24f1249a62
Three pieces of the multi-bucket federation made real:
1. Catalog migration (POST /catalog/migrate-buckets)
- One-shot normalizer for ObjectRef.bucket field
- Empty -> "primary"; legacy "data"/"local" -> "primary"
- Idempotent; re-running on canonical state is no-op
- Ran on existing catalog: 12 refs renamed from "data", 2 already
"primary", all 14 now canonical
2. X-Lakehouse-Bucket header middleware on ingest
- resolve_bucket() helper extracts header, returns
(bucket_name, store) or 404 with valid bucket list
- ingest_file and ingest_db_stream now route writes per-request
- Defaults to "primary" when header absent
- pipeline::ingest_file_to_bucket records the actual bucket on the
ObjectRef so catalog stays the source of truth for "where does this
data live"
- Verified: ingest with X-Lakehouse-Bucket: testing lands in
data/_testing/, ingest without header lands in data/, bad header
returns 404 with hint
3. queryd registers every bucket with DataFusion
- QueryEngine now holds Arc<BucketRegistry> instead of single store
- build_context iterates all buckets, registers each as a separate
ObjectStore under URL scheme "lakehouse-{bucket}://"
- ListingTable URLs include the per-object bucket scheme so
DataFusion routes scans automatically based on ObjectRef.bucket
- Profile bucket names like "profile:user" sanitized to
"lakehouse-profile-user" since URL host segments can't contain ":"
- Tolerant of duplicate manifest entries (pre-existing
pipeline::ingest_file behavior creates a fresh dataset id per
ingest); duplicates skipped with debug log
- Backward compat: legacy "lakehouse://data/" URL still registered
pointing at primary
Success gate: cross-bucket CROSS JOIN
SELECT p.name, p.role, a.species
FROM people_test p (bucket: testing)
CROSS JOIN animals a (bucket: primary)
LIMIT 5
returns rows correctly. DataFusion routed each scan to its bucket's
ObjectStore based on the URL scheme.
No regressions: SELECT COUNT(*) FROM candidates still returns 100000
from the primary bucket.
Deferred to Phase 17:
- POST /profile/{user}/activate (HNSW hot-load on profile switch)
- vectord storage paths becoming bucket-scoped (trial journals,
eval sets per-profile)
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
175 lines
9.8 KiB
Markdown
175 lines
9.8 KiB
Markdown
# Phase Tracker
|
||
|
||
## Phase 0: Bootstrap ✅
|
||
- [x] Cargo workspace with all crate stubs compiling
|
||
- [x] `shared` crate: error types, ObjectRef, DatasetId
|
||
- [x] `gateway` with Axum: GET /health → 200
|
||
- [x] tracing + tracing-subscriber wired in gateway
|
||
- [x] justfile with build, test, run recipes
|
||
- [x] docs committed to git
|
||
|
||
## Phase 1: Storage + Catalog ✅
|
||
- [x] storaged: object_store backend init (LocalFileSystem)
|
||
- [x] storaged: Axum endpoints (PUT/GET/DELETE/LIST)
|
||
- [x] shared/arrow_helpers.rs: RecordBatch ↔ Parquet + schema fingerprinting
|
||
- [x] catalogd/registry.rs: in-memory index + manifest persistence
|
||
- [x] catalogd service: POST/GET /datasets + by-name
|
||
- [x] gateway routes wired
|
||
|
||
## Phase 2: Query Engine ✅
|
||
- [x] queryd: SessionContext + object_store config
|
||
- [x] queryd: ListingTable from catalog ObjectRefs
|
||
- [x] queryd service: POST /query/sql → JSON
|
||
- [x] queryd → catalogd wiring
|
||
- [x] gateway routes /query
|
||
|
||
## Phase 3: AI Integration ✅
|
||
- [x] Python sidecar: FastAPI + Ollama (embed/generate/rerank)
|
||
- [x] Dockerfile for sidecar
|
||
- [x] aibridge/client.rs: HTTP client
|
||
- [x] aibridge service: Axum proxy endpoints
|
||
- [x] Model config via env vars
|
||
|
||
## Phase 4: Frontend ✅
|
||
- [x] Dioxus scaffold, WASM build
|
||
- [x] Ask tab: natural language → AI SQL → results
|
||
- [x] Explore tab: dataset browser + AI summary
|
||
- [x] SQL tab: raw DataFusion editor
|
||
- [x] System tab: health checks for all services
|
||
|
||
## Phase 5: Hardening ✅
|
||
- [x] Proto definitions (lakehouse.proto)
|
||
- [x] Internal gRPC: CatalogService on :3101
|
||
- [x] OpenTelemetry tracing: stdout exporter
|
||
- [x] Auth middleware: X-API-Key (toggleable)
|
||
- [x] Config-driven startup: lakehouse.toml
|
||
|
||
## Phase 6: Ingest Pipeline ✅
|
||
- [x] CSV ingest with auto schema detection
|
||
- [x] JSON ingest (array + newline-delimited, nested flattening)
|
||
- [x] PDF text extraction (lopdf)
|
||
- [x] Text/SMS file ingest
|
||
- [x] Content hash dedup (SHA-256)
|
||
- [x] POST /ingest/file multipart upload
|
||
- [x] 12 unit tests
|
||
|
||
## Phase 7: Vector Index + RAG ✅
|
||
- [x] chunker: configurable size + overlap, sentence-boundary aware
|
||
- [x] store: embeddings as Parquet (binary f32 vectors)
|
||
- [x] search: brute-force cosine similarity
|
||
- [x] rag: embed → search → retrieve → LLM answer with citations
|
||
- [x] POST /vectors/index, /search, /rag
|
||
- [x] Background job system with progress tracking
|
||
- [x] Dual-pipeline supervisor with checkpointing + retry
|
||
- [x] 100K embeddings: 177/sec on A4000, zero failures
|
||
- [x] 6 unit tests
|
||
|
||
## Phase 8: Hot Cache + Incremental Updates ✅
|
||
- [x] MemTable hot cache: LRU, configurable max (16GB)
|
||
- [x] POST /query/cache/pin, /cache/evict, GET /cache/stats
|
||
- [x] Delta store: append-only delta Parquet files
|
||
- [x] Merge-on-read: queries combine base + deltas
|
||
- [x] Compaction: POST /query/compact
|
||
- [x] Benchmarked: 9.8x speedup (1M rows: 942ms → 96ms)
|
||
|
||
## Phase 8.5: Agent Workspaces ✅
|
||
- [x] WorkspaceManager with daily/weekly/monthly/pinned tiers
|
||
- [x] Saved searches, shortlists, activity logs per workspace
|
||
- [x] Instant zero-copy handoff between agents
|
||
- [x] Persistence to object storage, rebuild on startup
|
||
|
||
## Phase 9: Event Journal ✅
|
||
- [x] journald crate: append-only mutation log
|
||
- [x] Event schema: entity, field, old/new value, actor, source, workspace
|
||
- [x] In-memory buffer with auto-flush to Parquet
|
||
- [x] GET /journal/history/{entity_id}, /recent, /stats
|
||
- [x] POST /journal/event, /update, /flush
|
||
|
||
## Phase 10: Rich Catalog v2 ✅
|
||
- [x] DatasetManifest: description, owner, sensitivity, columns, lineage, freshness, tags
|
||
- [x] PII auto-detection: email, phone, SSN, salary, address, medical
|
||
- [x] Column-level metadata with sensitivity flags
|
||
- [x] Lineage tracking: source_system → ingest_job → dataset
|
||
- [x] PATCH /catalog/datasets/by-name/{name}/metadata
|
||
- [x] Backward compatible (serde default)
|
||
|
||
## Phase 11: Embedding Versioning ✅
|
||
- [x] IndexRegistry: model_name, model_version, dimensions per index
|
||
- [x] Index metadata persisted as JSON, rebuilt on startup
|
||
- [x] GET /vectors/indexes — list all (filter by source/model)
|
||
- [x] GET /vectors/indexes/{name} — metadata
|
||
- [x] Background jobs auto-register metadata on completion
|
||
|
||
## Phase 12: Tool Registry ✅
|
||
- [x] 6 built-in staffing tools (search_candidates, get_candidate, revenue_by_client, recruiter_performance, cold_leads, open_jobs)
|
||
- [x] Parameter validation + SQL template substitution
|
||
- [x] Permission levels: read / write / admin
|
||
- [x] Full audit trail per invocation
|
||
- [x] GET /tools, GET /tools/{name}, POST /tools/{name}/call, GET /tools/audit
|
||
|
||
## Phase 13: Security & Access Control ✅
|
||
- [x] Role-based access: admin, recruiter, analyst, agent
|
||
- [x] Field-level sensitivity enforcement
|
||
- [x] Column masking determination per agent
|
||
- [x] Query audit logging
|
||
- [x] GET/POST /access/roles, GET /access/audit, POST /access/check
|
||
|
||
## Phase 14: Schema Evolution ✅
|
||
- [x] Schema diff detection (added, removed, type changed, renamed)
|
||
- [x] Fuzzy rename detection (shared word parts)
|
||
- [x] Auto-generated migration rules with confidence scores
|
||
- [x] AI migration prompt builder for complex cases
|
||
- [x] 5 unit tests
|
||
|
||
## Phase 15+: Horizon
|
||
- [x] HNSW vector index with iteration-friendly trial system (2026-04-16)
|
||
- `HnswStore.build_index_with_config` — parameterized ef_construction, ef_search, seed
|
||
- `EmbeddingCache` — pins 100K vectors in memory, shared across trials
|
||
- `harness::EvalSet` — named query sets with brute-force ground truth
|
||
- `TrialJournal` — append-only JSONL at `_hnsw_trials/{index}.jsonl`
|
||
- Endpoints: `/vectors/hnsw/trial`, `/hnsw/trials/{idx}`, `/hnsw/trials/{idx}/best?metric={recall|latency|pareto}`, `/hnsw/evals`, `/hnsw/evals/{name}/autogen`, `/hnsw/cache/stats`
|
||
- Measured on 100K resumes: **brute-force 44-54ms → HNSW 509us-1830us**, recall 0.92-1.00 depending on `ef_construction`. Sweet spot: ec=80 es=30 → p50=873us recall=1.00 — locked in as `HnswConfig::default()`
|
||
- [x] Catalog manifest repair — `POST /catalog/resync-missing` restores row_count and columns from parquet footers (2026-04-16). All 7 staffing tables recovered to PRD-matching 2.47M rows.
|
||
- [~] Federated multi-bucket query — **foundation complete 2026-04-16**, see ADR-017
|
||
- [x] `StorageConfig.buckets` + `rescue_bucket` + `profile_root` config shape
|
||
- [x] `SecretsProvider` trait + `FileSecretsProvider` (reads /etc/lakehouse/secrets.toml, checks 0600 perms)
|
||
- [x] `storaged::BucketRegistry` — multi-backend, rescue-aware, reachability probes
|
||
- [x] `storaged::error_journal::ErrorJournal` — append-only JSONL at `primary://_errors/bucket_errors.jsonl`
|
||
- [x] Endpoints: `GET /storage/buckets`, `GET /storage/errors`, `GET /storage/bucket-health`
|
||
- [x] Bucket-aware I/O: `PUT/GET /storage/buckets/{bucket}/objects/{*key}` with rescue fallback + `X-Lakehouse-Rescue-Used` observability headers
|
||
- [x] Backward compat: empty `[[storage.buckets]]` synthesizes a `primary` from legacy `root`
|
||
- [x] Three-bucket test (primary + rescue + testing) verified: normal reads, rescue fallback with headers, hard-fail missing, write to unknown bucket 503, error journal + health summary
|
||
- [x] `X-Lakehouse-Bucket` header middleware on ingest endpoints (2026-04-16)
|
||
- [x] Catalog migration: `POST /catalog/migrate-buckets` stamps `bucket = "primary"` on legacy refs (12 renamed, 14 total now canonical)
|
||
- [x] `queryd` registers every bucket with DataFusion for cross-bucket SQL — verified with people_test (testing) × animals (primary) CROSS JOIN
|
||
- [ ] Profile hot-load endpoints: `POST /profile/{user}/activate|deactivate` (deferred to Phase 17)
|
||
- [ ] `vectord` bucket-scoped paths (trial journals, eval sets per-bucket) (deferred to Phase 17)
|
||
- [x] Database connector ingest (Postgres first) — 2026-04-16
|
||
- `pg_stream::stream_table_to_parquet` — ORDER BY + LIMIT/OFFSET pagination, configurable batch_size
|
||
- `parse_dsn` — postgresql:// and postgres:// URL scheme, user/password/host/port/db
|
||
- `POST /ingest/db` endpoint: `{dsn, table, dataset_name?, batch_size?, order_by?, limit?}` → streams to Parquet, registers in catalog with PII detection + redacted-password lineage
|
||
- Existing `POST /ingest/postgres/import` (structured config) preserved alongside
|
||
- 4 DSN-parser unit tests + live end-to-end test against `knowledge_base.team_runs` (586 rows, 13 cols, 6 batches, 196ms)
|
||
- [x] Phase B: Lance storage evaluation — 2026-04-16
|
||
- `crates/lance-bench` standalone pilot (Lance 4.0) avoids DataFusion/Arrow version conflict with main stack
|
||
- 8-dimension benchmark on resumes_100k_v2 — see docs/ADR-019-vector-storage.md for scorecard
|
||
- Decision: hybrid architecture. Parquet+HNSW stays primary (2.55× faster search at 100K in-RAM). Lance added as per-profile second backend for random access (112× faster), append (0.08s vs full rewrite), hot-swap (14× faster index builds), and scale past 5M RAM ceiling.
|
||
- [x] Phase C: Decoupled embedding refresh — 2026-04-16
|
||
- `DatasetManifest`: `last_embedded_at`, `embedding_stale_since`, `embedding_refresh_policy` (Manual | OnAppend | Scheduled)
|
||
- `Registry::mark_embeddings_stale` / `clear_embeddings_stale` / `stale_datasets`
|
||
- Ingest paths (CSV pipeline + Postgres streaming) auto-mark-stale when writing to an already-embedded dataset
|
||
- `vectord::refresh::refresh_index` — reads dataset, diffs doc_ids vs existing embeddings, embeds only new rows, writes combined index, clears stale
|
||
- `POST /vectors/refresh/{dataset}` + `GET /vectors/stale`
|
||
- Id columns accept `Utf8`, `Int32`, `Int64`
|
||
- End-to-end on threat_intel: initial 20-row embed 2.1s; re-ingest to 54 rows auto-marks stale; delta refresh embeds only 34 new in 970ms (6× faster than full re-embed); stale cleared
|
||
- [ ] Database connector ingest (Postgres/MySQL)
|
||
- [ ] PDF OCR (Tesseract)
|
||
- [ ] Scheduled ingest (cron)
|
||
- [ ] Fine-tuned domain models
|
||
- [ ] Multi-node query distribution
|
||
|
||
---
|
||
|
||
**30 unit tests | 11 crates | 16 ADRs | 2.47M rows | 100K vectors | All built 2026-03-27**
|
||
**HNSW trial system: 2026-04-16**
|