降配

task/home_feed_recommend_strategy_d.py

@@ -212,9 +212,7 @@ for row in pandas_df.iterrows():
     ctr = row[1]['卡片ctr']
     pid = hashlib.md5((partition_date + device_os_type + active_type + card_content_type + is_cpc).encode("utf8")).hexdigest()
     instert_sql = """replace into home_feed_recommend_strategy_d(
-    day_id,device_os_type,active_type,card_content_type,recommend_type,card_click,card_exposure,avg_page_stay,navbar_search,
-    highlight_word,self_welfare_card,recommend_welfare_card,recommend_content_card,recommend_special_card,transfer_card,video_consultation,
-    partition_day,pid,recommend_ctr,second_jump_ctr,click_ctr,page_pv_20_percent
+    partition_date,device_os_type,active_type,card_content_type,is_cpc,exp_pv,click_pv,ctr,pid
     ) VALUES('{partition_date}','{device_os_type}','{active_type}','{card_content_type}','{is_cpc}',{exp_pv},{click_pv},
     {ctr},'{pid}');""".format(
         partition_date=partition_date, device_os_type=device_os_type, active_type=active_type, card_content_type=card_content_type,