Three behavioural improvements driven by the sub-agent end-to-end test
findings, plus scheduler tweaks to prevent the post-deploy contention
burst we measured.
CATALOG (catalog-side bugs the test agents tripped on):
- new entity_type field per remote row (BASE TABLE / VIEW /
MATERIALIZED VIEW). For views, rows + size_bytes return null
instead of the misleading 0 that __TABLES__ reports.
- where_examples now validates against the table's actual schema
(cached known_columns from refresh). The pre-fix behavior
blindly advertised `country_code = 'CZ'` on tables with no
country_code column — the sub-agent tests reliably hit this on
unit_economics.
- new known_columns + entity_type columns on bq_metadata_cache;
populated by bq_metadata_refresh.refresh_one from the same
fetch_bq_columns_full call (no extra BQ roundtrip) plus a
cheap INFORMATION_SCHEMA.TABLES lookup for table_type.
QUERY COST-GUARD:
- remote_scan_too_large suggestion now names views explicitly:
`Target(s) <ids> are VIEW or MATERIALIZED VIEW. BigQuery does
not push LIMIT into the view body — SELECT * FROM <view>
LIMIT 1 still runs the full underlying scan.` Programmatic
consumers get a new view_targets field on the error detail.
SCHEDULER HYGIENE (the post-deploy 1-minute window where
concurrent parquet downloads dropped to ~1 MB/s):
- SCHEDULER_STARTUP_GRACE_SECONDS (default 60) holds the first
tick so the burst doesn't overlap cache_warmup writes.
- SCHEDULER_BQ_METADATA_INITIAL_OFFSET_MAX_SECONDS (default 900)
randomises bq-metadata-refresh's first-fire offset.
TESTS:
- test_bq_metadata_cache_repo: entity_type + known_columns round-trip
- test_v2_catalog_remote_metadata: where_examples validation, views
return null rows/size_bytes, cold rows have empty examples
- test_api_query_guardrail: VIEW-aware suggestion text + view_targets
- test_connectors_bigquery_metadata: entity_type lookup mock + new
fields in TableMetadata expectations
- test_scheduler_sidecar: grace + jitter env-var resolution
Since 0.47.0 GET /api/v2/catalog enriched each remote BigQuery row by
fetching INFORMATION_SCHEMA.TABLE_STORAGE + COLUMNS through the DuckDB
BigQuery extension *inside the request*. On cold caches that fanned out
to O(N) sequential BQ jobs-API roundtrips — easily 90 s+ on partitioned
/ view-backed tables — and reliably blew the CLI's 30 s httpx
ReadTimeout. Reproduced with py-spy: three AnyIO worker threads stuck
inside connectors/bigquery/metadata._fetch_via_legacy_tables.
Refactor: enrichment is read exclusively from a new persistent
bq_metadata_cache DuckDB table (schema v40), populated by a scheduler-
driven refresh job at SCHEDULER_BQ_METADATA_REFRESH_INTERVAL (default
4 h). Cold catalog response on a fresh container is now tens of
milliseconds with metadata_freshness=never_fetched for unwarmed rows.
New surface:
- POST /api/admin/run-bq-metadata-refresh (scheduler-driven, full)
- POST /api/v2/metadata-cache/refresh?table=<id> (admin, single)
- GET /api/v2/metadata-cache/status (auth, non-admin)
- metadata_freshness field per catalog row
Removed (internal API): v2_catalog._size_hint_for_row,
_resolve_remote_metadata, _metadata_provider_for,
_build_metadata_request, _materialized_size_hint, in-memory
_metadata_cache. Response shape unchanged for external consumers.
991 tests passing; 2 pre-existing failures (test_db v3→v4 ladder,
test_cli_binary_rename) unrelated to this change.
