recommend.py 8.9 KB

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  1. import time
  2. import multiprocessing
  3. import traceback
  4. from datetime import datetime
  5. from log import Log
  6. from config import set_config
  7. from video_recall import PoolRecall
  8. from video_rank import video_rank, bottom_strategy, video_rank_by_w_h_rate
  9. from db_helper import RedisHelper
  10. import gevent
  11. log_ = Log()
  12. config_ = set_config()
  13. def video_recommend(mid, uid, size, app_type, algo_type, client_info):
  14. """
  15. 首页线上推荐逻辑
  16. :param mid: mid type-string
  17. :param uid: uid type-string
  18. :param size: 请求视频数量 type-int
  19. :param app_type: 产品标识 type-int
  20. :param algo_type: 算法类型 type-string
  21. :param client_info: 用户位置信息 {"country": "国家", "province": "省份", "city": "城市"}
  22. :return:
  23. """
  24. ab_code = config_.AB_CODE['initial']
  25. # ####### 多进程召回
  26. start_recall = time.time()
  27. # log_.info('====== recall')
  28. '''
  29. cores = multiprocessing.cpu_count()
  30. pool = multiprocessing.Pool(processes=cores)
  31. pool_recall = PoolRecall(app_type=app_type, mid=mid, uid=uid, ab_code=ab_code)
  32. _, last_rov_recall_key, _ = pool_recall.get_video_last_idx()
  33. pool_list = [
  34. # rov召回池
  35. pool.apply_async(pool_recall.rov_pool_recall, (size,)),
  36. # 流量池
  37. pool.apply_async(pool_recall.flow_pool_recall, (size,))
  38. ]
  39. recall_result_list = [p.get() for p in pool_list]
  40. pool.close()
  41. pool.join()
  42. '''
  43. recall_result_list = []
  44. pool_recall = PoolRecall(app_type=app_type, mid=mid, uid=uid, ab_code=ab_code, client_info=client_info)
  45. _, last_rov_recall_key, _ = pool_recall.get_video_last_idx()
  46. t = [gevent.spawn(pool_recall.rov_pool_recall, size), gevent.spawn(pool_recall.flow_pool_recall, size)]
  47. gevent.joinall(t)
  48. recall_result_list = [i.get() for i in t]
  49. end_recall = time.time()
  50. log_.info('mid: {}, uid: {}, recall: {}, execute time = {}ms'.format(
  51. mid, uid, recall_result_list, (end_recall - start_recall) * 1000))
  52. # ####### 排序
  53. start_rank = time.time()
  54. # log_.info('====== rank')
  55. data = {
  56. 'rov_pool_recall': recall_result_list[0],
  57. 'flow_pool_recall': recall_result_list[1]
  58. }
  59. rank_result = video_rank(data=data, size=size)
  60. end_rank = time.time()
  61. log_.info('mid: {}, uid: {}, rank_result: {}, execute time = {}ms'.format(
  62. mid, uid, rank_result, (end_rank - start_rank) * 1000))
  63. if not rank_result:
  64. # 兜底策略
  65. # log_.info('====== bottom strategy')
  66. start_bottom = time.time()
  67. rank_result = bottom_strategy(size=size, app_type=app_type, ab_code=ab_code)
  68. end_bottom = time.time()
  69. log_.info('mid: {}, uid: {}, bottom strategy result: {}, execute time = {}ms'.format(
  70. mid, uid, rank_result, (end_bottom - start_bottom) * 1000))
  71. return rank_result, last_rov_recall_key
  72. def ab_test_op(rank_result, ab_code_list, app_type, mid, uid, **kwargs):
  73. """
  74. 对排序后的结果 按照AB实验进行对应的分组操作
  75. :param rank_result: 排序后的结果
  76. :param ab_code_list: 此次请求参与的 ab实验组
  77. :param app_type: 产品标识
  78. :param mid: mid
  79. :param uid: uid
  80. :param kwargs: 其他参数
  81. :return:
  82. """
  83. # ####### 视频宽高比AB实验
  84. # 对内容精选进行 视频宽高比分发实验
  85. if config_.AB_CODE['w_h_rate'] in ab_code_list and app_type in config_.AB_TEST.get('w_h_rate', []):
  86. rank_result = video_rank_by_w_h_rate(videos=rank_result)
  87. log_.info('app_type: {}, mid: {}, uid: {}, rank_by_w_h_rate_result: {}'.format(
  88. app_type, mid, uid, rank_result))
  89. return rank_result
  90. def update_redis_data(result, app_type, mid, last_rov_recall_key):
  91. """
  92. 根据最终的排序结果更新相关redis数据
  93. :param result: 排序结果
  94. :param app_type: 产品标识
  95. :param mid: mid
  96. :param last_rov_recall_key: 用户上一次在rov召回池对应的位置 redis key
  97. :return: None
  98. """
  99. # ####### redis数据刷新
  100. try:
  101. # log_.info('====== update redis')
  102. # 预曝光数据同步刷新到Redis, 过期时间为0.5h
  103. redis_helper = RedisHelper()
  104. preview_key_name = config_.PREVIEW_KEY_PREFIX + '{}.{}'.format(app_type, mid)
  105. preview_video_ids = [int(item['videoId']) for item in result]
  106. if preview_video_ids:
  107. # log_.error('key_name = {} \n values = {}'.format(preview_key_name, tuple(preview_video_ids)))
  108. redis_helper.add_data_with_set(key_name=preview_key_name, values=tuple(preview_video_ids), expire_time=30 * 60)
  109. log_.info('preview redis update success!')
  110. # 将此次获取的ROV召回池config_.K末位视频id同步刷新到Redis中,方便下次快速定位到召回位置,过期时间为1天
  111. rov_recall_video = [item['videoId'] for item in result[:config_.K]
  112. if item['pushFrom'] == config_.PUSH_FROM['rov_recall']]
  113. if len(rov_recall_video) > 0:
  114. if not redis_helper.get_score_with_value(key_name=config_.UPDATE_ROV_KEY_NAME, value=rov_recall_video[-1]):
  115. redis_helper.set_data_to_redis(key_name=last_rov_recall_key, value=rov_recall_video[-1])
  116. log_.info('last video redis update success!')
  117. # 将此次分发的流量池视频,对 本地分发数-1 进行记录
  118. flow_recall_video = [item for item in result if item['pushFrom'] == config_.PUSH_FROM['flow_recall']]
  119. if flow_recall_video:
  120. update_local_distribute_count(flow_recall_video)
  121. log_.info('update local distribute count success!')
  122. except Exception as e:
  123. log_.error("update redis data fail!")
  124. log_.error(traceback.format_exc())
  125. def update_local_distribute_count(videos):
  126. """
  127. 更新本地分发数
  128. :param videos: 视频列表 type-list [{'videoId':'', 'flowPool':'', 'distributeCount': '',
  129. 'rovScore': '', 'pushFrom': 'flow_pool', 'abCode': self.ab_code}, ....]
  130. :return:
  131. """
  132. try:
  133. redis_helper = RedisHelper()
  134. for item in videos:
  135. key_name = '{}{}.{}'.format(config_.LOCAL_DISTRIBUTE_COUNT_PREFIX, item['videoId'], item['flowPool'])
  136. # 本地记录的分发数 - 1
  137. redis_helper.decr_key(key_name=key_name, amount=1, expire_time=5 * 60)
  138. # if redis_helper.key_exists(key_name=key_name):
  139. # # 该视频本地有记录,本地记录的分发数 - 1
  140. # redis_helper.decr_key(key_name=key_name, amount=1, expire_time=5 * 60)
  141. # else:
  142. # # 该视频本地无记录,接口获取的分发数 - 1
  143. # redis_helper.incr_key(key_name=key_name, amount=int(item['distributeCount']) - 1, expire_time=5 * 60)
  144. except Exception as e:
  145. log_.error('update_local_distribute_count error...')
  146. log_.error(traceback.format_exc())
  147. def video_homepage_recommend(mid, uid, size, app_type, algo_type, client_info):
  148. """
  149. 首页线上推荐逻辑
  150. :param mid: mid type-string
  151. :param uid: uid type-string
  152. :param size: 请求视频数量 type-int
  153. :param app_type: 产品标识 type-int
  154. :param algo_type: 算法类型 type-string
  155. :param client_info: 用户位置信息 {"country": "国家", "province": "省份", "city": "城市"}
  156. :return:
  157. """
  158. # 简单召回 - 排序 - 兜底
  159. rank_result, last_rov_recall_key = video_recommend(mid=mid, uid=uid, size=size, app_type=app_type,
  160. algo_type=algo_type, client_info=client_info)
  161. # ab-test
  162. result = ab_test_op(rank_result=rank_result, ab_code_list=[config_.AB_CODE['w_h_rate']],
  163. app_type=app_type, mid=mid, uid=uid)
  164. # redis数据刷新
  165. update_redis_data(result=result, app_type=app_type, mid=mid, last_rov_recall_key=last_rov_recall_key)
  166. return result
  167. def video_relevant_recommend(video_id, mid, uid, size, app_type):
  168. """
  169. 相关推荐逻辑
  170. :param video_id: 相关推荐的头部视频id
  171. :param mid: mid type-string
  172. :param uid: uid type-string
  173. :param size: 请求视频数量 type-int
  174. :param app_type: 产品标识 type-int
  175. :return: videos type-list
  176. """
  177. # videos = video_recommend(mid=mid, uid=uid, size=size, app_type=app_type, algo_type='', client_info=None)
  178. # 简单召回 - 排序 - 兜底
  179. rank_result, last_rov_recall_key = video_recommend(mid=mid, uid=uid, size=size, app_type=app_type,
  180. algo_type='', client_info=None)
  181. # ab-test
  182. result = ab_test_op(rank_result=rank_result, ab_code_list=[config_.AB_CODE['w_h_rate']],
  183. app_type=app_type, mid=mid, uid=uid, video_id=video_id)
  184. # redis数据刷新
  185. update_redis_data(result=result, app_type=app_type, mid=mid, last_rov_recall_key=last_rov_recall_key)
  186. return result
  187. if __name__ == '__main__':
  188. videos = [{'videoId': '12345', 'flowPool': '133#442#2', 'distributeCount': 10}]
  189. update_local_distribute_count(videos)