Backend (each change benchmark-gated with BEFORE replicas + equivalence
gates; see examples/bench_round11_micro.rs, bench_round11_queries.rs,
bench_log_writer.rs and benches/ROUND11.md — final numbers land in the
follow-up doc commit):
- StoragePath re-representation: single canonical joined String, segments
derived on demand; File/Folder drop the duplicated path_string field
(4000→1000 allocs per 500-row listing page)
- Display classifier fusion: classify_display shares one stack-lowered
extension across the three decision trees; call sites in FileDto,
folder/favorites/recent handlers, trash, path-resolver (+ interning
where Arc::from was still used)
- /status.php and /openapi.json memoized into OnceLock<Bytes> (openapi
rebuilt a 171 KiB spec per request: 2.8 ms → 18 ns)
- NC upload-session PROPFIND: write! + pre-sized body + stack RFC2822
dates (2.3-2.6x, 2582→772 allocs at 256 chunks)
- REST download: dead FileDto clone removed (capture mime/size + move)
- CalendarEventDto/TrashedItem into_parts moves (11 KiB ical_data memcpy
gone per CalDAV row); CardDAV getlastmodified stack render
- 4xx path: borrowed ErrorResponse serialize, ErrorKind::as_str,
not_found/already_exists clone kill
- vCard emit via write!; search page moved out with into_iter skip/take;
content-hit UUIDs parsed once; group last-user check via HashSet
- RateLimiter: lock-free get + insert (and_upsert_with variant REJECTED
by benchmark); CSRF token borrow-compare + borrowed cookie extraction
- Thumbnail/preview ETags built from as_str (Debug-identical bytes)
- Encrypted backend: encrypt_in_place_detached single-buffer write path,
chunk-sized reserve in collect_stream; retry labels made lazy
- PG: deferred upload registration 3→1 round-trips (persist_file CTE
template); direct_grant_cache for Calendar/AddressBook/Playlist authz
(single-flight + set_role/clear_role invalidation); expand_user
tokio::join!; geo clusters min(uuid)::text; recluster face assignment
batched into one UNNEST update
- People recluster cosine: norms precomputed once (bit-identical gate)
- NC capabilities poll logs demoted to debug; tracing-appender dep added
for the log-writer benchmark
Frontend:
- ResourceList.selectedEntries O(N)-per-toggle → id-index projection
O(k log k); favorites/recent consume the batchToolbar snippet param and
drop their duplicate filter + dead selectedIds mirror
- Recent: star state via new favoriteIds prop — a star click no longer
rebuilds all N entries
- admin timeAgo >30d fallback uses the cached Intl.DateTimeFormat
- vitest gates in src/lib/components/round11.bench.test.ts
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01ABhTEHuGujvwoodh67Kga7
read_blob_stream / read_blob_range_stream reassembled a CDC file by fetching
its chunks with `buffered(1)` — strictly sequential, so the next chunk's
backend fetch (a file `open` locally; a full request round-trip on S3/Azure)
only started after the current chunk was fully drained.
A benchmark of the exact pipeline (stream::iter(chunks).map(get).buffered(K)
.try_flatten()) showed a blind `buffered(4)` is the WRONG fix: on a local
disk it is neutral on a warm page cache and ~37% SLOWER cold, because
concurrent opens turn one sequential read into several competing random-I/O
streams over content-addressed (scattered) chunk files. The win is entirely
on remote backends, where per-chunk request latency dominates and overlapping
fetches hide it (≈ linear in K).
So the read-ahead depth is now a backend hint, not a constant:
- BlobStorageBackend::read_prefetch() default 1 (sequential; safe for local).
- S3 / Azure override to 8 (overlap GETs to hide TTFB).
- cached / encrypted / retry / migration delegate to the backend that serves
the bytes.
- Both CDC read paths use `self.backend.read_prefetch().max(1)`.
Net: local backend unchanged (no regression); remote reassembly ~4-8x faster.
Ordered `buffered` (not buffer_unordered) keeps chunks in sequence.
Bench (per-chunk fetch-latency model): buffered(1)->(4)/(8) = x3.9 / x7.8
@1ms, x4.0 / x8.1 @5ms, x4.0 / x8.0 @20ms. Local warm: 230ms@1 vs 227ms@4
(noise); local cold: 425ms@1 vs 585ms@4 (why local stays at 1).
https://claude.ai/code/session_01DCszkkU11LYxMEUWr4setK
Edouard Vanbelle