fix: 트랙 API DB 접속 버그 수정 (context manager)

- kcgdb.get_conn()을 with문 없이 사용 → cursor 에러
- with kcgdb.get_conn() as conn: 으로 수정
- 디버그 로그 추가 (rows 수, track 매칭 수, vessel_store 크기)
- 결과: 47 vessels, 47 with track data (25567#1 그룹)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

prediction/main.py

@@ -85,24 +85,26 @@ def get_correlation_tracks(
     from cache.vessel_store import vessel_store
 
     try:
-        conn = kcgdb.get_conn()
-        cur = conn.cursor()
+        with kcgdb.get_conn() as conn:
+            cur = conn.cursor()
 
-        # Get correlated vessels from ALL active models
-        cur.execute("""
-            SELECT s.target_mmsi, s.target_type, s.target_name,
-                   s.current_score, m.name AS model_name
-            FROM kcg.gear_correlation_scores s
-            JOIN kcg.correlation_param_models m ON s.model_id = m.id
-            WHERE s.group_key = %s
-              AND s.current_score >= %s
-              AND m.is_active = TRUE
-            ORDER BY s.current_score DESC
-        """, (group_key, min_score))
+            # Get correlated vessels from ALL active models
+            cur.execute("""
+                SELECT s.target_mmsi, s.target_type, s.target_name,
+                       s.current_score, m.name AS model_name
+                FROM kcg.gear_correlation_scores s
+                JOIN kcg.correlation_param_models m ON s.model_id = m.id
+                WHERE s.group_key = %s
+                  AND s.current_score >= %s
+                  AND m.is_active = TRUE
+                ORDER BY s.current_score DESC
+            """, (group_key, min_score))
 
-        rows = cur.fetchall()
-        cur.close()
-        conn.close()
+            rows = cur.fetchall()
+            cur.close()
+
+        logger.info('correlation tracks: group_key=%r, min_score=%s, rows=%d',
+                     group_key, min_score, len(rows))
 
         if not rows:
             return {'groupKey': group_key, 'vessels': []}
@@ -131,6 +133,9 @@ def get_correlation_tracks(
 
         # Get tracks from vessel_store
         tracks = vessel_store.get_vessel_tracks(mmsis, hours)
+        with_tracks = sum(1 for m in mmsis if m in tracks and len(tracks[m]) > 0)
+        logger.info('correlation tracks: %d unique mmsis, %d with track data, vessel_store._tracks has %d entries',
+                     len(mmsis), with_tracks, len(vessel_store._tracks))
 
         # Build response
         vessels = []