diff --git a/api/api_v1/endpoints/xquery.py b/api/api_v1/endpoints/xquery.py
index 1d5d36b..79594bb 100644
--- a/api/api_v1/endpoints/xquery.py
+++ b/api/api_v1/endpoints/xquery.py
@@ -16,7 +16,7 @@ from common import *
 
 from api import deps
 from db import get_database
-from db.ckdb import get_ck_db, CKDrive
+from db.ckdb import get_ck_db, CKDrive, ckdb
 from db.redisdb import get_redis_pool, RedisDrive
 
 from models.behavior_analysis import BehaviorAnalysis
@@ -75,42 +75,42 @@ async def ltv_model_sql(
         split_="""AND 1 """
         news_sql = split_sql[0] + split_+new_sql + split_sql[1] + split_+new_sql+ split_sql[2]+split_+split_sql[3]
         df = await ckdb.query_dataframe(news_sql)
-    # 判断11月23号之前的数据
-    list_data_range=analysis.date_range
-    liststr_data_range=[]
-    for i in list_data_range:
-        liststr_data_range.append(str(i))
-    quota = analysis.event_view['quota']
-    #判断是设备LTV则执行下面代码，如是角色实充LTV则不执行
-    if quota == '#distinct_id':
-        if '2021-11-22' in liststr_data_range or '2021-11-22' >=liststr_data_range[-1]:
-            #取搜索最后为11.23号之前的数据
-            if '2021-11-22' >=liststr_data_range[-1]:
-                news_sql=""""""
-                split_sql=sql.split('AND is_new_device = 1')
-                new_sql=split_sql[0]+split_sql[1]+split_sql[2]
-                news_sql+=new_sql
-                df_twenty_three=await ckdb.query_dataframe(news_sql)
-            #取包含有11.23号之前和23号之后的那一段
-            else:
-                start_date=str(list_data_range[0])
-                end_date='2021-11-22'
-                news_sql = """"""
-                split_sql = sql.split('AND is_new_device = 1')
-                for i in split_sql:
-                    news_sql += i
-                #用正则表达式切时间
-                zhengze_time=r'\d{4}-\d{1,2}-\d{1,2}'
-                zhengze_sql=re.split(zhengze_time,news_sql)
-                zz_new_sql=zhengze_sql[0]+start_date+zhengze_sql[1]+end_date+zhengze_sql[2]+start_date+zhengze_sql[3]+end_date+zhengze_sql[4]
-                zz_news_sql=""""""
-                zz_news_sql+=zz_new_sql
-                df_twenty_three = await ckdb.query_dataframe(zz_news_sql)
-            #上下合并两组数据，忽略以前的索引下标
-            df= pd.concat([df,df_twenty_three], axis=0, ignore_index=True)
-            df.sort_values('date', inplace=True)
-            #去重
-            #df.drop_duplicates(inplace=True)
+    # # 判断11月23号之前的数据
+    # list_data_range=analysis.date_range
+    # liststr_data_range=[]
+    # for i in list_data_range:
+    #     liststr_data_range.append(str(i))
+    # quota = analysis.event_view['quota']
+    # #判断是设备LTV则执行下面代码，如是角色实充LTV则不执行
+    # if quota == '#distinct_id':
+    #     if '2021-11-22' in liststr_data_range or '2021-11-22' >=liststr_data_range[-1]:
+    #         #取搜索最后为11.23号之前的数据
+    #         if '2021-11-22' >=liststr_data_range[-1]:
+    #             news_sql=""""""
+    #             split_sql=sql.split('AND is_new_device = 1')
+    #             new_sql=split_sql[0]+split_sql[1]+split_sql[2]
+    #             news_sql+=new_sql
+    #             df_twenty_three=await ckdb.query_dataframe(news_sql)
+    #         #取包含有11.23号之前和23号之后的那一段
+    #         else:
+    #             start_date=str(list_data_range[0])
+    #             end_date='2021-11-22'
+    #             news_sql = """"""
+    #             split_sql = sql.split('AND is_new_device = 1')
+    #             for i in split_sql:
+    #                 news_sql += i
+    #             #用正则表达式切时间
+    #             zhengze_time=r'\d{4}-\d{1,2}-\d{1,2}'
+    #             zhengze_sql=re.split(zhengze_time,news_sql)
+    #             zz_new_sql=zhengze_sql[0]+start_date+zhengze_sql[1]+end_date+zhengze_sql[2]+start_date+zhengze_sql[3]+end_date+zhengze_sql[4]
+    #             zz_news_sql=""""""
+    #             zz_news_sql+=zz_new_sql
+    #             df_twenty_three = await ckdb.query_dataframe(zz_news_sql)
+    #         #上下合并两组数据，忽略以前的索引下标
+    #         df= pd.concat([df,df_twenty_three], axis=0, ignore_index=True)
+    #         df.sort_values('date', inplace=True)
+    #         #去重
+    #         #df.drop_duplicates(inplace=True)
     quota = res['quota']  #字段名
     ltv_n = res['ltv_n']
     #df = await ckdb.query_dataframe(sql)
@@ -159,7 +159,7 @@ async def ltv_model_sql(
     split_time = str_time01.split('-')
     #str_time = str(res['date_range'][0])
     # split_time = str_time.split('-')
-    now_time = time.strftime("%Y-%m-%d", time.localtime())
+    now_time=time.strftime("%Y-%m-%d",time.localtime())
     split_now_time = now_time.split('-')
     today = datetime.datetime(int(split_time[0]), int(split_time[1]), int(split_time[2]))
     now_day = datetime.datetime(int(split_now_time[0]), int(split_now_time[1]), int(split_now_time[2]))