refactor(db)!: clean up business SQL access

- make realtime replacement and analysis result writes transactional\n- consolidate SCADA repositories and remove process-global project state\n- validate SCADA batches and use indexed GIS-backed business queries\n\nBREAKING CHANGE: remove the public analysis result writer and the pipeline-health network_name query parameter.

app/infra/db/timescaledb/composite_queries.py

@@ -14,7 +14,6 @@ from app.infra.db.postgresql.scada import ScadaInfoRepository
 from app.infra.db.timescaledb.repositories.realtime import RealtimeRepository
 from app.infra.db.timescaledb.repositories.analysis import AnalysisResultsRepository
 from app.infra.db.timescaledb.repositories.scada import ScadaRepository
-from app.native.wndb.model.pipes import get_pipes_by_property
 
 
 class CompositeQueries:
@@ -454,20 +453,25 @@ class CompositeQueries:
         if not cleaned_rows:
             raise ValueError("SCADA 数据清洗未产生任何数据库更新")
 
-        updated_rows = await ScadaRepository.update_scada_field_batch(
-            timescale_conn,
-            cleaned_rows,
-            "cleaned_value",
-        )
-        if updated_rows == 0:
-            raise ValueError("SCADA 清洗结果未匹配任何已有监测数据")
+        expected_rows = len({(row[0], row[1]) for row in cleaned_rows})
+        async with timescale_conn.transaction():
+            updated_rows = await ScadaRepository.update_scada_field_batch(
+                timescale_conn,
+                cleaned_rows,
+                "cleaned_value",
+            )
+            if updated_rows != expected_rows:
+                raise ValueError(
+                    "SCADA 清洗目标在写入期间发生变化，"
+                    f"预期更新 {expected_rows} 行，实际更新 {updated_rows} 行"
+                )
 
         return "success"
 
     @staticmethod
     async def predict_pipeline_health(
         timescale_conn: AsyncConnection,
-        network_name: str,
+        postgres_conn: AsyncConnection,
         query_time: datetime,
     ) -> List[Dict[str, Any]]:
         """
@@ -478,7 +482,6 @@ class CompositeQueries:
 
         Args:
             timescale_conn: TimescaleDB 异步连接
-            db_name: 管网数据库名称
             query_time: 查询时间
             property_conditions: 可选的管道筛选条件，如 {"diameter": 300}
 
@@ -505,12 +508,21 @@ class CompositeQueries:
             # 3. 只查询有流速数据的管道的基本信息
             valid_link_ids = list(velocity_data.keys())
 
-            # 批量查询这些管道的详细信息
-            fields = ["id", "diameter", "node1", "node2"]
-            all_links = get_pipes_by_property(network_name, fields=fields)
+            # GIS 物化视图是低频更新管网的查询面；只读取本次有结果的管道。
+            async with postgres_conn.cursor() as cur:
+                await cur.execute(
+                    """
+                    SELECT id, diameter, start_node_id AS node1,
+                           end_node_id AS node2
+                    FROM gis.pipes
+                    WHERE id = ANY(%s)
+                    """,
+                    (valid_link_ids,),
+                )
+                all_links = await cur.fetchall()
 
             # 转换为字典以快速查找
-            links_dict = {link["id"]: link for link in all_links}
+            links_dict = {str(link["id"]): link for link in all_links}
 
             # 获取所有需要查询的节点ID
             node_ids = set()