region_rule_rank_h.py 11 KB

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  1. # -*- coding: utf-8 -*-
  2. # @ModuleName: region_rule_rank_h
  3. # @Author: Liqian
  4. # @Time: 2022/5/5 15:54
  5. # @Software: PyCharm
  6. import datetime
  7. import pandas as pd
  8. import math
  9. from odps import ODPS
  10. from threading import Timer
  11. from utils import MysqlHelper, RedisHelper, get_data_from_odps
  12. from config import set_config
  13. from log import Log
  14. config_, _ = set_config()
  15. log_ = Log()
  16. region_code = {
  17. '河北省': '130000',
  18. '山西省': '140000',
  19. '辽宁省': '210000',
  20. '吉林省': '220000',
  21. '黑龙江省': '230000',
  22. '江苏省': '320000',
  23. '浙江省': '330000',
  24. '安徽省': '340000',
  25. '福建省': '350000',
  26. '江西省': '360000',
  27. '山东省': '370000',
  28. '河南省': '410000',
  29. '湖北省': '420000',
  30. '湖南省': '430000',
  31. '广东省': '440000',
  32. '海南省': '460000',
  33. '四川省': '510000',
  34. '贵州省': '520000',
  35. '云南省': '530000',
  36. '陕西省': '610000',
  37. '甘肃省': '620000',
  38. '青海省': '630000',
  39. '台湾省': '710000',
  40. '北京': '110000',
  41. '天津': '120000',
  42. '内蒙古': '150000',
  43. '上海': '310000',
  44. '广西': '450000',
  45. '重庆': '500000',
  46. '西藏': '540000',
  47. '宁夏': '640000',
  48. '新疆': '650000',
  49. '香港': '810000',
  50. '澳门': '820000',
  51. }
  52. features = [
  53. 'videoid',
  54. 'lastonehour_preview', # 过去1小时预曝光人数
  55. 'lastonehour_view', # 过去1小时曝光人数
  56. 'lastonehour_play', # 过去1小时播放人数
  57. 'lastonehour_share', # 过去1小时分享人数
  58. 'lastonehour_return', # 过去1小时分享,过去1小时回流人数
  59. 'lastonehour_preview_total_final', # 过去1小时预曝光次数
  60. 'lastonehour_view_total_final', # 过去1小时曝光次数
  61. 'lastonehour_play_total_final', # 过去1小时播放次数
  62. 'lastonehour_share_total_final', # 过去1小时分享次数
  63. ]
  64. def get_region_code(region):
  65. """获取省份对应的code"""
  66. mysql_helper = MysqlHelper(mysql_info=config_.MYSQL_INFO)
  67. sql = f"SELECT ad_code FROM region_adcode WHERE parent_id = 0 AND region LIKE '{region}%';"
  68. ad_code = mysql_helper.get_data(sql=sql)
  69. return ad_code[0][0]
  70. def h_data_check(project, table, now_date):
  71. """检查数据是否准备好"""
  72. odps = ODPS(
  73. access_id=config_.ODPS_CONFIG['ACCESSID'],
  74. secret_access_key=config_.ODPS_CONFIG['ACCESSKEY'],
  75. project=project,
  76. endpoint=config_.ODPS_CONFIG['ENDPOINT'],
  77. connect_timeout=3000,
  78. read_timeout=500000,
  79. pool_maxsize=1000,
  80. pool_connections=1000
  81. )
  82. try:
  83. dt = datetime.datetime.strftime(now_date, '%Y%m%d%H')
  84. sql = f'select * from {project}.{table} where dt = {dt}'
  85. with odps.execute_sql(sql=sql).open_reader() as reader:
  86. data_count = reader.count
  87. except Exception as e:
  88. data_count = 0
  89. return data_count
  90. def get_rov_redis_key(now_date):
  91. """获取rov模型结果存放key"""
  92. redis_helper = RedisHelper()
  93. now_dt = datetime.datetime.strftime(now_date, '%Y%m%d')
  94. key_name = f'{config_.RECALL_KEY_NAME_PREFIX}{now_dt}'
  95. if not redis_helper.key_exists(key_name=key_name):
  96. pre_dt = datetime.datetime.strftime(now_date - datetime.timedelta(days=1), '%Y%m%d')
  97. key_name = f'{config_.RECALL_KEY_NAME_PREFIX}{pre_dt}'
  98. return key_name
  99. def get_feature_data(project, table, now_date):
  100. """获取特征数据"""
  101. dt = datetime.datetime.strftime(now_date, '%Y%m%d%H')
  102. # dt = '2022041310'
  103. records = get_data_from_odps(date=dt, project=project, table=table)
  104. feature_data = []
  105. for record in records:
  106. item = {}
  107. for feature_name in features:
  108. item[feature_name] = record[feature_name]
  109. feature_data.append(item)
  110. feature_df = pd.DataFrame(feature_data)
  111. return feature_df
  112. def cal_score(df):
  113. """
  114. 计算score
  115. :param df: 特征数据
  116. :return:
  117. """
  118. # score计算公式: sharerate*backrate*logback*ctr
  119. # sharerate = lastonehour_share/(lastonehour_play+1000)
  120. # backrate = lastonehour_return/(lastonehour_share+10)
  121. # ctr = lastonehour_play/(lastonehour_preview+1000), 对ctr限最大值:K2 = 0.6 if ctr > 0.6 else ctr
  122. # score = sharerate * backrate * LOG(lastonehour_return+1) * K2
  123. df = df.fillna(0)
  124. df['share_rate'] = df['lastonehour_share'] / (df['lastonehour_play'] + 1000)
  125. df['back_rate'] = df['lastonehour_return'] / (df['lastonehour_share'] + 10)
  126. df['log_back'] = (df['lastonehour_return'] + 1).apply(math.log)
  127. df['ctr'] = df['lastonehour_play'] / (df['lastonehour_preview'] + 1000)
  128. df['K2'] = df['ctr'].apply(lambda x: 0.6 if x > 0.6 else x)
  129. df['score'] = df['share_rate'] * df['back_rate'] * df['log_back'] * df['K2']
  130. df = df.sort_values(by=['score'], ascending=False)
  131. return df
  132. def video_rank(df, now_date, now_h, rule_key, param, region):
  133. """
  134. 获取符合进入召回源条件的视频,与每日更新的rov模型结果视频列表进行合并
  135. :param df:
  136. :param now_date:
  137. :param now_h:
  138. :param rule_key: 小时级数据进入条件
  139. :param param: 小时级数据进入条件参数
  140. :param region: 所属地域
  141. :return:
  142. """
  143. # 获取rov模型结果
  144. redis_helper = RedisHelper()
  145. key_name = get_rov_redis_key(now_date=now_date)
  146. initial_data = redis_helper.get_data_zset_with_index(key_name=key_name, start=0, end=-1, with_scores=True)
  147. log_.info(f'initial data count = {len(initial_data)}')
  148. # 获取符合进入召回源条件的视频,进入条件:小时级回流>=20 && score>=0.005
  149. return_count = param.get('return_count')
  150. score_value = param.get('score_rule')
  151. h_recall_df = df[(df['lastonehour_return'] >= return_count) & (df['score'] >= score_value)]
  152. h_recall_videos = h_recall_df['videoid'].to_list()
  153. log_.info(f'h_recall videos count = {len(h_recall_videos)}')
  154. # 写入对应的redis
  155. h_video_ids =[]
  156. h_recall_result = {}
  157. for video_id in h_recall_videos:
  158. score = h_recall_df[h_recall_df['videoid'] == video_id]['score']
  159. h_recall_result[int(video_id)] = float(score)
  160. h_video_ids.append(int(video_id))
  161. h_recall_key_name = \
  162. f"{config_.RECALL_KEY_NAME_PREFIX_REGION_BY_H}{region}.{rule_key}.{datetime.datetime.strftime(now_date, '%Y%m%d')}.{now_h}"
  163. if len(h_recall_result) > 0:
  164. redis_helper.add_data_with_zset(key_name=h_recall_key_name, data=h_recall_result, expire_time=23 * 3600)
  165. # 清空线上过滤应用列表
  166. redis_helper.del_keys(key_name=f"{config_.REGION_H_VIDEO_FILER}{region}.{rule_key}")
  167. # 去重更新rov模型结果,并另存为redis中
  168. initial_data_dup = {}
  169. for video_id, score in initial_data:
  170. if int(video_id) not in h_video_ids:
  171. initial_data_dup[int(video_id)] = score
  172. log_.info(f"initial data dup count = {len(initial_data_dup)}")
  173. initial_key_name = \
  174. f"{config_.RECALL_KEY_NAME_PREFIX_DUP_REGION_H}{region}.{rule_key}.{datetime.datetime.strftime(now_date, '%Y%m%d')}.{now_h}"
  175. if len(initial_data_dup) > 0:
  176. redis_helper.add_data_with_zset(key_name=initial_key_name, data=initial_data_dup, expire_time=23 * 3600)
  177. def rank_by_h(project, table, now_date, now_h, rule_params, region_code_list):
  178. # 获取特征数据
  179. feature_df = get_feature_data(project=project, table=table, now_date=now_date)
  180. # 获取所有的region
  181. # region_code_list = list(set(feature_df[''].to_list()))
  182. # rank
  183. for key, value in rule_params.items():
  184. log_.info(f"rule = {key}, param = {value}")
  185. for region in region_code_list:
  186. log_.info(f"region = {region}")
  187. # 计算score
  188. score_df = cal_score(df=feature_df)
  189. video_rank(df=score_df, now_date=now_date, now_h=now_h, rule_key=key, param=value, region=region)
  190. # to-csv
  191. score_filename = f"score_{region}_{key}_{datetime.datetime.strftime(now_date, '%Y%m%d%H')}.csv"
  192. score_df.to_csv(f'./data/{score_filename}')
  193. def h_rank_bottom(now_date, now_h, rule_key, region_code_list):
  194. """未按时更新数据,用上一小时结果作为当前小时的数据"""
  195. log_.info(f"rule_key = {rule_key}")
  196. # 获取rov模型结果
  197. redis_helper = RedisHelper()
  198. if now_h == 0:
  199. redis_dt = datetime.datetime.strftime(now_date - datetime.timedelta(days=1), '%Y%m%d')
  200. redis_h = 23
  201. else:
  202. redis_dt = datetime.datetime.strftime(now_date, '%Y%m%d')
  203. redis_h = now_h - 1
  204. key_prefix_list = [config_.RECALL_KEY_NAME_PREFIX_REGION_BY_H, config_.RECALL_KEY_NAME_PREFIX_DUP_REGION_H]
  205. # fea_df = get_feature_data(project=project, table=table, now_date=now_date - datetime.timedelta(hours=1))
  206. # region_list = list(set(fea_df[''].to_list()))
  207. for region in region_code_list:
  208. log_.info(f"region = {region}")
  209. for key_prefix in key_prefix_list:
  210. key_name = f"{key_prefix}{region}.{rule_key}.{redis_dt}.{redis_h}"
  211. initial_data = redis_helper.get_data_zset_with_index(key_name=key_name, start=0, end=-1, with_scores=True)
  212. final_data = dict()
  213. for video_id, score in initial_data:
  214. final_data[video_id] = score
  215. # 存入对应的redis
  216. final_key_name = \
  217. f"{key_prefix}{region}.{rule_key}.{datetime.datetime.strftime(now_date, '%Y%m%d')}.{now_h}"
  218. if len(final_data) > 0:
  219. redis_helper.add_data_with_zset(key_name=final_key_name, data=final_data, expire_time=23 * 3600)
  220. # 清空线上过滤应用列表
  221. redis_helper.del_keys(key_name=f"{config_.REGION_H_VIDEO_FILER}{region}.{rule_key}")
  222. def h_timer_check():
  223. rule_params = config_.RULE_PARAMS_REGION
  224. project = config_.PROJECT_REGION
  225. table = config_.TABLE_REGION
  226. region_code_list = [code for region, code in region_code.items()]
  227. now_date = datetime.datetime.today()
  228. log_.info(f"now_date: {datetime.datetime.strftime(now_date, '%Y%m%d%H')}")
  229. now_h = datetime.datetime.now().hour
  230. now_min = datetime.datetime.now().minute
  231. if now_h == 0:
  232. for key, _ in rule_params.items():
  233. h_rank_bottom(now_date=now_date, now_h=now_h, rule_key=key, region_code_list=region_code_list)
  234. return
  235. # 查看当前小时更新的数据是否已准备好
  236. h_data_count = h_data_check(project=project, table=table, now_date=now_date)
  237. if h_data_count > 0:
  238. log_.info(f'h_data_count = {h_data_count}')
  239. # 数据准备好,进行更新
  240. rank_by_h(now_date=now_date, now_h=now_h, rule_params=rule_params,
  241. project=project, table=table, region_code_list=region_code_list)
  242. elif now_min > 50:
  243. log_.info('h_recall data is None, use bottom data!')
  244. for key, _ in rule_params.items():
  245. h_rank_bottom(now_date=now_date, now_h=now_h, rule_key=key, region_code_list=region_code_list)
  246. else:
  247. # 数据没准备好,1分钟后重新检查
  248. Timer(60, h_timer_check).start()
  249. if __name__ == '__main__':
  250. h_timer_check()