fix(showcase): over-sample + random-order to break near-dup clustering — #699

TABLESAMPLE SYSTEM_ROWS reads CONTIGUOUS rows from each sampled page, so
sequentially-imported near-duplicates (multi-image posts, variant sets) came
back adjacent and clustered in the showcase ("three near-identical in a row").
Sample limit*5 rows (spanning more pages) then ORDER BY random() before taking
limit — breaks the physical adjacency for much better spread, still cheap
(random() over a few hundred rows, not the whole table).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

backend/app/services/showcase_service.py

@@ -20,11 +20,20 @@ class ShowcaseService:
     async def random_sample(self, limit: int = 60) -> list[dict]:
         if limit < 1 or limit > 200:
             raise ValueError("limit must be between 1 and 200")
+        # Over-sample then random-order (#699): SYSTEM_ROWS reads CONTIGUOUS rows
+        # from each sampled page, so sequentially-imported near-duplicates
+        # (multi-image posts, variant sets) come back adjacent and cluster in the
+        # showcase ("three near-identical in a row"). Sampling a multiple of
+        # `limit` spans more pages, and ORDER BY random() before taking `limit`
+        # breaks the physical adjacency — far better spread, still cheap
+        # (random() over a few hundred rows, not the whole table).
+        oversample = min(limit * 5, 1000)
         stmt = select(ImageRecord).from_statement(
             text(
-                "SELECT * FROM image_record "
-                "TABLESAMPLE SYSTEM_ROWS(:n)"
-            ).bindparams(n=limit)
+                "SELECT * FROM ("
+                "  SELECT * FROM image_record TABLESAMPLE SYSTEM_ROWS(:o)"
+                ") sub ORDER BY random() LIMIT :n"
+            ).bindparams(o=oversample, n=limit)
         )
         rows = (await self.session.execute(stmt)).scalars().all()
         return [