/** * @module tests/benchmarks/model-b-scalability.spike * @description SPIKE (throwaway, spike/model-b-write-perf branch) — the DECISION-CRITICAL * half of the Model B evaluation. The write-perf spike showed writes are cheap at * durability parity; the adversarial review showed the REAL risk is structural and * grows with the number of retained generations N: * * 1. READ-vs-depth — resolveAt/changedBetween LINEARLY scan the global committedGens * array → historical reads (asOf/get, diff, since) become O(N) = O(database-age). * 2. REOPEN-vs-depth — GenerationStore.open enumerates+sorts EVERY generation dir → O(N) cold start. * 3. RAM-vs-depth — deltaCache holds a Set per committed generation → O(N) resident heap. * 4. COMPACTION cost — the only thing that bounds 1-3; time it + the post-compaction footprint. * * Each is measured at two depths (small, large). A ~linear slope CONFIRMS that brainy-TS's * current global-committedGens design does NOT scale under Model B (every write = a generation), * and that the canonical Model-B history must be a PER-ID INDEX (mirroring cor's delta_history * BTreeMap, O(log n)) rather than a global scan. Memory backend is used where the scan/RAM cost * is backend-independent (committedGens is in-memory); filesystem only where reopen/compaction * touch disk. * * Run (force GC available): node --expose-gc node_modules/.bin/tsx tests/benchmarks/model-b-scalability.spike.ts * small scale: SPIKE_SCALE=small ... */ import { rmSync, mkdirSync, existsSync } from 'node:fs' import { execSync } from 'node:child_process' import { Brainy } from '../../src/index.js' import { NounType } from '../../src/types/graphTypes.js' import type { BrainyConfig } from '../../src/types/brainy.types.js' // Silence brainy's verbose per-brain logging (floods stdout, slows the run). const _log = console.log.bind(console) const say = (...a: any[]) => _log(...a) for (const m of ['log', 'info', 'debug', 'warn'] as const) (console as any)[m] = () => {} const SMALL = process.env.SPIKE_SCALE === 'small' const DIM = 384 const FS_ROOT = '/media/dpsifr/storage/home/Projects/brainy/.spike-data' // Two depths to read the slope. Memory legs can go deep cheaply; fs legs (fsync per gen) stay smaller. const DEPTHS_MEM = SMALL ? [500, 5_000] : [2_000, 20_000] const DEPTHS_FS = SMALL ? [300, 1_500] : [1_000, 6_000] const READ_REPEATS = SMALL ? 20 : 50 function vec(i: number): number[] { const v = new Array(DIM) let mag = 0 for (let d = 0; d < DIM; d++) { const x = Math.sin((i + 1) * 0.001 + d * 0.1); v[d] = x; mag += x * x } mag = Math.sqrt(mag) || 1 for (let d = 0; d < DIM; d++) v[d] /= mag return v } async function mkBrain(backend: 'memory' | 'filesystem', dir?: string): Promise { const storage: BrainyConfig['storage'] = backend === 'memory' ? { type: 'memory' } : { type: 'filesystem', path: dir! } const brain = new Brainy({ requireSubtype: false, storage, eagerEmbeddings: false, // never load WASM — we pass precomputed vectors // Keep history fully retained for the measurement (no mid-run compaction skewing depth). retention: { autoCompact: false } as any, index: { m: 16, efConstruction: 200, efSearch: 50 }, cache: { maxSize: 1000, ttl: 3600 } } as BrainyConfig) brain.use({ name: 'const-embedder', activate: async (ctx: any) => { ctx.registerProvider('embeddings', async () => vec(0)); return true } } as any) await brain.init() return brain } function payload(i: number) { return { type: NounType.Document, subtype: 'note', data: `doc ${i}`, vector: vec(i), metadata: { i, batch: 'spike' } } } function freshDir(name: string): string { const dir = `${FS_ROOT}/${name}` if (existsSync(dir)) rmSync(dir, { recursive: true, force: true }) mkdirSync(dir, { recursive: true }) return dir } function allocBytes(dir: string): number { try { return parseInt(execSync(`du -s --block-size=1 ${dir}`, { encoding: 'utf8' }).split(/\s+/)[0], 10) } catch { return -1 } } const SEED = 32 // small working set; X (id[0]) is the never-updated probe entity /** Build N committed generations via transact([1]). X = ids[0] is seeded then NEVER updated, so a * read of X at the oldest pin must scan all N generations to confirm it is unchanged (worst case). */ async function buildGenerations(b: Brainy, nGens: number): Promise<{ ids: string[]; g0: number; gN: number }> { const ids: string[] = [] // Seed via ONE transact so g0 is a committed generation (asOf needs a committed gen). const seedOps = Array.from({ length: SEED }, (_, i) => ({ op: 'add' as const, ...payload(i) })) const seedDb = await b.transact(seedOps as any) for (const id of (await b.find({ type: NounType.Document, limit: SEED }))) ids.push(id.id) await seedDb.release?.() const g0 = b.generation() // N generations, each a single-op-equivalent transact([1]) update on the CHURN set (ids[1..]), // never touching X=ids[0]. for (let k = 0; k < nGens; k++) { const id = ids[1 + (k % (ids.length - 1))] const d = await b.transact([{ op: 'update', id, metadata: { k } }] as any) await d.release?.() } return { ids, g0, gN: b.generation() } } function median(xs: number[]): number { const s = [...xs].sort((a, b) => a - b); return s[Math.floor(s.length / 2)] } async function timeMs(fn: () => Promise, repeats: number): Promise { const ts: number[] = [] for (let r = 0; r < repeats; r++) { const t = process.hrtime.bigint(); await fn(); ts.push(Number(process.hrtime.bigint() - t) / 1e6) } return median(ts) } async function main() { say(`[scale] start (scale=${SMALL ? 'small' : 'full'}); gc=${typeof (global as any).gc === 'function' ? 'on' : 'OFF (run with node --expose-gc)'}`) if (existsSync(FS_ROOT)) rmSync(FS_ROOT, { recursive: true, force: true }) mkdirSync(FS_ROOT, { recursive: true }) const results: any = { readVsDepth: [], reopenVsDepth: [], ramVsDepth: [], compaction: [] } // ---- 1. READ latency vs history depth (memory; scan is in-memory) ---- say(`\n========== READ latency vs history depth (the O(database-age) test) ==========`) for (const N of DEPTHS_MEM) { const b = await mkBrain('memory') const { ids, g0, gN } = await buildGenerations(b, N) const X = ids[0] // asOf(oldest).get(X): resolveAt(X,g0) scans all N committedGens (X never touched) → expect O(N). const tAsOfGet = await timeMs(async () => { const db = await b.asOf(g0); await db.get(X); await db.release?.() }, READ_REPEATS) // diff(g0,gN): changedBetween scans the full (g0,gN] range → expect O(N). const tDiff = await timeMs(async () => { await b.diff(g0, gN) }, Math.max(5, READ_REPEATS / 5)) await b.close() say(`N=${N.toLocaleString()} gens: asOf(oldest).get(X) = ${tAsOfGet.toFixed(3)} ms | diff(g0,gN) = ${tDiff.toFixed(2)} ms`) results.readVsDepth.push({ N, asOfGetMs: tAsOfGet, diffMs: tDiff }) } { const [a, c] = results.readVsDepth if (a && c) say(` → asOf-get scaling ${a.N}→${c.N} (${(c.N / a.N).toFixed(0)}x depth): ${(c.asOfGetMs / a.asOfGetMs).toFixed(1)}x slower (linear≈${(c.N / a.N).toFixed(0)}x → confirms O(N) scan)`) } // ---- 2. RAM resident vs history depth (memory; deltaCache holds a Set per gen) ---- say(`\n========== RAM (heapUsed) vs history depth (deltaCache O(N) Sets) ==========`) for (const N of DEPTHS_MEM) { if ((global as any).gc) (global as any).gc() const before = process.memoryUsage().heapUsed const b = await mkBrain('memory') await buildGenerations(b, N) if ((global as any).gc) (global as any).gc() const after = process.memoryUsage().heapUsed const perGen = (after - before) / N await b.close() say(`N=${N.toLocaleString()} gens: heapUsed +${((after - before) / 1024 / 1024).toFixed(1)} MiB (${perGen.toFixed(0)} bytes/generation resident)`) results.ramVsDepth.push({ N, deltaBytes: after - before, bytesPerGen: perGen }) } // ---- 3. COLD-REOPEN vs history depth (filesystem; open() walks every gen dir) ---- say(`\n========== COLD-REOPEN time vs history depth (O(generations) dir walk) ==========`) for (const N of DEPTHS_FS) { const dir = freshDir(`reopen-${N}`) let b = await mkBrain('filesystem', dir) await buildGenerations(b, N) await b.close() const tOpen = await timeMs(async () => { const rb = await mkBrain('filesystem', dir); await rb.close() }, SMALL ? 3 : 5) rmSync(dir, { recursive: true, force: true }) say(`N=${N.toLocaleString()} gens: cold reopen = ${tOpen.toFixed(0)} ms`) results.reopenVsDepth.push({ N, reopenMs: tOpen }) } { const [a, c] = results.reopenVsDepth if (a && c) say(` → reopen scaling ${a.N}→${c.N} (${(c.N / a.N).toFixed(0)}x depth): ${(c.reopenMs / a.reopenMs).toFixed(1)}x slower`) } // ---- 4. COMPACTION cost + footprint (filesystem) ---- say(`\n========== COMPACTION cost (the bound on 1-3) ==========`) { const N = DEPTHS_FS[DEPTHS_FS.length - 1] const dir = freshDir(`compact-${N}`) const b = await mkBrain('filesystem', dir) await buildGenerations(b, N) await b.flush() const beforeBytes = allocBytes(`${dir}/_generations`) const t = process.hrtime.bigint() const res = await b.compactHistory({ maxGenerations: 100 } as any) const compMs = Number(process.hrtime.bigint() - t) / 1e6 await b.flush() const afterBytes = allocBytes(`${dir}/_generations`) await b.close() rmSync(dir, { recursive: true, force: true }) say(`N=${N.toLocaleString()} gens → compactHistory({maxGenerations:100}): ${compMs.toFixed(0)} ms, removed ${(res as any)?.removedGenerations ?? '?'} gens`) say(` _generations footprint: ${(beforeBytes / 1024 / 1024).toFixed(1)} MiB → ${(afterBytes / 1024 / 1024).toFixed(1)} MiB allocated`) results.compaction.push({ N, compactMs: compMs, removed: (res as any)?.removedGenerations, beforeBytes, afterBytes }) } const fs = await import('node:fs') fs.writeFileSync('/media/dpsifr/storage/home/Projects/brainy/tests/benchmarks/_scalability-results.json', JSON.stringify(results, null, 2)) say(`\nRaw results → tests/benchmarks/_scalability-results.json`) if (existsSync(FS_ROOT)) rmSync(FS_ROOT, { recursive: true, force: true }) } main().then(() => { say('[scale] done.'); process.exit(0) }).catch((e) => { console.error(e); process.exit(1) })