update

task/recommend_strategy_fix.py

@@ -81,8 +81,8 @@ spark.sql("CREATE TEMPORARY FUNCTION is_json AS 'com.gmei.hive.common.udf.UDFJso
 spark.sql("CREATE TEMPORARY FUNCTION arrayMerge AS 'com.gmei.hive.common.udf.UDFArryMerge'")
 
 
-task_days = 120
-for t in range(5, task_days):
+task_days = 3
+for t in range(0, task_days):
     day_num = 0 - t
     now = (datetime.datetime.now() + datetime.timedelta(days=day_num))
     last_30_day_str = (now + datetime.timedelta(days=-30)).strftime("%Y%m%d")

task/spark_test.py

@@ -95,11 +95,8 @@ spark.sql("CREATE TEMPORARY FUNCTION arrayMerge AS 'com.gmei.hive.common.udf.UDF
 sql_search_ctr = r"""
 select count(1) from (
  SELECT  partition_date,            
-                    
                     cl_id,
-                    v.recommend_type,
                     count(card_id) as session_pv0,
-                    count(distinct app_session_id) as session_pv
             FROM
             (
                SELECT partition_date,

task/首页推荐策略日报.sql

@@ -470,6 +470,7 @@ CREATE TABLE recommend_strategy_d_fix(
    recommend_ctr FLOAT,
    second_jump_ctr FLOAT,
    click_ctr FLOAT,
+   page_pv_20_percent FLOAT,
 
    pid varchar(100),
    PRIMARY KEY ( pid )
@@ -478,5 +479,5 @@ CREATE TABLE recommend_strategy_d_fix(
 alert 
 ALTER TABLE recommend_strategy_d ADD recommend_ctr FLOAT;
 ALTER TABLE recommend_strategy_d ADD second_jump_ctr FLOAT;
-ALTER TABLE recommend_strategy_d ADD click_ctr FLOAT;
+ALTER TABLE recommend_strategy_d_fix ADD page_pv_20_percent FLOAT;