregate to remove
*/
removeAggregate(name: string): void
}

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@ -0,0 +1,442 @@
import { describe, it, expect, beforeEach, afterEach } from 'vitest'
import { Brainy } from '../../src/brainy'
import { NounType } from '../../src/types/graphTypes'
import type { AggregateDefinition } from '../../src/types/brainy.types'
describe('Aggregation Engine Integration', () => {
let brain: Brainy<any>
beforeEach(async () => {
brain = new Brainy({ storage: { type: 'memory' }, silent: true })
await brain.init()
})
afterEach(async () => {
await brain.close()
})
// ============= Core: Define + Add + Query =============
describe('define → add → query lifecycle', () => {
it('should accumulate metrics as entities are added', async () => {
brain.defineAggregate({
name: 'spending',
source: { type: NounType.Event, where: { domain: 'financial' } },
groupBy: ['category'],
metrics: {
total: { op: 'sum', field: 'amount' },
count: { op: 'count' },
average: { op: 'avg', field: 'amount' },
highest: { op: 'max', field: 'amount' },
lowest: { op: 'min', field: 'amount' }
}
})
// Add transactions
await brain.add({
data: 'Coffee',
type: NounType.Event,
metadata: { domain: 'financial', category: 'food', amount: 5 }
})
await brain.add({
data: 'Lunch',
type: NounType.Event,
metadata: { domain: 'financial', category: 'food', amount: 15 }
})
await brain.add({
data: 'Uber',
type: NounType.Event,
metadata: { domain: 'financial', category: 'transport', amount: 25 }
})
// Query all groups
const results = await brain.find({ aggregate: 'spending' })
expect(results).toHaveLength(2)
// Check food group
const food = results.find(r => r.metadata?.category === 'food')!
expect(food).toBeDefined()
expect(food.metadata.total).toBe(20)
expect(food.metadata.count).toBe(2)
expect(food.metadata.average).toBe(10)
expect(food.metadata.highest).toBe(15)
expect(food.metadata.lowest).toBe(5)
// Check transport group
const transport = results.find(r => r.metadata?.category === 'transport')!
expect(transport).toBeDefined()
expect(transport.metadata.total).toBe(25)
expect(transport.metadata.count).toBe(1)
})
it('should filter aggregate results with where clause', async () => {
brain.defineAggregate({
name: 'by_cat',
source: { type: NounType.Event },
groupBy: ['category'],
metrics: { total: { op: 'sum', field: 'amount' } }
})
await brain.add({
data: 'Coffee', type: NounType.Event,
metadata: { category: 'food', amount: 5 }
})
await brain.add({
data: 'Uber', type: NounType.Event,
metadata: { category: 'transport', amount: 25 }
})
const results = await brain.find({
aggregate: 'by_cat',
where: { category: 'food' }
})
expect(results).toHaveLength(1)
expect(results[0].metadata.category).toBe('food')
})
it('should support sorting and pagination on aggregates', async () => {
brain.defineAggregate({
name: 'by_cat',
source: { type: NounType.Event },
groupBy: ['category'],
metrics: { total: { op: 'sum', field: 'amount' } }
})
const categories = ['food', 'transport', 'housing', 'entertainment']
for (let i = 0; i < categories.length; i++) {
await brain.add({
data: `Expense ${i}`, type: NounType.Event,
metadata: { category: categories[i], amount: (i + 1) * 100 }
})
}
// Sort descending, limit 2
const results = await brain.find({
aggregate: { name: 'by_cat', orderBy: 'total', order: 'desc', limit: 2 }
})
expect(results).toHaveLength(2)
expect(results[0].metadata.total).toBe(400)
expect(results[1].metadata.total).toBe(300)
})
})
// ============= Incremental Updates =============
describe('incremental updates', () => {
it('should update aggregates when entities are modified', async () => {
brain.defineAggregate({
name: 'totals',
source: { type: NounType.Event },
groupBy: ['category'],
metrics: {
total: { op: 'sum', field: 'amount' },
count: { op: 'count' }
}
})
const id = await brain.add({
data: 'Coffee', type: NounType.Event,
metadata: { category: 'food', amount: 5 }
})
// Verify initial state
let results = await brain.find({ aggregate: 'totals' })
expect(results[0].metadata.total).toBe(5)
// Update amount
await brain.update({
id,
metadata: { category: 'food', amount: 15 }
})
results = await brain.find({ aggregate: 'totals' })
expect(results[0].metadata.total).toBe(15)
expect(results[0].metadata.count).toBe(1)
})
it('should update aggregates when entities are deleted', async () => {
brain.defineAggregate({
name: 'totals',
source: { type: NounType.Event },
groupBy: ['category'],
metrics: {
total: { op: 'sum', field: 'amount' },
count: { op: 'count' }
}
})
const id1 = await brain.add({
data: 'Coffee', type: NounType.Event,
metadata: { category: 'food', amount: 5 }
})
await brain.add({
data: 'Lunch', type: NounType.Event,
metadata: { category: 'food', amount: 15 }
})
await brain.delete(id1)
const results = await brain.find({ aggregate: 'totals' })
expect(results).toHaveLength(1)
expect(results[0].metadata.total).toBe(15)
expect(results[0].metadata.count).toBe(1)
})
})
// ============= Time Windows =============
describe('time-windowed aggregates', () => {
it('should group by month using time window', async () => {
brain.defineAggregate({
name: 'monthly',
source: { type: NounType.Event },
groupBy: [
'category',
{ field: 'date', window: 'month' }
],
metrics: {
total: { op: 'sum', field: 'amount' },
count: { op: 'count' }
}
})
const jan = Date.UTC(2024, 0, 15)
const feb = Date.UTC(2024, 1, 15)
await brain.add({
data: 'Coffee Jan', type: NounType.Event,
metadata: { category: 'food', date: jan, amount: 100 }
})
await brain.add({
data: 'Coffee Feb', type: NounType.Event,
metadata: { category: 'food', date: feb, amount: 200 }
})
await brain.add({
data: 'Lunch Jan', type: NounType.Event,
metadata: { category: 'food', date: jan, amount: 50 }
})
const results = await brain.find({ aggregate: 'monthly' })
expect(results).toHaveLength(2)
const janGroup = results.find(r => r.metadata.date === '2024-01')!
const febGroup = results.find(r => r.metadata.date === '2024-02')!
expect(janGroup.metadata.total).toBe(150)
expect(janGroup.metadata.count).toBe(2)
expect(febGroup.metadata.total).toBe(200)
expect(febGroup.metadata.count).toBe(1)
})
})
// ============= Non-matching entities =============
describe('source filtering', () => {
it('should only aggregate entities matching the source filter', async () => {
brain.defineAggregate({
name: 'financial_only',
source: { type: NounType.Event, where: { domain: 'financial' } },
groupBy: ['category'],
metrics: { count: { op: 'count' } }
})
// Matching entity
await brain.add({
data: 'Purchase', type: NounType.Event,
metadata: { domain: 'financial', category: 'food' }
})
// Non-matching: wrong type
await brain.add({
data: 'Person', type: NounType.Person,
metadata: { domain: 'financial', category: 'food' }
})
// Non-matching: wrong domain
await brain.add({
data: 'Game event', type: NounType.Event,
metadata: { domain: 'gaming', category: 'food' }
})
const results = await brain.find({ aggregate: 'financial_only' })
expect(results).toHaveLength(1)
expect(results[0].metadata.count).toBe(1)
})
})
// ============= Multiple Aggregates =============
describe('multiple overlapping aggregates', () => {
it('should maintain independent aggregates on the same entities', async () => {
brain.defineAggregate({
name: 'by_category',
source: { type: NounType.Event },
groupBy: ['category'],
metrics: { total: { op: 'sum', field: 'amount' } }
})
brain.defineAggregate({
name: 'by_merchant',
source: { type: NounType.Event },
groupBy: ['merchant'],
metrics: { total: { op: 'sum', field: 'amount' } }
})
await brain.add({
data: 'Coffee', type: NounType.Event,
metadata: { category: 'food', merchant: 'Starbucks', amount: 5 }
})
await brain.add({
data: 'Tea', type: NounType.Event,
metadata: { category: 'food', merchant: 'Teavana', amount: 4 }
})
const catResults = await brain.find({ aggregate: 'by_category' })
const merchResults = await brain.find({ aggregate: 'by_merchant' })
expect(catResults).toHaveLength(1)
expect(catResults[0].metadata.total).toBe(9)
expect(merchResults).toHaveLength(2)
const starbucks = merchResults.find(r => r.metadata.merchant === 'Starbucks')!
const teavana = merchResults.find(r => r.metadata.merchant === 'Teavana')!
expect(starbucks.metadata.total).toBe(5)
expect(teavana.metadata.total).toBe(4)
})
})
// ============= Error Handling =============
describe('error handling', () => {
it('should throw when querying an undefined aggregate', async () => {
await expect(brain.find({ aggregate: 'nonexistent' }))
.rejects.toThrow()
})
it('should throw when defining aggregate without groupBy', () => {
expect(() => brain.defineAggregate({
name: 'bad',
source: { type: NounType.Event },
groupBy: [],
metrics: { count: { op: 'count' } }
})).toThrow()
})
})
// ============= removeAggregate =============
describe('removeAggregate', () => {
it('should remove aggregate and reject subsequent queries', async () => {
brain.defineAggregate({
name: 'temp',
source: { type: NounType.Event },
groupBy: ['category'],
metrics: { count: { op: 'count' } }
})
await brain.add({
data: 'Test', type: NounType.Event,
metadata: { category: 'food' }
})
// Aggregate exists
const results = await brain.find({ aggregate: 'temp' })
expect(results).toHaveLength(1)
// Remove it
brain.removeAggregate('temp')
// Should throw on query
await expect(brain.find({ aggregate: 'temp' })).rejects.toThrow()
})
})
// ============= Result format =============
describe('result format', () => {
it('should return Result<T>[] with Measurement type', async () => {
brain.defineAggregate({
name: 'test',
source: { type: NounType.Event },
groupBy: ['category'],
metrics: { count: { op: 'count' } }
})
await brain.add({
data: 'Test', type: NounType.Event,
metadata: { category: 'food' }
})
const results = await brain.find({ aggregate: 'test' })
expect(results).toHaveLength(1)
const result = results[0]
expect(result.id).toBeDefined()
expect(result.score).toBe(1.0)
expect(result.type).toBe(NounType.Measurement)
expect(result.entity).toBeDefined()
expect(result.entity.type).toBe(NounType.Measurement)
expect(result.entity.service).toBe('brainy:aggregation')
expect(result.metadata.__aggregate).toBe('test')
})
})
// ============= Scale test =============
describe('scale', () => {
it('should handle 100 entities with 3 aggregates', async () => {
// Note: Full scale testing (10K+ entities) is in unit tests which skip
// embedding overhead. This integration test verifies end-to-end wiring
// with real Brainy operations including embeddings.
brain.defineAggregate({
name: 'by_category', source: { type: NounType.Event },
groupBy: ['category'],
metrics: { total: { op: 'sum', field: 'amount' }, count: { op: 'count' } }
})
brain.defineAggregate({
name: 'by_merchant', source: { type: NounType.Event },
groupBy: ['merchant'],
metrics: { total: { op: 'sum', field: 'amount' } }
})
brain.defineAggregate({
name: 'monthly', source: { type: NounType.Event },
groupBy: [{ field: 'date', window: 'month' }],
metrics: { total: { op: 'sum', field: 'amount' }, count: { op: 'count' } }
})
const categories = ['food', 'transport', 'housing', 'entertainment', 'utilities']
const merchants = ['Starbucks', 'Uber', 'Amazon', 'Netflix', 'Con Edison']
const baseDate = Date.UTC(2024, 0, 1)
for (let i = 0; i < 100; i++) {
await brain.add({
data: `Transaction ${i}`,
type: NounType.Event,
metadata: {
category: categories[i % 5],
merchant: merchants[i % 5],
amount: Math.round(Math.random() * 10000) / 100,
date: baseDate + (i % 90) * 86400_000
}
})
}
// Verify category aggregate
const catResults = await brain.find({ aggregate: 'by_category' })
expect(catResults).toHaveLength(5)
const totalCount = catResults.reduce((sum, r) => sum + (r.metadata.count as number), 0)
expect(totalCount).toBe(100)
// Verify merchant aggregate
const merchResults = await brain.find({ aggregate: 'by_merchant' })
expect(merchResults).toHaveLength(5)
// Verify monthly aggregate
const monthlyResults = await brain.find({ aggregate: 'monthly' })
expect(monthlyResults.length).toBeGreaterThan(0)
const monthlyTotalCount = monthlyResults.reduce(
(sum, r) => sum + (r.metadata.count as number), 0
)
expect(monthlyTotalCount).toBe(100)
}, 60_000)
})
})

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@ -0,0 +1,620 @@
import { describe, it, expect, beforeEach, afterEach } from 'vitest'
import { AggregationIndex } from '../../../src/aggregation/AggregationIndex'
import { MemoryStorage } from '../../../src/storage/storageFactory'
import { NounType } from '../../../src/types/graphTypes'
import type { AggregateDefinition, AggregateGroupState } from '../../../src/types/brainy.types'
describe('AggregationIndex', () => {
let storage: MemoryStorage
let index: AggregationIndex
beforeEach(async () => {
storage = new MemoryStorage()
await storage.init()
index = new AggregationIndex(storage)
await index.init()
})
afterEach(async () => {
await index.close()
})
// ============= Definition Management =============
describe('defineAggregate', () => {
it('should register a valid aggregate definition', () => {
const def: AggregateDefinition = {
name: 'test_agg',
source: { type: NounType.Event },
groupBy: ['category'],
metrics: { count: { op: 'count' } }
}
index.defineAggregate(def)
expect(index.hasAggregate('test_agg')).toBe(true)
expect(index.getDefinitions()).toHaveLength(1)
expect(index.getDefinitions()[0].name).toBe('test_agg')
})
it('should reject definition without name', () => {
expect(() => index.defineAggregate({
name: '',
source: { type: NounType.Event },
groupBy: ['x'],
metrics: { count: { op: 'count' } }
})).toThrow('requires a name')
})
it('should reject definition without groupBy', () => {
expect(() => index.defineAggregate({
name: 'bad',
source: { type: NounType.Event },
groupBy: [],
metrics: { count: { op: 'count' } }
})).toThrow('at least one groupBy')
})
it('should reject definition without metrics', () => {
expect(() => index.defineAggregate({
name: 'bad',
source: { type: NounType.Event },
groupBy: ['x'],
metrics: {}
})).toThrow('at least one metric')
})
it('should reject sum metric without field', () => {
expect(() => index.defineAggregate({
name: 'bad',
source: { type: NounType.Event },
groupBy: ['x'],
metrics: { total: { op: 'sum' } }
})).toThrow("requires a 'field'")
})
it('should allow count metric without field', () => {
index.defineAggregate({
name: 'ok',
source: { type: NounType.Event },
groupBy: ['x'],
metrics: { count: { op: 'count' } }
})
expect(index.hasAggregate('ok')).toBe(true)
})
})
describe('removeAggregate', () => {
it('should remove an existing aggregate', () => {
index.defineAggregate({
name: 'temp',
source: { type: NounType.Event },
groupBy: ['x'],
metrics: { count: { op: 'count' } }
})
expect(index.hasAggregate('temp')).toBe(true)
index.removeAggregate('temp')
expect(index.hasAggregate('temp')).toBe(false)
})
})
// ============= Write-Time Hooks =============
describe('onEntityAdded', () => {
const spendingDef: AggregateDefinition = {
name: 'spending',
source: { type: NounType.Event, where: { domain: 'financial' } },
groupBy: ['category'],
metrics: {
total: { op: 'sum', field: 'amount' },
count: { op: 'count' },
average: { op: 'avg', field: 'amount' },
highest: { op: 'max', field: 'amount' },
lowest: { op: 'min', field: 'amount' }
}
}
beforeEach(() => {
index.defineAggregate(spendingDef)
})
it('should accumulate sum/count/avg/min/max for matching entities', () => {
index.onEntityAdded('e1', {
type: NounType.Event,
metadata: { domain: 'financial', category: 'food', amount: 10 }
})
index.onEntityAdded('e2', {
type: NounType.Event,
metadata: { domain: 'financial', category: 'food', amount: 20 }
})
index.onEntityAdded('e3', {
type: NounType.Event,
metadata: { domain: 'financial', category: 'food', amount: 30 }
})
const results = index.queryAggregate({ name: 'spending' })
expect(results).toHaveLength(1)
expect(results[0].groupKey).toEqual({ category: 'food' })
expect(results[0].metrics.total).toBe(60)
expect(results[0].metrics.count).toBe(3)
expect(results[0].metrics.average).toBe(20)
expect(results[0].metrics.highest).toBe(30)
expect(results[0].metrics.lowest).toBe(10)
expect(results[0].count).toBe(3)
})
it('should create separate groups for different keys', () => {
index.onEntityAdded('e1', {
type: NounType.Event,
metadata: { domain: 'financial', category: 'food', amount: 10 }
})
index.onEntityAdded('e2', {
type: NounType.Event,
metadata: { domain: 'financial', category: 'transport', amount: 50 }
})
const results = index.queryAggregate({ name: 'spending' })
expect(results).toHaveLength(2)
const food = results.find(r => r.groupKey.category === 'food')!
const transport = results.find(r => r.groupKey.category === 'transport')!
expect(food.metrics.total).toBe(10)
expect(transport.metrics.total).toBe(50)
})
it('should skip entities that do not match source filter', () => {
// Wrong type
index.onEntityAdded('e1', {
type: NounType.Person,
metadata: { domain: 'financial', category: 'food', amount: 100 }
})
// Missing domain
index.onEntityAdded('e2', {
type: NounType.Event,
metadata: { category: 'food', amount: 100 }
})
const results = index.queryAggregate({ name: 'spending' })
expect(results).toHaveLength(0)
})
it('should skip materialized aggregate entities (infinite loop prevention)', () => {
index.onEntityAdded('agg1', {
type: NounType.Measurement,
service: 'brainy:aggregation',
metadata: { domain: 'financial', category: 'food', amount: 999 }
})
const results = index.queryAggregate({ name: 'spending' })
expect(results).toHaveLength(0)
})
it('should skip entities with __aggregate metadata (infinite loop prevention)', () => {
index.onEntityAdded('agg2', {
type: NounType.Event,
metadata: { __aggregate: 'spending', domain: 'financial', category: 'food', amount: 999 }
})
const results = index.queryAggregate({ name: 'spending' })
expect(results).toHaveLength(0)
})
})
describe('onEntityUpdated', () => {
beforeEach(() => {
index.defineAggregate({
name: 'totals',
source: { type: NounType.Event },
groupBy: ['category'],
metrics: {
total: { op: 'sum', field: 'amount' },
count: { op: 'count' }
}
})
})
it('should reverse old contribution and apply new', () => {
const oldEntity = { type: NounType.Event, metadata: { category: 'food', amount: 10 } }
const newEntity = { type: NounType.Event, metadata: { category: 'food', amount: 25 } }
index.onEntityAdded('e1', oldEntity)
expect(index.queryAggregate({ name: 'totals' })[0].metrics.total).toBe(10)
index.onEntityUpdated('e1', newEntity, oldEntity)
const results = index.queryAggregate({ name: 'totals' })
expect(results[0].metrics.total).toBe(25)
expect(results[0].metrics.count).toBe(1)
})
it('should handle category change (different group keys)', () => {
const old = { type: NounType.Event, metadata: { category: 'food', amount: 10 } }
const updated = { type: NounType.Event, metadata: { category: 'transport', amount: 10 } }
index.onEntityAdded('e1', old)
index.onEntityUpdated('e1', updated, old)
const results = index.queryAggregate({ name: 'totals' })
// Old group should be removed (empty), new group should exist
expect(results).toHaveLength(1)
expect(results[0].groupKey.category).toBe('transport')
expect(results[0].metrics.total).toBe(10)
})
it('should handle entity no longer matching source', () => {
const old = { type: NounType.Event, metadata: { category: 'food', amount: 10 } }
const updated = { type: NounType.Person, metadata: { category: 'food', amount: 10 } }
index.onEntityAdded('e1', old)
expect(index.queryAggregate({ name: 'totals' })).toHaveLength(1)
index.onEntityUpdated('e1', updated, old)
expect(index.queryAggregate({ name: 'totals' })).toHaveLength(0)
})
it('should handle entity now matching source', () => {
const old = { type: NounType.Person, metadata: { category: 'food', amount: 10 } }
const updated = { type: NounType.Event, metadata: { category: 'food', amount: 10 } }
index.onEntityAdded('e1', old) // Won't match
expect(index.queryAggregate({ name: 'totals' })).toHaveLength(0)
index.onEntityUpdated('e1', updated, old)
expect(index.queryAggregate({ name: 'totals' })).toHaveLength(1)
expect(index.queryAggregate({ name: 'totals' })[0].metrics.total).toBe(10)
})
})
describe('onEntityDeleted', () => {
beforeEach(() => {
index.defineAggregate({
name: 'totals',
source: { type: NounType.Event },
groupBy: ['category'],
metrics: {
total: { op: 'sum', field: 'amount' },
count: { op: 'count' }
}
})
})
it('should decrement sum and count', () => {
const entity = { type: NounType.Event, metadata: { category: 'food', amount: 10 } }
index.onEntityAdded('e1', entity)
index.onEntityAdded('e2', { type: NounType.Event, metadata: { category: 'food', amount: 20 } })
index.onEntityDeleted('e1', entity)
const results = index.queryAggregate({ name: 'totals' })
expect(results).toHaveLength(1)
expect(results[0].metrics.total).toBe(20)
expect(results[0].metrics.count).toBe(1)
})
it('should remove group when last entity is deleted', () => {
const entity = { type: NounType.Event, metadata: { category: 'food', amount: 10 } }
index.onEntityAdded('e1', entity)
index.onEntityDeleted('e1', entity)
const results = index.queryAggregate({ name: 'totals' })
expect(results).toHaveLength(0)
})
})
// ============= Time Windows =============
describe('time-windowed groupBy', () => {
beforeEach(() => {
index.defineAggregate({
name: 'monthly',
source: { type: NounType.Event },
groupBy: [
'category',
{ field: 'date', window: 'month' }
],
metrics: {
total: { op: 'sum', field: 'amount' },
count: { op: 'count' }
}
})
})
it('should group by both category and time window', () => {
const jan = Date.UTC(2024, 0, 15)
const feb = Date.UTC(2024, 1, 15)
index.onEntityAdded('e1', {
type: NounType.Event,
metadata: { category: 'food', date: jan, amount: 100 }
})
index.onEntityAdded('e2', {
type: NounType.Event,
metadata: { category: 'food', date: feb, amount: 200 }
})
index.onEntityAdded('e3', {
type: NounType.Event,
metadata: { category: 'food', date: jan, amount: 50 }
})
const results = index.queryAggregate({ name: 'monthly' })
expect(results).toHaveLength(2)
const janGroup = results.find(r => r.groupKey.date === '2024-01')!
const febGroup = results.find(r => r.groupKey.date === '2024-02')!
expect(janGroup.metrics.total).toBe(150)
expect(janGroup.metrics.count).toBe(2)
expect(febGroup.metrics.total).toBe(200)
expect(febGroup.metrics.count).toBe(1)
})
})
// ============= Query =============
describe('queryAggregate', () => {
beforeEach(() => {
index.defineAggregate({
name: 'spending',
source: { type: NounType.Event },
groupBy: ['category'],
metrics: {
total: { op: 'sum', field: 'amount' },
count: { op: 'count' }
}
})
// Add several categories
for (let i = 0; i < 5; i++) {
index.onEntityAdded(`food-${i}`, {
type: NounType.Event,
metadata: { category: 'food', amount: 10 * (i + 1) }
})
}
for (let i = 0; i < 3; i++) {
index.onEntityAdded(`transport-${i}`, {
type: NounType.Event,
metadata: { category: 'transport', amount: 20 * (i + 1) }
})
}
index.onEntityAdded('housing-1', {
type: NounType.Event,
metadata: { category: 'housing', amount: 1500 }
})
})
it('should throw for unknown aggregate', () => {
expect(() => index.queryAggregate({ name: 'nonexistent' })).toThrow("not found")
})
it('should return all groups by default', () => {
const results = index.queryAggregate({ name: 'spending' })
expect(results).toHaveLength(3)
})
it('should filter by where clause', () => {
const results = index.queryAggregate({
name: 'spending',
where: { category: 'food' }
})
expect(results).toHaveLength(1)
expect(results[0].groupKey.category).toBe('food')
expect(results[0].metrics.total).toBe(150) // 10+20+30+40+50
})
it('should sort by metric ascending', () => {
const results = index.queryAggregate({
name: 'spending',
orderBy: 'total',
order: 'asc'
})
expect(results[0].metrics.total).toBeLessThanOrEqual(results[1].metrics.total)
})
it('should sort by metric descending', () => {
const results = index.queryAggregate({
name: 'spending',
orderBy: 'total',
order: 'desc'
})
expect(results[0].metrics.total).toBe(1500) // housing
})
it('should support limit', () => {
const results = index.queryAggregate({
name: 'spending',
orderBy: 'total',
order: 'desc',
limit: 2
})
expect(results).toHaveLength(2)
})
it('should support offset', () => {
const all = index.queryAggregate({
name: 'spending',
orderBy: 'total',
order: 'desc'
})
const page2 = index.queryAggregate({
name: 'spending',
orderBy: 'total',
order: 'desc',
offset: 1,
limit: 1
})
expect(page2).toHaveLength(1)
expect(page2[0].groupKey.category).toBe(all[1].groupKey.category)
})
})
// ============= Multiple Overlapping Aggregates =============
describe('multiple aggregates', () => {
it('should update multiple aggregates on a single entity add', () => {
index.defineAggregate({
name: 'by_category',
source: { type: NounType.Event },
groupBy: ['category'],
metrics: { count: { op: 'count' } }
})
index.defineAggregate({
name: 'by_merchant',
source: { type: NounType.Event },
groupBy: ['merchant'],
metrics: { total: { op: 'sum', field: 'amount' } }
})
index.onEntityAdded('e1', {
type: NounType.Event,
metadata: { category: 'food', merchant: 'Starbucks', amount: 5 }
})
const catResults = index.queryAggregate({ name: 'by_category' })
const merchResults = index.queryAggregate({ name: 'by_merchant' })
expect(catResults).toHaveLength(1)
expect(catResults[0].metrics.count).toBe(1)
expect(merchResults).toHaveLength(1)
expect(merchResults[0].metrics.total).toBe(5)
})
})
// ============= Persistence =============
describe('persistence', () => {
it('should persist definitions and state across flush/init cycles', async () => {
index.defineAggregate({
name: 'persist_test',
source: { type: NounType.Event },
groupBy: ['category'],
metrics: { total: { op: 'sum', field: 'amount' } }
})
index.onEntityAdded('e1', {
type: NounType.Event,
metadata: { category: 'food', amount: 42 }
})
// Flush to persist
await index.flush()
// Create new index from same storage
const index2 = new AggregationIndex(storage)
await index2.init()
expect(index2.hasAggregate('persist_test')).toBe(true)
const results = index2.queryAggregate({ name: 'persist_test' })
expect(results).toHaveLength(1)
expect(results[0].metrics.total).toBe(42)
await index2.close()
})
it('should rebuild state when definition hash changes', async () => {
index.defineAggregate({
name: 'hash_test',
source: { type: NounType.Event },
groupBy: ['category'],
metrics: { total: { op: 'sum', field: 'amount' } }
})
index.onEntityAdded('e1', {
type: NounType.Event,
metadata: { category: 'food', amount: 42 }
})
await index.flush()
// Create new index and register a DIFFERENT definition with same name
const index2 = new AggregationIndex(storage)
await index2.init()
// The loaded state should be present (definition unchanged)
expect(index2.queryAggregate({ name: 'hash_test' })[0].metrics.total).toBe(42)
// Now define with different metrics — should clear state
index2.defineAggregate({
name: 'hash_test',
source: { type: NounType.Event },
groupBy: ['category'],
metrics: { count: { op: 'count' } } // Changed from sum to count
})
// State should be fresh (empty — no entities added to the new definition)
const results = index2.queryAggregate({ name: 'hash_test' })
expect(results).toHaveLength(0)
await index2.close()
})
})
// ============= Service Filter =============
describe('source service filter', () => {
it('should filter by service', () => {
index.defineAggregate({
name: 'svc_test',
source: { type: NounType.Event, service: 'finance-app' },
groupBy: ['category'],
metrics: { count: { op: 'count' } }
})
index.onEntityAdded('e1', {
type: NounType.Event,
service: 'finance-app',
metadata: { category: 'food' }
})
index.onEntityAdded('e2', {
type: NounType.Event,
service: 'other-app',
metadata: { category: 'food' }
})
const results = index.queryAggregate({ name: 'svc_test' })
expect(results).toHaveLength(1)
expect(results[0].metrics.count).toBe(1)
})
})
// ============= Scale Test =============
describe('performance at scale', () => {
it('should handle 10,000 entities efficiently', () => {
index.defineAggregate({
name: 'scale_test',
source: { type: NounType.Event },
groupBy: ['category'],
metrics: {
total: { op: 'sum', field: 'amount' },
count: { op: 'count' }
}
})
const categories = ['food', 'transport', 'housing', 'entertainment', 'utilities']
const start = performance.now()
for (let i = 0; i < 10_000; i++) {
index.onEntityAdded(`e${i}`, {
type: NounType.Event,
metadata: {
category: categories[i % categories.length],
amount: Math.random() * 1000
}
})
}
const elapsed = performance.now() - start
// 10K entities should process in under 500ms (O(1) per entity)
expect(elapsed).toBeLessThan(500)
const results = index.queryAggregate({ name: 'scale_test' })
expect(results).toHaveLength(5)
// Each category should have 2000 entities
for (const r of results) {
expect(r.metrics.count).toBe(2000)
}
})
})
})

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import { describe, it, expect, vi, beforeEach, afterEach } from 'vitest'
import { AggregateMaterializer, MaterializerBrainAccess } from '../../../src/aggregation/materializer'
import { NounType } from '../../../src/types/graphTypes'
import type { AggregateDefinition, AggregateGroupState, MetricState } from '../../../src/types/brainy.types'
/**
* Creates a mock brain access object for testing materialization
* without a full Brainy instance.
*/
function createMockBrain(): MaterializerBrainAccess & {
adds: Array<{ data: string; type: NounType; metadata: Record<string, unknown>; id?: string; service?: string }>
updates: Array<{ id: string; data?: string; metadata?: Record<string, unknown>; merge?: boolean }>
} {
const adds: any[] = []
const updates: any[] = []
return {
adds,
updates,
async add(params) {
adds.push(params)
return `mat-${adds.length}`
},
async update(params) {
updates.push(params)
}
}
}
function createGroupState(
groupKey: Record<string, string | number>,
metrics: Record<string, MetricState>,
materializedEntityId?: string
): AggregateGroupState {
return {
groupKey,
metrics,
materializedEntityId,
lastUpdated: Date.now()
}
}
function createMetricState(sum: number, count: number, min: number, max: number): MetricState {
return { sum, count, min, max }
}
describe('AggregateMaterializer', () => {
let brain: ReturnType<typeof createMockBrain>
let materializer: AggregateMaterializer
const definition: AggregateDefinition = {
name: 'spending',
source: { type: NounType.Event },
groupBy: ['category'],
metrics: {
total: { op: 'sum', field: 'amount' },
count: { op: 'count' },
average: { op: 'avg', field: 'amount' },
highest: { op: 'max', field: 'amount' },
lowest: { op: 'min', field: 'amount' }
},
materialize: true
}
beforeEach(() => {
vi.useFakeTimers()
brain = createMockBrain()
materializer = new AggregateMaterializer(brain, 100) // 100ms debounce for tests
})
afterEach(() => {
materializer.close()
vi.useRealTimers()
})
it('should create a Measurement entity on first materialization', async () => {
const groupState = createGroupState(
{ category: 'food' },
{
total: createMetricState(150, 3, 10, 80),
count: createMetricState(3, 3, Infinity, -Infinity),
average: createMetricState(150, 3, 10, 80),
highest: createMetricState(150, 3, 10, 80),
lowest: createMetricState(150, 3, 10, 80)
}
)
materializer.scheduleMaterialize('spending', definition, { category: 'food' }, groupState)
// Should not have fired yet (debounced)
expect(brain.adds).toHaveLength(0)
// Advance timers past debounce
await vi.advanceTimersByTimeAsync(150)
expect(brain.adds).toHaveLength(1)
const added = brain.adds[0]
expect(added.type).toBe('measurement')
expect(added.service).toBe('brainy:aggregation')
expect(added.metadata.__aggregate).toBe('spending')
expect(added.metadata.category).toBe('food')
expect(added.metadata.total).toBe(150)
expect(added.metadata.count).toBe(3)
expect(added.metadata.average).toBe(50)
expect(added.metadata.highest).toBe(80)
expect(added.metadata.lowest).toBe(10)
expect(added.data).toContain('spending:')
expect(added.data).toContain('category=food')
})
it('should update existing entity when materializedEntityId is set', async () => {
const groupState = createGroupState(
{ category: 'food' },
{
total: createMetricState(200, 4, 10, 100),
count: createMetricState(4, 4, Infinity, -Infinity)
},
'existing-entity-id'
)
materializer.scheduleMaterialize('spending', definition, { category: 'food' }, groupState)
await vi.advanceTimersByTimeAsync(150)
expect(brain.adds).toHaveLength(0)
expect(brain.updates).toHaveLength(1)
expect(brain.updates[0].id).toBe('existing-entity-id')
expect(brain.updates[0].metadata!.total).toBe(200)
})
it('should debounce rapid updates', async () => {
const groupState1 = createGroupState(
{ category: 'food' },
{ total: createMetricState(100, 1, 100, 100), count: createMetricState(1, 1, Infinity, -Infinity) }
)
const groupState2 = createGroupState(
{ category: 'food' },
{ total: createMetricState(200, 2, 50, 150), count: createMetricState(2, 2, Infinity, -Infinity) }
)
materializer.scheduleMaterialize('spending', definition, { category: 'food' }, groupState1)
await vi.advanceTimersByTimeAsync(50)
materializer.scheduleMaterialize('spending', definition, { category: 'food' }, groupState2)
await vi.advanceTimersByTimeAsync(150)
// Only the second (latest) state should be materialized
expect(brain.adds).toHaveLength(1)
expect(brain.adds[0].metadata.total).toBe(200)
})
it('should not materialize when materialize=false', async () => {
const defNoMat: AggregateDefinition = {
...definition,
materialize: false
}
const groupState = createGroupState(
{ category: 'food' },
{ total: createMetricState(100, 1, 100, 100) }
)
materializer.scheduleMaterialize('spending', defNoMat, { category: 'food' }, groupState)
await vi.advanceTimersByTimeAsync(150)
expect(brain.adds).toHaveLength(0)
})
it('should not materialize when materialize=undefined', async () => {
const defNoMat: AggregateDefinition = {
...definition,
materialize: undefined
}
const groupState = createGroupState(
{ category: 'food' },
{ total: createMetricState(100, 1, 100, 100) }
)
materializer.scheduleMaterialize('spending', defNoMat, { category: 'food' }, groupState)
await vi.advanceTimersByTimeAsync(150)
expect(brain.adds).toHaveLength(0)
})
describe('flush', () => {
it('should immediately materialize all pending entries', async () => {
const groupState = createGroupState(
{ category: 'food' },
{ total: createMetricState(100, 1, 100, 100), count: createMetricState(1, 1, Infinity, -Infinity) }
)
materializer.scheduleMaterialize('spending', definition, { category: 'food' }, groupState)
expect(brain.adds).toHaveLength(0)
await materializer.flush()
expect(brain.adds).toHaveLength(1)
})
})
describe('close', () => {
it('should cancel pending timers without materializing', async () => {
const groupState = createGroupState(
{ category: 'food' },
{ total: createMetricState(100, 1, 100, 100) }
)
materializer.scheduleMaterialize('spending', definition, { category: 'food' }, groupState)
materializer.close()
await vi.advanceTimersByTimeAsync(200)
expect(brain.adds).toHaveLength(0)
})
})
})

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import { describe, it, expect } from 'vitest'
import { bucketTimestamp, parseBucketRange } from '../../../src/aggregation/timeWindows'
describe('timeWindows', () => {
describe('bucketTimestamp', () => {
// Use a fixed timestamp: 2024-03-15 14:30:45 UTC
const ts = Date.UTC(2024, 2, 15, 14, 30, 45)
it('should bucket by hour', () => {
expect(bucketTimestamp(ts, 'hour')).toBe('2024-03-15T14')
})
it('should bucket by day', () => {
expect(bucketTimestamp(ts, 'day')).toBe('2024-03-15')
})
it('should bucket by week', () => {
// 2024-03-15 is a Friday in ISO week 11
expect(bucketTimestamp(ts, 'week')).toBe('2024-W11')
})
it('should bucket by month', () => {
expect(bucketTimestamp(ts, 'month')).toBe('2024-03')
})
it('should bucket by quarter', () => {
expect(bucketTimestamp(ts, 'quarter')).toBe('2024-Q1')
})
it('should bucket by year', () => {
expect(bucketTimestamp(ts, 'year')).toBe('2024')
})
it('should bucket by custom interval (300 seconds = 5 min)', () => {
const result = bucketTimestamp(ts, { seconds: 300 })
// Should floor to nearest 5-minute boundary
const parsed = new Date(result).getTime()
expect(parsed % (300 * 1000)).toBe(0)
expect(parsed).toBeLessThanOrEqual(ts)
expect(ts - parsed).toBeLessThan(300 * 1000)
})
it('should handle midnight correctly for day', () => {
const midnight = Date.UTC(2024, 0, 1, 0, 0, 0)
expect(bucketTimestamp(midnight, 'day')).toBe('2024-01-01')
})
it('should handle end of year for month', () => {
const dec = Date.UTC(2024, 11, 31, 23, 59, 59)
expect(bucketTimestamp(dec, 'month')).toBe('2024-12')
})
it('should handle Q4 correctly', () => {
const oct = Date.UTC(2024, 9, 1)
expect(bucketTimestamp(oct, 'quarter')).toBe('2024-Q4')
})
it('should handle Q2 correctly', () => {
const may = Date.UTC(2024, 4, 15)
expect(bucketTimestamp(may, 'quarter')).toBe('2024-Q2')
})
it('should handle week at year boundary', () => {
// Dec 31, 2024 is in ISO week 1 of 2025
const yearEnd = Date.UTC(2024, 11, 31)
const result = bucketTimestamp(yearEnd, 'week')
// Should be 2025-W01 (ISO standard: week containing the first Thursday)
expect(result).toBe('2025-W01')
})
it('should handle leap year Feb 29', () => {
const leapDay = Date.UTC(2024, 1, 29, 12, 0, 0)
expect(bucketTimestamp(leapDay, 'day')).toBe('2024-02-29')
expect(bucketTimestamp(leapDay, 'month')).toBe('2024-02')
})
})
describe('parseBucketRange', () => {
it('should parse hour range', () => {
const range = parseBucketRange('2024-03-15T14', 'hour')
expect(range.start).toBe(Date.UTC(2024, 2, 15, 14, 0, 0))
expect(range.end).toBe(Date.UTC(2024, 2, 15, 15, 0, 0))
})
it('should parse day range', () => {
const range = parseBucketRange('2024-03-15', 'day')
expect(range.start).toBe(Date.UTC(2024, 2, 15, 0, 0, 0))
expect(range.end).toBe(Date.UTC(2024, 2, 16, 0, 0, 0))
})
it('should parse week range', () => {
const range = parseBucketRange('2024-W11', 'week')
// ISO week 11 of 2024 starts on Monday March 11
expect(range.start).toBe(Date.UTC(2024, 2, 11, 0, 0, 0))
expect(range.end - range.start).toBe(7 * 86400_000) // 7 days
})
it('should parse month range', () => {
const range = parseBucketRange('2024-03', 'month')
expect(range.start).toBe(Date.UTC(2024, 2, 1, 0, 0, 0))
expect(range.end).toBe(Date.UTC(2024, 3, 1, 0, 0, 0))
})
it('should parse quarter range', () => {
const range = parseBucketRange('2024-Q1', 'quarter')
expect(range.start).toBe(Date.UTC(2024, 0, 1, 0, 0, 0))
expect(range.end).toBe(Date.UTC(2024, 3, 1, 0, 0, 0))
})
it('should parse year range', () => {
const range = parseBucketRange('2024', 'year')
expect(range.start).toBe(Date.UTC(2024, 0, 1, 0, 0, 0))
expect(range.end).toBe(Date.UTC(2025, 0, 1, 0, 0, 0))
})
it('should parse custom interval range', () => {
const ts = new Date(Date.UTC(2024, 2, 15, 14, 30, 0)).toISOString()
const range = parseBucketRange(ts, { seconds: 300 })
expect(range.end - range.start).toBe(300_000)
})
it('should handle Feb range correctly for leap year', () => {
const range = parseBucketRange('2024-02', 'month')
expect(range.start).toBe(Date.UTC(2024, 1, 1, 0, 0, 0))
expect(range.end).toBe(Date.UTC(2024, 2, 1, 0, 0, 0))
// Feb 2024 has 29 days (leap year)
expect(range.end - range.start).toBe(29 * 86400_000)
})
it('should roundtrip: bucket then parse contains original timestamp', () => {
const ts = Date.UTC(2024, 2, 15, 14, 30, 45)
for (const gran of ['hour', 'day', 'month', 'quarter', 'year'] as const) {
const bucket = bucketTimestamp(ts, gran)
const range = parseBucketRange(bucket, gran)
expect(ts).toBeGreaterThanOrEqual(range.start)
expect(ts).toBeLessThan(range.end)
}
})
})
})