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ffm-baseline
Commit 3e0282f2 authored by 高雅喆's avatar 高雅喆
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update

parent 232a9d62
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Showing with 2 additions and 4 deletions
eda/smart_rank/dist_update_user_history_order_tags.py
View file @ 3e0282f2
...@@ -67,7 +67,7 @@ def get_user_history_order_service_tag(user_id, stat_date): ...@@ -67,7 +67,7 @@ def get_user_history_order_service_tag(user_id, stat_date):
tags_dict = cur_zhengxing.fetchall() tags_dict = cur_zhengxing.fetchall()
tags_list = [i["tag_id"] for i in tags_dict] tags_list = [i["tag_id"] for i in tags_dict]
# 写gmkv # 写gmkv
gm_kv_cli = redis.Redis(host="172.16.40.135", port=5379, db=6, socket_timeout=2000) gm_kv_cli = redis.Redis(host="172.16.40.135", port=5379, db=2, socket_timeout=2000)
user_history_order_tags_key = "user:history_order:tags:user_id:" + str(user_id) user_history_order_tags_key = "user:history_order:tags:user_id:" + str(user_id)
tags_list_json = json.dumps(tags_list) tags_list_json = json.dumps(tags_list)
gm_kv_cli.set(user_history_order_tags_key, tags_list_json) gm_kv_cli.set(user_history_order_tags_key, tags_list_json)
...@@ -115,7 +115,6 @@ if __name__ == '__main__': ...@@ -115,7 +115,6 @@ if __name__ == '__main__':
spark.sparkContext.setLogLevel("WARN") spark.sparkContext.setLogLevel("WARN")
device_ids_lst_rdd = spark.sparkContext.parallelize(device_ids_lst) device_ids_lst_rdd = spark.sparkContext.parallelize(device_ids_lst)
gm_kv_cli = redis.Redis(host="172.16.40.135", port=5379, db=6, socket_timeout=2000)
result = device_ids_lst_rdd.repartition(100).map(lambda x: get_user_history_order_service_tag(x, stat_date)) result = device_ids_lst_rdd.repartition(100).map(lambda x: get_user_history_order_service_tag(x, stat_date))
result.collect() result.collect()
......
eda/smart_rank/dist_update_user_portrait.py
View file @ 3e0282f2
...@@ -110,7 +110,7 @@ def get_user_tag_score(cl_id, all_log_df, stat_date, size=10): ...@@ -110,7 +110,7 @@ def get_user_tag_score(cl_id, all_log_df, stat_date, size=10):
finally_score_lst = finally_score[["tag_id","tag_score"]].to_dict('record') finally_score_lst = finally_score[["tag_id","tag_score"]].to_dict('record')
tag_id_list = tag_list2dict(finally_score_lst, size) tag_id_list = tag_list2dict(finally_score_lst, size)
# 写gmkv # 写gmkv
gm_kv_cli = redis.Redis(host="172.16.40.135", port=5379, db=6, socket_timeout=2000) gm_kv_cli = redis.Redis(host="172.16.40.135", port=5379, db=2, socket_timeout=2000)
cl_id_portrait_key = "user:portrait_tags:cl_id:" + str(cl_id) cl_id_portrait_key = "user:portrait_tags:cl_id:" + str(cl_id)
tag_id_list_json = json.dumps(tag_id_list) tag_id_list_json = json.dumps(tag_id_list)
gm_kv_cli.set(cl_id_portrait_key, tag_id_list_json) gm_kv_cli.set(cl_id_portrait_key, tag_id_list_json)
...@@ -157,7 +157,6 @@ if __name__ == '__main__': ...@@ -157,7 +157,6 @@ if __name__ == '__main__':
spark.sparkContext.setLogLevel("WARN") spark.sparkContext.setLogLevel("WARN")
device_ids_lst_rdd = spark.sparkContext.parallelize(device_ids_lst) device_ids_lst_rdd = spark.sparkContext.parallelize(device_ids_lst)
gm_kv_cli = redis.Redis(host="172.16.40.135", port=5379, db=6, socket_timeout=2000)
result = device_ids_lst_rdd.repartition(100).map(lambda x: get_user_tag_score(x, all_log_df, stat_date)) result = device_ids_lst_rdd.repartition(100).map(lambda x: get_user_tag_score(x, all_log_df, stat_date))
result.collect() result.collect()
......
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