Three list endpoints resolved each resource with one query per id:
- GET /api/grants/incoming and /api/grants/outgoing used
join_all(ids.map(get_file)) + join_all(ids.map(get_folder)), so a single
page (limit ≤ 200) could demand ~200 concurrent connections from the
20-connection primary pool, causing acquire-timeouts and head-of-line
blocking under load.
- The NextCloud favorites REPORT (oc:filter-files) fetched get_file/
get_folder once per favorite — up to N serial round-trips per sync.
Add by-ids batch reads that mirror the existing get_file/get_folder column
mapping and NOT is_trashed filter:
- FileBlobReadRepository::get_files_by_ids / FolderDbRepository::get_folders_by_ids
(one SELECT ... WHERE id = ANY($1)), exposed as FileRetrievalService::
get_files_by_ids / FolderService::get_folders_by_ids returning DTOs.
- Both grant handlers and the favorites REPORT now issue two batch queries
total and look results up by id, preserving original order. Missing ids
(stale grants whose resource was deleted, or trashed/removed favorites)
drop out exactly as before. No auth-semantics change: these paths already
resolved ids vetted by the authorization engine / favorites table.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01TAzLEQDaLak3dnrEN3YT35
FileContentCache (moka, 512 MiB) was keyed by the file UUID, so content that
the CDC store already deduplicates to ONE blob on disk was cached once PER
FILE in RAM: N files sharing a blob held N copies, all counting against the
512 MiB cap. With effective dedup the cache filled with duplicates and
thrashed.
Key it by the blob hash instead (already on FileDto::content_hash):
- The in-RAM cache now benefits from dedup like the disk does — each distinct
blob is cached once and shared across every file/user that references it,
so a download by user A warms the cache for user B's identical content.
- Content is immutable by hash, so entries never go stale; the existing
invalidate(file_id) calls become harmless no-ops (a UUID never matches a
hash key) and can be removed in a later cleanup.
- ETag is now the immutable content hash (strong validator).
- Guarded: a hash-less stub DTO disables caching for that request rather than
colliding every such file on the empty key.
Response Content-Type still comes from the DTO, not the cache, so keying does
not affect the served MIME (verified).
Benchmark (real moka, exact 512 MiB/weight config, 400 files x 4 MiB = 1600 MiB
working set, 4000 uniform-random accesses):
dedup 1x : file_id 35.8% hit / 2568 reads vs hash 35.6% / 2577 (no dedup -> no change; control)
dedup 5x : file_id 35.8% hit / 2570 reads vs hash 98.0% / 80 (32x fewer disk reads, RAM 512->320 MiB)
dedup 20x: file_id 35.1% hit / 2596 reads vs hash 99.5% / 20 (130x fewer disk reads, RAM 512->80 MiB)
The win scales with the dedup ratio; with no dedup it is a no-op.
https://claude.ai/code/session_01DCszkkU11LYxMEUWr4setK
- JWT secret auto-generates and persists to <STORAGE_PATH>/.jwt_secret
- Remove setup token: first admin setup is open until system initialized
- Fix schema.sql: move CREATE EXTENSION pg_trgm/ltree to top
- Update login UI and auth.js to remove setup token fields
- Add type aliases (FileRow, FolderRow, FolderRowPaginated, FolderRowOptUser) to reduce type complexity
- Simplify redundant closures in app_password_handler and webdav_handler
- Remove needless borrow in auth_handler
- Collapse nested if/let chains in login_lockout, webdav_lock, auth, rate_limit
- Box LockEntry in acquire() Err variant to fix large enum variant warning
- Rename DeviceCodeStatus::from_str to parse to avoid should_implement_trait lint
- Add #[allow(clippy::too_many_arguments)] and #[allow(clippy::result_unit_err)] where appropriate
- Convert integration_tests from cargo feature to custom cfg attribute
- Add check-cfg lint config in Cargo.toml for integration_tests cfg
Replace String with Arc<str> for fields that contain repeated static
values (mime_type, icon_class, icon_special_class, category) in
FileDto, FolderDto, and OptimizedFileContent.
These fields are computed from ~40 static lookup tables and cloned
on every request. With Arc<str>, clone becomes O(1) atomic increment
instead of O(n) heap allocation — saving thousands of allocations/s
under load.
Fields kept as String: id, name, path, folder_id, owner_id
(unique per item, rarely cloned).
Zero API impact — serde serializes Arc<str> identically to String.
https://claude.ai/code/session_01EbAFEfyJNLRmJHmmYDX3Tt
Remove async-trait dependency and use native Rust async fn in traits.
Replace Arc<dyn Trait> with Arc<ConcreteType> throughout the codebase
to enable monomorphization and eliminate dynamic dispatch overhead.
Key changes:
- Remove write-behind cache (no implementation existed)
- Fix should_transcode static method call
- Use ContactStorageAdapter directly instead of dyn AddressBookUseCase
- Clean up unused trait imports across services and DI
https://claude.ai/code/session_01EbAFEfyJNLRmJHmmYDX3Tt
Replace list_files_in_subtree (fetch_all → Vec) with stream_files_in_subtree
that returns a Pin<Box<dyn Stream<Item = Result<File/FileDto>>>> backed by a
PostgreSQL cursor via sqlx::fetch().
Changes:
- FileReadPort::stream_files_in_subtree() returns streaming cursor (no default)
- FileRetrievalUseCase::stream_files_in_subtree() maps File→FileDto on the fly
- FileBlobReadRepository: async_stream::try_stream! + sqlx::fetch() cursor
- batch_operations: consume stream into HashMap incrementally
- zip_service: consume stream into HashMap incrementally
- All stubs/mocks updated (return empty stream)
Eliminates:
- Double allocation: Vec<(9-tuple)> + Vec<File> materialized simultaneously
- Unbounded RAM proportional to subtree size (was ~500 bytes × N files)
- Latency: callers blocked until last row fetched from PG
RAM is now O(folders) for the HashMap, not O(files).
Replace String with Arc<str> for etag and content_type fields in the
content cache. String::clone() allocates and copies the full string on
every cache hit (O(n)), while Arc<str>::clone() is O(1) — just an atomic
ref-count increment.
This eliminates 2 heap allocations per cache hit on the hottest download
path. At 1000 req/s that is 2000 fewer alloc/dealloc cycles per second.
Changed files:
- cache_ports.rs: trait signatures String → Arc<str>
- file_content_cache.rs: CacheEntry fields, get/put methods, tests
- stubs.rs: StubContentCachePort signatures
- file_retrieval_service.rs: caller creates Arc<str> before put()
Replace BFS traversal that issued 2 SQL queries per folder (list_files +
list_folders) with 2 total queries using PostgreSQL ltree <@ operator:
1. list_subtree_folders: single GiST-indexed scan for all folders
2. list_files_in_subtree: single GiST-indexed join for all files
Files are grouped by folder_id in a HashMap, then iterated in directory
order (folders pre-sorted by path from SQL).
Changes across 4 architecture layers:
- Domain: FolderRepository::list_subtree_folders (default impl)
- Application ports: FolderUseCase, FileRetrievalUseCase, FileReadPort
- Application services: FolderService, FileRetrievalService passthroughs
- Infrastructure: PG implementations + ZipService rewrite
Query count: O(N) → O(1). Latency for 100-folder tree: ~200 round-trips → 3.
Standardize code formatting across all 173 Rust source files
using rustfmt. No functional changes - purely cosmetic.
This establishes a consistent code style baseline for the
project going forward.
- Remove Serialize/Deserialize from File, Folder, Session, User, Contact entities
- Create contact_persistence_dto.rs for JSONB persistence in infrastructure layer
- Update contact_pg_repository to use persistence DTOs
- Fix dependency on zip crate (downgrade from 7.2.0 to 2.1.0)
- Fix unused variable warnings in main.rs
- Move PathService import from domain to infrastructure
- Add missing fields to CoreServices and RepositoryServices
- Create proper service initialization in main.rs
Clean Architecture improvements:
- Domain layer no longer depends on serde framework
- Persistence concerns isolated to infrastructure layer
- TokenClaims in auth_service.rs is only exception (required for JWT)