Pre-fix flow:
1. extractor subprocess writes _meta with N remote rows + creates N inner
views in extract.duckdb (rebuild_from_registry skips materialized rows
per design — explicit `continue` at line 389)
2. _run_materialized_pass calls materialize_query, which writes parquet
atomically + returns stats — but never updates _meta
3. orchestrator.rebuild scans _meta, finds only the N remote rows, creates
master views only for them. Materialized parquet is on disk but
invisible to /api/query → 400 'not yet materialized'
Symptom appears after every container recreate (the previous run's _meta
state is wiped because docker compose down nukes the named volume that
backs extract.duckdb on some compose layouts; even on volumes that
persist, the next extractor pass calls _create_meta_table which DROPs
+ CREATEs _meta cleanly).
Fix: after os.replace(tmp_path, parquet_path) in materialize_query, open
extract.duckdb (read-write), DELETE existing _meta row for table_id,
INSERT new one with query_mode='materialized', and CREATE OR REPLACE
VIEW <table_id> AS SELECT * FROM read_parquet(<path>). All inside a
single transaction so concurrent reads see either old or new state, not
torn rows. Fail-soft on lock contention or schema drift — parquet
remains canonical, next sync pass recovers.
Tests: 3 new in test_bq_materialize.py covering:
- meta + inner view registered after materialize, alongside existing
remote rows
- re-run replaces (not duplicates) the meta row
- skips inner-view registration when extract.duckdb doesn't exist yet
(fresh BQ-only deployment edge case)
Pre-fix, materialize ran the admin source_query as 'COPY (sql) TO parquet'
through the DuckDB BQ extension session. The extension defaults to the
BQ Storage Read API for bq.<ds>.<tbl> references, which rejects views
('non-table entities cannot be read with the storage API'). The fix
always wraps admin SQL into bigquery_query('<billing>', '<inner>') so
COPY uses the BQ jobs API uniformly for tables and views.
Cost guardrail dry-run now operates on the inner SQL (BQ-native), so
the BQ Python client parses it and the cap engages — pre-fix the dry-run
hit 'Table-valued function not found: bigquery_query' and fail-opened.
