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* perf(codex-usage): resume rollout scans at the last parsed byte Codex rollout files are append-only and grow all day, but any append changed both mtime and size, so `canReuse` discarded the cached entry and the scanner re-read the whole file from byte 0 on the Electron main process. On one real corpus that was 6.59 GB re-read per cycle across 26.63 GB / 21,110 files. Each parsed file now persists a resume point: the offset just past the last newline-terminated line, the parse context at that offset (session id, cwd, model, running totals), a sha256 of the 4 KiB before it, and the file's dev:ino. A grown file resumes there and merges the appended rollup into the cached one; anything unproven falls back to a full reparse — truncation, an in-place rewrite, rotation, a counted tail with no trailing newline, a legacy copied-session suffix offset, or a file that must reclaim deferred fork claims. Resume never depends on mtime equality, so a coarse-mtime filesystem cannot hide an append. Fixture: a 75,737-byte rollout with a 758-byte append re-read 76,495 bytes before and 8,950 after (the append plus two bounded 4 KiB boundary windows). Also bounds the automation-attribution force predicate for both Codex and Claude: it keyed on `lastScanError`, so a persistently failing scan forced a fresh full rescan on every single lookup. It now keys on the most recent scan attempt, which is one forced scan per run regardless of outcome. * perf(usage): run the Claude/Codex/OpenCode usage scans on a worker thread The three first-party usage scans walk whole rollout and transcript corpora and read OpenCode's SQLite synchronously, all on the Electron main process. They rarely produce a long stall — the JSONL reader streams, so it yields to the loop between chunks — but they pin the main-process event loop at ~95% utilization for the scan's whole duration, which is what every IPC message, timer and window event then queues behind. Move that work to one lazily-spawned, unref'd worker thread shared by all three providers, following the OpenCode SQLite scanner precedent (#8864). Measured on a synthetic 4,000-rollout corpus (25.8 MB cache): a cold scan drops from 2,147 ms of main-thread time to 31 ms, and a steady-state incremental scan from 165 ms to 64 ms. The worker is stateless and the cache crosses the boundary both ways. That costs ~64 ms of structured clone at this corpus size, against 2,147 ms saved on the cold path, and it keeps the persisted cache the single source of truth — a worker-owned copy would need an invalidation protocol and a second resident copy of the same multi-MB array. Failure is closed, never a silent empty result: a worker that cannot spawn, times out, or crash-loops rejects, and the store records the scan error and keeps the previous projection. Two clients already carried the same FIFO/timeout/crash-cap machinery, so extract it once as WorkerThreadRequestQueue (with the packaged entry-path resolver as worker-thread-entry-path) and move all three onto it, rather than adding a third copy. Their existing tests pass unchanged. The oracle is event-loop utilization on the calling thread, not a stopwatch: usage-scan-worker-event-loop.test.ts runs the same scan both ways and asserts the worker leg leaves the caller idle while the main-thread leg does not, so CI load moves both legs together (#18788). * test(usage): compare the two scan arms instead of two fixed thresholds The event-loop oracle claimed to be self-calibrating — its header said "the ratio is self-calibrating, so CI load moves both legs together (#18788) instead of tipping a fixed millisecond threshold." It computed no ratio. Two separate `it()` blocks each asserted an absolute threshold against its own arm, run separately, so load moved them independently. The comment described a test nobody wrote, and the flake it promised was impossible is the one that landed: `activeRatio > 0.8` on the calling-thread arm measured 0.764 on an ubuntu runner. Fixing the comment is not enough, because the fraction is the wrong quantity. CPU contention drags the calling-thread arm's active/wall fraction *down* toward the worker's, since the loop parks waiting on a contended libuv pool. A 4-vCPU Linux container measured that arm at 0.175-0.756 across twenty runs, idle and loaded — never once above 0.8. Active *milliseconds* move the other way: contention stretches the caller's JS time far more than it stretches the worker arm's fixed post-and-deserialize cost, so the gap widens under load. Merge the two arms into one case over one corpus and assert the worker arm costs the caller under a fifth of the inline arm's active milliseconds. Same twenty Linux runs: 10.9x-83.6x, passing throughout. Keep the presence preconditions on both arms — an arm that silently scanned nothing satisfies the comparison trivially — and extend them to the calling-thread arm, which previously checked only file and session counts. * fix(ports): name the dropped command when the probe queue is full The shared-queue extraction turned `Port scan command queue is full; dropped ${command}.` into a constant string, because `describeFull` was given no way to see the request. Pile-up is per-probe, so the name is the only thing in that log that identifies which of lsof/ps/netstat was shed. Pass the rejected request to `describeFull` and restore the name. The request is built before the cap check so it exists to be named; the id it burns is a correlation token, so a gap costs nothing. The existing overflow test asserted only the error class, which is why the regression escaped a 29-test suite. It now dispatches the overflow under a different command than the accepted ones and asserts the message text, so a message that names the wrong request fails too. Also add a direct WorkerThreadRequestQueue test. Three subsystems share the queue and each client test only sees the parts its own protocol exercises, with `queueCap` reachable from port-scan alone. Covers one-at-a-time FIFO dispatch, the deadline starting at dispatch rather than enqueue, the consecutive-death cap, and both points where that count clears. And record the child-process hazard at the usage worker entry. `terminate()` reaps nothing the thread spawned, and OpenCode discovery reaches a fork today: `wslGated*` forks the WSL transcript sidecar for a `\\wsl$\...` path, which a Windows `OPENCODE_DB` or `XDG_DATA_HOME` can be. One scan through that entry with a UNC `OPENCODE_DB` forked a sidecar that outlived `terminate()`. * test(ai-vault): assert the OpenCode worker messages exactly, not by fragment Checked every message string in the two clients the shared-queue extraction rewrote against origin/main. Only the port-scan queue-full one regressed (fixed in the previous commit); the OpenCode SQLite client's four messages render identically, the remaining source diffs being renames — `error.message` to `lastError`, `call.timeoutMs` and `CALL_DEADLINE_MS` to `timeoutMs`. `session-scanner-worker-client.ts` was not touched by the extraction. But its suite could not have caught it either. `/timed out/`, `/exited with code/` and a bare `rejects.toThrow()` all still match a message that has lost its interpolated value, which is the same blind spot that let the port-scan regression through. Assert the rendered text instead: the timeout names its deadline, the exit names its code, and the crash-loop drain still carries the text of the fault that killed the run. * fix(usage): correct the worker entry's child-process note The previous note said `worker.terminate()` leaves a forked sidecar orphaned. It does not, and the reproduction that appeared to show it used a stub sidecar missing the `process.on('disconnect', () => process.exit(0))` the real entry has. With a faithful one: the sidecar lives exactly as long as the thread and is gone within 2s of `terminate()`, because tearing the thread down closes the IPC channel it owned. Two worker lifecycles forked two sidecars and leaked neither, and the pre-worker main-thread path reaps its sidecar the same way, on host exit. What is true and worth recording: a fork is reachable from this bundle at all, which is easy to miss; it survives only as long as the channel does; and the sidecar is now re-forked per worker lifecycle instead of pooled for the app's life. State those, and warn that a future child which does not exit on channel close would not get the same free cleanup. * fix(usage): kill a wedged scan worker on no progress, not on wall clock `USAGE_SCAN_TIMEOUT_MS` was a 10-minute deadline on the whole scan. A cold scan of a real history is legitimately minutes — 637 s measured on a 30 GB corpus with 300 worktrees before the per-cwd memo, ~51 s after — so a larger corpus or a slower disk crosses it. Crossing it killed the worker, recorded a scan error and left the cache unadvanced, so the next refresh started cold and died at the same point, forever. The deadline is now a no-progress window. The worker posts a file counter as it walks the corpus (`UsageScanWorkerProgress`, rate-limited to one message a second), and `WorkerThreadRequestQueue` re-arms the active call's timer on each one via the new optional `isProgress`. Clients that do not pass it keep the plain wall-clock deadline. `MAX_CONSECUTIVE_DEATHS` and idle teardown are unchanged. * refactor(usage): report scan progress as a file count, not one call per file Claude's scanner walks batches, so a per-file callback made it loop just to bump a counter.
220 lines
7.3 KiB
TypeScript
220 lines
7.3 KiB
TypeScript
import { LazyWorkerThreadHost, type WorkerThreadFactory } from './lazy-worker-thread-host'
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/**
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* FIFO one-at-a-time request half shared by every main-process worker-thread
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* client: per-call timeout armed at dispatch, respawn-on-fault capped so a
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* payload that reliably kills the worker cannot spin a crash loop, idle
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* teardown, and — the rule that matters — failing queued calls closed instead
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* of moving their work back onto the main thread. `LazyWorkerThreadHost` owns
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* the thread's lifetime; this owns which call a message belongs to.
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*/
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export type WorkerThreadRequestQueueOptions<TRequest> = {
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factory: WorkerThreadFactory
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idleTeardownMs: number
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/** Consecutive deaths after which the remaining queue is failed rather than respawned. */
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maxConsecutiveDeaths: number
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/**
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* Omit for an unbounded queue; set it where pile-up is itself the bug.
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* `describeFull` gets the rejected request so the message can name the work
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* that was dropped, which is the only detail a log has to identify it.
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*/
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queueCap?: { maxQueuedCalls: number; describeFull: (request: TRequest) => string }
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/**
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* Marks a message as liveness for the active call rather than its result.
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* Omit it and `describeTimeout`'s deadline is a wall clock on the whole call;
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* supply it and the deadline becomes a no-progress window, re-armed by every
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* progress message the active call sends. Work that is slow but still moving
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* must not be killed for being slow.
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*/
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isProgress?: (message: { id: number }) => boolean
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/** The client's own error subclass, so callers can tell "no worker" from a fault. */
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createUnavailableError: (message: string) => Error
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describeTimeout: (timeoutMs: number) => string
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describeExit: (code: number) => string
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describeCrashLoop: (lastError: string) => string
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/** First spawn failure only; a repeating one must not repeat the log. */
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onUnavailable: (error: unknown) => void
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}
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type PendingCall<TRequest, TResponse> = {
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request: TRequest
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timeoutMs: number
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resolve: (value: TResponse) => void
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reject: (error: Error) => void
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timer: NodeJS.Timeout | null
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}
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export class WorkerThreadRequestQueue<
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TRequest extends { id: number },
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TResponse extends { id: number }
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> {
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private active: PendingCall<TRequest, TResponse> | null = null
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private queue: PendingCall<TRequest, TResponse>[] = []
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private consecutiveDeaths = 0
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private nextId = 1
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private readonly host: LazyWorkerThreadHost<TResponse>
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constructor(private readonly options: WorkerThreadRequestQueueOptions<TRequest>) {
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this.host = new LazyWorkerThreadHost<TResponse>({
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factory: options.factory,
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idleTeardownMs: options.idleTeardownMs,
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onMessage: (response) => this.onMessage(response),
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onError: (error) => this.onWorkerFault(error),
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onExit: (code) => this.onWorkerExit(code),
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isIdle: () => !this.active && this.queue.length === 0,
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onUnavailable: options.onUnavailable
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})
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}
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/**
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* Queue one request and resolve with the worker's matching response.
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* @param buildRequest - Builds the request body around the correlation id this queue stamps.
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* @param timeoutMs - Deadline measured from dispatch, not from enqueue.
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* @returns The worker's response; rejects on timeout, crash, or an unspawnable worker.
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*/
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dispatch(buildRequest: (id: number) => TRequest, timeoutMs: number): Promise<TResponse> {
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return new Promise((resolve, reject) => {
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// Built before the cap check so a rejection can name the dropped work;
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// the id it burns is only a correlation token, so a gap costs nothing.
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const request = buildRequest(this.nextId++)
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const cap = this.options.queueCap
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if (cap && this.queue.length >= cap.maxQueuedCalls) {
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reject(new Error(cap.describeFull(request)))
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return
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}
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// A fresh burst from full idle starts new work: clear any death count
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// carried from a prior burst so the respawn cap can't drain it early.
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if (!this.active && this.queue.length === 0) {
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this.consecutiveDeaths = 0
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}
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this.queue.push({
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request,
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timeoutMs,
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resolve,
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reject,
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timer: null
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})
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this.pump()
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})
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}
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private pump(): void {
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if (this.active || this.queue.length === 0) {
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return
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}
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const worker = this.host.ensure()
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if (!worker) {
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this.failQueuedAsUnavailable()
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return
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}
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const call = this.queue.shift()
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if (!call) {
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return
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}
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this.active = call
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this.host.clearIdleTimer()
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this.armDeadline(call)
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worker.postMessage(call.request)
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}
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/**
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* Clock starts at dispatch, not enqueue: a queue-inclusive deadline would fire
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* falsely on the calls waiting behind a long one. Re-armed on every progress.
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*/
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private armDeadline(call: PendingCall<TRequest, TResponse>): void {
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if (call.timer) {
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clearTimeout(call.timer)
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}
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call.timer = setTimeout(() => this.onTimeout(call), call.timeoutMs)
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call.timer.unref?.()
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}
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private onMessage(response: TResponse): void {
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const call = this.active
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if (!call || call.request.id !== response.id) {
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return
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}
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// Liveness, not a result: keep waiting, but restart the no-progress window.
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if (this.options.isProgress?.(response)) {
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this.armDeadline(call)
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return
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}
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this.consecutiveDeaths = 0
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this.settle(call, () => call.resolve(response))
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this.afterSettle()
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}
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private onTimeout(call: PendingCall<TRequest, TResponse>): void {
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if (this.active !== call) {
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return
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}
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this.onWorkerFault(new Error(this.options.describeTimeout(call.timeoutMs)))
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}
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private onWorkerExit(code: number): void {
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// A clean self-exit is not a death, but the stale handle must be dropped or
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// the next dispatch would post into the dead worker and stall to timeout.
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if (code === 0 && !this.active && this.queue.length === 0) {
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this.host.destroy()
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return
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}
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this.onWorkerFault(new Error(this.options.describeExit(code)))
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}
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private onWorkerFault(error: Error): void {
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const failed = this.active
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this.host.destroy()
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this.consecutiveDeaths++
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if (failed) {
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this.settle(failed, () => failed.reject(error))
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}
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if (this.consecutiveDeaths >= this.options.maxConsecutiveDeaths) {
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this.drainQueueAfterCrashLoop(error)
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return
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}
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if (this.queue.length > 0) {
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this.pump()
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}
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}
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private drainQueueAfterCrashLoop(error: Error): void {
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const pending = this.queue
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this.queue = []
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this.consecutiveDeaths = 0
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const drainError = new Error(this.options.describeCrashLoop(error.message))
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for (const call of pending) {
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this.settle(call, () => call.reject(drainError))
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}
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}
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private failQueuedAsUnavailable(): void {
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const pending = this.queue
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this.queue = []
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for (const call of pending) {
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this.settle(call, () =>
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call.reject(this.options.createUnavailableError('worker spawn failed'))
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)
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}
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}
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private settle(call: PendingCall<TRequest, TResponse>, run: () => void): void {
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if (call.timer) {
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clearTimeout(call.timer)
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call.timer = null
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}
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if (this.active === call) {
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this.active = null
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}
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run()
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}
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private afterSettle(): void {
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if (this.queue.length > 0) {
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this.pump()
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} else {
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this.host.scheduleIdleTeardown()
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}
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}
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}
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