feat(db): table-health readout — per-table bloat metrics in admin card
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You can't decide what to maintain without seeing what's bloating. Adds a
read-only health panel driven by Postgres' own statistics views.

- services/db_maintenance.py: get_table_health() queries pg_stat_user_tables +
  pg_total_relation_size + pg_database_size — per-table size, live/dead tuples,
  dead-tuple ratio (the bloat signal), and last (auto)vacuum/(auto)analyze.
- routes/admin.py: admin-only GET /api/admin/db-maintenance/health.
- SettingsView.vue: 'Table health' table in the maintenance card, all tables
  sorted by dead tuples, rows >=20% dead-ratio flagged; total DB size shown;
  refreshes after a Run-now so the dead-tuple drop is visible.
- Tests: health row/size shaping + null-timestamp passthrough; route + service
  surface.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
This commit is contained in:
2026-06-14 17:53:24 -04:00
parent c4553d937c
commit 96079d5b77
5 changed files with 208 additions and 4 deletions
+8
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@@ -225,6 +225,14 @@ async def get_db_maintenance():
})
@admin_bp.route("/db-maintenance/health", methods=["GET"])
@admin_required
async def get_db_maintenance_health():
"""Read-only per-table bloat/health stats from Postgres + total DB size."""
from scribe.services.db_maintenance import get_table_health
return jsonify(await get_table_health())
@admin_bp.route("/db-maintenance", methods=["PUT"])
@admin_required
async def update_db_maintenance():
+60 -1
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@@ -18,7 +18,9 @@ import logging
import time
from datetime import datetime, timezone
from scribe.models import engine
from sqlalchemy import text
from scribe.models import async_session, engine
from scribe.services.settings import get_admin_setting, set_admin_setting
logger = logging.getLogger(__name__)
@@ -104,6 +106,63 @@ async def run_maintenance(tables: tuple[str, ...] | list[str] | None = None) ->
return summary
# Read-only table-health query against Postgres' own statistics views. The key
# signal is the dead-tuple ratio (dead / (live + dead)) — that IS bloat; a high
# ratio on a large table means autovacuum isn't keeping up. Timestamps confirm
# maintenance is actually running on each table.
_HEALTH_SQL = text("""
SELECT
relname AS table_name,
n_live_tup AS live,
n_dead_tup AS dead,
CASE WHEN n_live_tup + n_dead_tup > 0
THEN round(100.0 * n_dead_tup / (n_live_tup + n_dead_tup), 1)
ELSE 0 END AS dead_pct,
pg_total_relation_size(relid) AS total_bytes,
n_mod_since_analyze AS mod_since_analyze,
GREATEST(last_vacuum, last_autovacuum) AS last_vacuum,
GREATEST(last_analyze, last_autoanalyze) AS last_analyze
FROM pg_stat_user_tables
ORDER BY n_dead_tup DESC, total_bytes DESC
""")
def _iso(value) -> str | None:
return value.isoformat() if value is not None else None
async def get_table_health() -> dict:
"""Per-table health from Postgres statistics + the total database size.
Read-only (system catalogs only). Returns:
{"db_bytes": int, "tables": [
{"table": str, "live": int, "dead": int, "dead_pct": float,
"total_bytes": int, "mod_since_analyze": int,
"last_vacuum": iso|None, "last_analyze": iso|None}
]}
"""
async with async_session() as session:
db_bytes = (
await session.execute(text("SELECT pg_database_size(current_database())"))
).scalar() or 0
rows = (await session.execute(_HEALTH_SQL)).mappings().all()
tables = [
{
"table": r["table_name"],
"live": int(r["live"] or 0),
"dead": int(r["dead"] or 0),
"dead_pct": float(r["dead_pct"] or 0),
"total_bytes": int(r["total_bytes"] or 0),
"mod_since_analyze": int(r["mod_since_analyze"] or 0),
"last_vacuum": _iso(r["last_vacuum"]),
"last_analyze": _iso(r["last_analyze"]),
}
for r in rows
]
return {"db_bytes": int(db_bytes), "tables": tables}
async def get_last_run() -> dict | None:
"""Return the most recent run summary, or None if it has never run."""
raw = await get_admin_setting(_LAST_RUN_KEY, "")