update

ad_predict.py

@@ -76,25 +76,43 @@ def get_creative_id_with_thompson_weight(mid, creative_id_list, gevent_pool, sor
     gevent.joinall(tasks)
     thompson_res_list = [t.get() for t in tasks]
     # 获取creative_id对应cvr, 给定对应权重
+    # st_1 = time.time()
     cvr_mapping = {}
     creative_weight = {}
-    for creative_id in creative_id_list:
+    key_list = [f"{config_.CREATIVE_CVR_KEY_PREFIX}{creative_id}" for creative_id in creative_id_list]
+    cvr_list = []
+    name_list = []
+    for i in range(len(key_list)):
+        if i % 20 == 0 and i != 0:
+            print(len(name_list))
+            cvr_res = redis_helper.get_batch_key(name_list=name_list)
+            cvr_list.extend(cvr_res)
+            name_list = [key_list[i]]
+        else:
+            name_list.append(key_list[i])
+    if len(name_list) > 0:
+        cvr_res = redis_helper.get_batch_key(name_list=name_list)
+        cvr_list.extend(cvr_res)
+    for i, creative_id in enumerate(creative_id_list):
         creative_weight[creative_id] = config_.CREATIVE_WEIGHT_INITIAL
-        cvr = redis_helper.get_data_from_redis(
-            key_name=f"{config_.CREATIVE_CVR_KEY_PREFIX}{creative_id}")
+        cvr = cvr_list[i]
         if cvr is None:
             continue
         try:
             cvr_mapping[creative_id] = float(cvr)
         except:
             continue
-    cvr_sorted = sorted(cvr_mapping.items(), key=lambda x: x[1], reverse=False)
+    # log_.info(f"st1: {(time.time() - st_1) * 1000}ms")
 
+    # st_2 = time.time()
+    cvr_sorted = sorted(cvr_mapping.items(), key=lambda x: x[1], reverse=False)
     for i, item in enumerate(cvr_sorted):
         creative_id = item[0]
         creative_weight[creative_id] += (i * config_.WEIGHT_GRADIENT)
+    # log_.info(f"st2: {(time.time() - st_2) * 1000}ms")
 
     # 对有cvr的creative进行加权
+    # st_3 = time.time()
     thompson_weight_res_list = []
     weight_sum = sum([weight for _, weight in creative_weight.items()])
     for thompson_res in thompson_res_list:
@@ -106,6 +124,8 @@ def get_creative_id_with_thompson_weight(mid, creative_id_list, gevent_pool, sor
             weight_score = score
         thompson_weight_res = thompson_res + [creative_weight[creative_id], weight_score]
         thompson_weight_res_list.append(thompson_weight_res)
+    # log_.info(f"st3: {(time.time() - st_3) * 1000}ms")
+
     # 重新排序
     thompson_res_rank = sorted(thompson_weight_res_list, key=lambda x: x[7], reverse=True)
     rank_res = {