The inline INSERT…SELECT backfill in migration 0045 wrapped the table
creation and a ~100 GB pass over image_record.tagger_predictions in one
transaction: nothing committed until the end, it was unmonitorable, and an
earlier MATERIALIZED-CTE form spilled the full 100 GB to temp on NFS. A
deploy got stuck on it for ~2h with image_prediction never appearing.
Split the concerns:
- 0045 now creates ONLY the table + indexes (instant DDL → web boots).
- New backend.app.tasks.admin.backfill_image_predictions_task copies the
>= store-floor predictions from the JSON into image_prediction, batched by
id window and committed per chunk: live progress, resumable (re-enqueues
from the last committed id), idempotent (ON CONFLICT DO NOTHING). json_each
stays in the DB executor streaming each window — no Python-side 100 GB load,
no materialization.
- POST /api/admin/maintenance/backfill-predictions + a Maintenance-tab card
to trigger the one-time run after upgrading.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The one-time backfill that actually shrinks the DB: drops stored
tagger_predictions entries below ml_settings.tagger_store_floor from every
image_record row, and clamps any allowlist min_confidence below the floor up
to it. Keep predicate (confidence >= floor) mirrors Tagger.infer's store gate
so backfilled rows match new imports. Keyset by id ASC, idempotent,
self-resumes on the soft time limit; runs on the maintenance_long lane.
pg_dump copies live data only, so this alone fixes the #739 backup timeout —
the reclaim (VACUUM FULL / pg_repack on image_record) is a separate, optional
disk-return step, brief because post-prune the live data is tiny.
- admin.prune_low_confidence_predictions_task + POST /api/admin/maintenance/prune-predictions
- PrunePredictionsCard in the Maintenance panel (shows the current floor)
- tests: registration + prune-keeps->=floor/drops-<floor + allowlist clamp
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
bvandeusen