diff --git a/app/data/schema.py b/app/data/schema.py
index e2675c2..964ef24 100644
--- a/app/data/schema.py
+++ b/app/data/schema.py
@@ -137,14 +137,6 @@ SCHEMA_STATEMENTS: Iterable[str] = (
     );
     """,
     """
-    CREATE TABLE IF NOT EXISTS indices (
-      id INTEGER PRIMARY KEY AUTOINCREMENT,
-      index_code VARCHAR(10) NOT NULL UNIQUE,
-      name VARCHAR(50) NOT NULL,
-      created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
-    );
-    """,
-    """
     CREATE TABLE IF NOT EXISTS index_basic (
       ts_code TEXT PRIMARY KEY,
       name TEXT,
@@ -618,19 +610,6 @@ def initialize_database() -> MigrationResult:
   with db_session() as session:
     cursor = session.cursor()
 
-    # 指数相关表已在 SCHEMA_STATEMENTS 中定义
-    
-    # 添加默认指数数据
-    indices = [
-        ("000300.SH", "沪深300"),
-        ("000905.SH", "中证500"),
-        ("000852.SH", "中证1000")
-    ]
-    cursor.executemany(
-        "INSERT OR IGNORE INTO indices (index_code, name) VALUES (?, ?)",
-        indices
-    )
-    
     # 创建表
     for statement in SCHEMA_STATEMENTS:
       try:
diff --git a/app/ingest/tushare.py b/app/ingest/tushare.py
index d13f042..f1f1170 100644
--- a/app/ingest/tushare.py
+++ b/app/ingest/tushare.py
@@ -387,8 +387,7 @@ _TABLE_SCHEMAS: Dict[str, str] = {
             trade_date VARCHAR(8) NOT NULL,
             ts_code VARCHAR(10) NOT NULL,
             weight FLOAT,
-            created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
-            INDEX idx_index_weight_lookup (index_code, trade_date)
+            created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
         );
     """,
     "fund_basic": """
@@ -1274,6 +1273,11 @@ def fetch_index_weight(start: date, end: date, index_code: str) -> Iterable[Dict
         {"index_code": index_code, "start_date": start_str, "end_date": end_str},
         limit=5000,
     )
+    # Filter out rows where con_code is null to avoid DB constraint violation
+    if df is not None and not df.empty:
+        df = df.dropna(subset=["con_code"])
+        # Rename con_code to ts_code to match database schema
+        df = df.rename(columns={"con_code": "ts_code"})
     return _df_to_records(df, ["index_code", "trade_date", "ts_code", "weight"])