Phase 2: DataFusion query engine over Parquet

- queryd: SessionContext with custom URL scheme to avoid path doubling with LocalFileSystem
- queryd: ListingTable registration from catalog ObjectRefs with schema inference
- queryd: POST /query/sql returns JSON {columns, rows, row_count}
- queryd→catalogd wiring: reads all datasets, registers as named tables
- gateway: wires QueryEngine with shared store + registry
- e2e verified: SELECT *, WHERE/ORDER BY, COUNT/AVG all correct

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

docs/PHASES.md

@@ -22,13 +22,13 @@
 **Gate: PASSED** — PUT object → register dataset → list → get by name. All via gateway HTTP.
 
 ## Phase 2: Query Engine
-- [ ] 2.1 — queryd: SessionContext + object_store config
-- [ ] 2.2 — queryd: ListingTable from catalog ObjectRefs
-- [ ] 2.3 — queryd service: POST /query → Arrow IPC or JSON
-- [ ] 2.4 — queryd → catalogd wiring
-- [ ] 2.5 — gateway routes /query
+- [x] 2.1 — queryd: SessionContext + object_store config (custom scheme to avoid path doubling)
+- [x] 2.2 — queryd: ListingTable from catalog ObjectRefs with schema inference
+- [x] 2.3 — queryd service: POST /query/sql → JSON (columns + rows + row_count)
+- [x] 2.4 — queryd → catalogd wiring (reads dataset list, registers as tables)
+- [x] 2.5 — gateway routes /query with QueryEngine state
 
-**Gate:** SQL over Parquet returns correct results via catalog resolution.
+**Gate: PASSED** — SELECT *, WHERE/ORDER BY, COUNT/AVG all return correct results via catalog.
 
 ## Phase 3: AI Integration
 - [ ] 3.1 — Python sidecar: FastAPI + Ollama (embed/generate/rerank)