bench_tokio_runtime (behind the bench feature) measures the two things
build_runtime changes vs the #[tokio::main] defaults:
A) worker over-subscription — throughput + p50/p99 of an async+CPU workload
with many workers vs core-sized, run under taskset to model a CPU quota.
B) blocking-pool RSS blast radius — peak RSS flooding the blocking pool with
memory-heavy spawn_blocking tasks, default 512 vs bounded.
No Postgres needed. Lets us verify the runtime change empirically before/after.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01JG5yYZ9s868mJwqT2Qz7ez
Adds `bench_blob_prefetch` (behind the `bench` feature) to measure the
local backend's chunk read-ahead depth — the `buffered(N)` read-ahead in
DedupService::stream_chunks fed by BlobStorageBackend::read_prefetch().
The bench reproduces the exact production reassembly combinator over a
real LocalBlobBackend (chunk files scattered across the 256 hash-prefix
dirs) and sweeps the prefetch depth under the two axes that decide whether
read-ahead helps on local disk:
- consumer speed: unthrottled (disk-bound) vs throttled@MB/s (network-bound)
- page cache: warm vs cold (posix_fadvise DONTNEED, Linux best-effort)
N=1 is current production; higher N is the candidate change. Lets us
verify gains/regressions empirically before changing read_prefetch(),
since the trait doc deliberately defaults local to 1.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01JG5yYZ9s868mJwqT2Qz7ez
read_blob_bytes read the same storage.chunk_manifests PK row twice per
full-blob read — blob_size (SELECT total_size) then read_blob_stream
(SELECT chunk_hashes) — even though both columns live in one row. Fold
them into a single `SELECT chunk_hashes, total_size` and share the chunk
stream builder via a new stream_chunks helper. The legacy (no-manifest)
path is unchanged. Output is identical; the read just costs one fewer DB
round-trip.
Benchmark (examples/bench_blob_manifest.rs, isolates the manifest lookup
against the real Postgres): ~1.9x throughput and p50/p99 roughly halved on
that sub-step; the win is the removed round-trip under pool pressure during
upload bursts. Note this is the manifest sub-step only — end-to-end
read_blob_bytes is dominated by the actual chunk reads, and it is a
background path (thumbnail generation / EXIF / indexing), not normal gallery
serving. Methodology + honest framing in benches/BLOB-MANIFEST.md.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Videos now get a thumbnail generated eagerly server-side on upload, through
the same WebP/blob-hash pipeline as photos — instead of the old browser path
that only ran when the Photos grid first rendered a video tile, re-downloaded
the whole video to seek a frame, and PUT 3 JPEGs back (and produced nothing at
all for HEVC/.mov, which a browser <video> cannot decode).
- New VideoFramePort (application) + FfmpegVideoFrameService / NoopVideoFrameService
(infrastructure): shell out to the system ffmpeg (no compile-time libav dep),
extract one representative frame as PNG, bounded by its own semaphore + a
per-process timeout + kill_on_drop. Noop when ffmpeg is absent/disabled, so
videos degrade gracefully to no thumbnail.
- ThumbnailRefreshHook.on_file_created routes video/* to
generate_video_thumbnails_background: stream the (decrypted, reassembled) blob
to a size- and time-bounded temp file on the data volume, extract a frame, and
reuse the shared render_and_persist_all_webp helper — so video thumbnails are
WebP, blob-hash keyed (dedup'd) and content-negotiated, exactly like photos.
- GET thumbnail serves the video's WebP to every client (byte-sniffed
Content-Type); a genuine miss returns 204.
- Config: OXICLOUD_ENABLE_VIDEO_THUMBNAILS (default true, needs ffmpeg detected
at startup) + OXICLOUD_FFMPEG_PATH / _CONCURRENCY / _TIMEOUT_SECS / _MAX_MB.
- Dockerfile installs ffmpeg in the runtime image.
- Frontend: drop the client-side generateVideoThumb/frameFromVideo re-download
path; the server is now the source of truth.
Benchmark (examples/bench_video_thumbnails.rs, needs ffmpeg): 4/4 codecs incl.
HEVC/.mov produce a thumbnail server-side (was 0% for HEVC); ~50-70 ms/frame in
the background; ~3.9 KB preview WebP; up to ~23x less per-first-view transfer on
the test corpus (far more on real multi-MB clips). Methodology in
benches/VIDEO-THUMB.md.
Hardening from an adversarial review: video render holds the decode_semaphore
like the image path; the ffmpeg scale filter bounds both dimensions; the blob
stream has a timeout; the temp file lives on the data volume; the size cap uses
saturating_mul.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Thumbnails are now generated eagerly as lossy WebP (the primary codec) and
served to clients that advertise `Accept: image/webp`; JPEG is kept as a lazy
fallback for older clients and NextCloud, generated on first request and then
cached like WebP.
- ThumbnailFormat{Webp,Jpeg} enum threaded through encode/render/generate, the
on-disk path ({hash}.webp / {hash}.jpg), the moka cache key
(file_id, size, format), and cleanup (both formats removed).
- file_handler: parse Accept -> format, format-keyed ETag, `Vary: Accept` on
every response (incl. 304) so shared caches never serve the wrong codec;
Content-Type is byte-sniffed (infer) so it always matches the bytes.
- preview_handler (NextCloud) pins JPEG.
- webp = "0.3" (vendored libwebp via cc, no system dependency).
WEBP_QUALITY=82, chosen via a quality sweep (bench Table E1): SSIM within
~0.005 of JPEG q80 (imperceptible at thumbnail scale) for ~62% fewer bytes. On
the photo-realistic bench corpus the full set (3 sizes x 3 photos) drops 65.6%
(213->73 KB); real photos with edges/text land nearer ~25-40%. Encode is +5ms,
paid once in the eager background generator (off the request path).
The bench corpus is now photo-realistic (per-channel sums of low-frequency
sinusoids) instead of white noise, which had distorted codec byte ratios.
Methodology + numbers in benches/WEBP.md.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The owner short-circuit in PgAclEngine::check ran a PK query
(SELECT user_id FROM storage.folders/files WHERE id=$1) on every authorization
check of a folder/file — the common case, since users mostly act on their own
resources. Memoise it in an owner_cache (moka, TTL 300s, 100k cap). The owner
column is immutable, so this is safe: the cache maps resource -> real owner and
can never grant a non-owner access (a different caller's owner==uid test fails
against the cached owner and falls through to grants); a hard-deleted resource
that briefly resolves to its former owner simply fails later at execution with
NotFound. The per-check sql_queries counter now increments only on a miss.
Removes 1 DB query + 1 pool-connection acquisition per owner check. Magnitude is
deployment-specific (query latency x whether the pool is contended); see
benches/ACL-OWNER-CACHE.md.
Also adds two DB perf-investigation harnesses, gated behind the `bench` feature
(need the dev Postgres; zero prod impact):
- examples/bench_db_pool.rs + benches/DB-POOL.md — pool size vs tail latency
- examples/bench_owner_cache.rs + benches/ACL-OWNER-CACHE.md — owner query vs cache
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Replace the image crate's scalar resampler with fast_image_resize
(AVX2/SSE4.1/NEON) in a shared encode_thumbnail() helper. render_all now
converts to RGB8 once and SIMD-resizes the shared buffer per size. Lanczos3 for
downscaling, CatmullRom when upscaling (Lanczos rings on enlargement).
Also folds the duplicated path-variant generate_all_sizes_background into the
shared render path -- it had missed BOTH shrink-on-load and SIMD resizing -- so
every thumbnail path now goes through one optimised routine (no duplication).
Measured on 14 cores vs the post-1.5 state (benches/BASELINE.md):
- PNG 2.60x faster (33.6->12.9ms), GIF/WebP 1.25-1.6x: full-resolution decode
paths where the resize dominates, so SIMD helps most
- JPEG only ~7% (shrink-on-load already shrank the bitmap) but peak heap fell
another ~2.5x (17.6->7.1MB): tight RGB buffers, RGB conversion once
- quality SSIM 0.986-0.994 at identical dims (>=0.98 gate)
Thumbnails are now exactly max_dim on the long side (e.g. 400x266) vs the old
fit-within 399x266 -- a <=1px change, invisible under object-fit: cover.
Bench example gains an exact-dims quality reference + semaphore throughput table.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Shrink-on-load decoupled peak heap from source resolution (~18-25 MB per decode
regardless of MP), so the RAM ceiling that justified halving decode concurrency
is gone. max_concurrent_decodes() now defaults to all cores, with an
OXICLOUD_THUMBNAIL_DECODE_CONCURRENCY override for ops tuning.
Measured on the real service path (Semaphore + spawn_blocking), 14 cores:
- 12MP: 92.7 -> 133.7 photos/s (1.44x)
- 24MP: 49.5 -> 69.9 photos/s (1.41x)
peak heap unchanged; cpus*2 yields nothing, confirming cpus is the right ceiling
for CPU-bound work (the gap to 2x is rayon oversubscription -- Task 1.7).
Adds a semaphore-bounded throughput harness (Table D) to the bench example.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Decode JPEGs at the smallest DCT scale (1/8·1/4·1/2·1/1) whose long axis is
still ≥ the largest needed thumbnail (800px), via jpeg-decoder, instead of a
full-resolution decode through the image crate. The full-res bitmap — the
dominant time and RAM cost — is never materialised. PNG/GIF/WebP and unusual
JPEG colour spaces (CMYK / 16-bit grey) fall back to a full decode.
Extracts the shared decode + EXIF-orientation logic into decode_oriented(),
removing the duplication that existed between render_thumbnail_from_data and
render_all_thumbnails_from_data.
Measured on 14 cores (see benches/BASELINE.md):
- render_all 1.8-2.0× faster (12MP 111->61ms, 48MP 398->203ms)
- peak heap 5.5-14.8× lower, now decoupled from source MP (~18-25MB regardless)
- saturated throughput 3-3.6× (parallel efficiency 4.9×->8.5×)
- quality SSIM 0.987-0.999 (>=0.98 gate), PSNR 47-55dB
Also adds the Phase 0 benchmark harness (gated behind the `bench` feature, zero
prod impact): deterministic image corpus (src/bench_support.rs), criterion
latency bench (benches/thumbnails.rs), and a peak-RAM/throughput/SSIM harness
(examples/bench_thumbnails_mem.rs). Baseline + before/after in benches/BASELINE.md.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude