update

task/ecommerce_income_report.py

@@ -132,8 +132,10 @@ for t in range(1, task_days):
     print(quanzhong_dau_sql)
     quanzhong_dau_df = spark.sql(quanzhong_dau_sql)
     quanzhong_dau_df.createOrReplaceTempView("quanzhong_dau_view")
-    # quanzhong_dau_df.show(1)
-    # sql_res = quanzhong_dau_df.collect()
+    quanzhong_dau_df.show(1)
+    sql_res = quanzhong_dau_df.collect()
+    for res in sql_res:
+        print(res)
 
     # DAU
     DAU_sql = """
@@ -164,8 +166,11 @@ for t in range(1, task_days):
     print(DAU_sql)
     dau_df = spark.sql(DAU_sql)
     dau_df.createOrReplaceTempView("dau_view")
-    # dau_df.show(1)
-    # sql_res = dau_df.collect()
+    dau_df.show(1)
+    sql_res = dau_df.collect()
+    for res in sql_res:
+        print(res)
+
     # CPT日均点击
     cpc_daily_click_sql = r"""
 SELECT partition_date,count(1) as pv
@@ -183,8 +188,10 @@ group BY partition_date
     print(cpc_daily_click_sql)
     cpc_daily_click_df = spark.sql(cpc_daily_click_sql)
     cpc_daily_click_df.createOrReplaceTempView("cpc_daily_click")
-    # cpc_daily_click_df.show(1)
-    # sql_res = cpc_daily_click_df.collect()
+    cpc_daily_click_df.show(1)
+    sql_res = cpc_daily_click_df.collect()
+    for res in sql_res:
+        print(res)
 
 
     # 商详页PV
@@ -256,8 +263,10 @@ group BY partition_date
     print(bus_detail_sql)
     bus_detail_df = spark.sql(bus_detail_sql)
     bus_detail_df.createOrReplaceTempView("bus_detail")
-    # bus_detail_df.show(1)
-    # sql_res = bus_detail_df.collect()
+    bus_detail_df.show(1)
+    sql_res = bus_detail_df.collect()
+    for res in sql_res:
+        print(res)
 
 
     # --cpc当日预算(有效口径)
@@ -316,8 +325,10 @@ GROUP BY day_id
     print(cpc_budget_sql)
     cpc_budget_df = spark.sql(cpc_budget_sql)
     cpc_budget_df.createOrReplaceTempView("cpc_budget")
-    # cpc_budget_df.show(1)
-    # sql_res = cpc_budget_df.collect()
+    cpc_budget_df.show(1)
+    sql_res = cpc_budget_df.collect()
+    for res in sql_res:
+        print(res)
 
     # cpc收入、广告总消耗
     cpc_income_sql = r"""
@@ -347,24 +358,27 @@ group by partition_day
     print(cpc_income_sql)
     cpc_income_df = spark.sql(cpc_income_sql)
     cpc_income_df.createOrReplaceTempView("cpc_income")
-    # cpc_income_df.show(1)
-    # sql_res = cpc_income_df.collect()
-
-    out_put_sql = """
-    SELECT bus_detail.referrer_search_welfare_pv / dau_view.dau as pv_div_dau,
-     bus_detail.referrer_search_welfare_pv / quanzhong_dau_view.quanzhong_dau as pv_div_quanzhong_dau,
-     (cpc_income.cpt_click_num + cpc_income.cpc_click_num) / bus_detail.referrer_search_welfare_pv as ad_flow_rat,
-     cpc_income.cpc_proportion_expend_amount/cpc_budget.budget as budget_consumption_rate,
-     cpc_income.cpc_proportion_expend_recharge_amount/cpc_income.cpc_click_num as cpc_item_pricing,
-     cpc_income.tol_proportion_expend_amount as tol_proportion_expend_amount
-    """
-    out_df = spark.sql(out_put_sql)
-    # out_df.createOrReplaceTempView("out_df")
-    out_df.show(1)
-    sql_res = out_df.collect()
+    cpc_income_df.show(1)
+    sql_res = cpc_income_df.collect()
     for res in sql_res:
         print(res)
 
+    #
+    # out_put_sql = """
+    # select bus_detail.referrer_search_welfare_pv / dau_view.dau as pv_div_dau,
+    #  bus_detail.referrer_search_welfare_pv / quanzhong_dau_view.quanzhong_dau as pv_div_quanzhong_dau,
+    #  (cpc_income.cpt_click_num + cpc_income.cpc_click_num) / bus_detail.referrer_search_welfare_pv as ad_flow_rat,
+    #  cpc_income.cpc_proportion_expend_amount/cpc_budget.budget as budget_consumption_rate,
+    #  cpc_income.cpc_proportion_expend_recharge_amount/cpc_income.cpc_click_num as cpc_item_pricing,
+    #  cpc_income.tol_proportion_expend_amount as tol_proportion_expend_amount
+    # """
+    # out_df = spark.sql(out_put_sql)
+    # # out_df.createOrReplaceTempView("out_df")
+    # out_df.show(1)
+    # sql_res = out_df.collect()
+    # for res in sql_res:
+    #     print(res)
+
 
 #     for active_type in res_dict:
 #             db = pymysql.connect(host='172.16.40.158', port=4000, user='st_user', passwd='aqpuBLYzEV7tML5RPsN1pntUzFy',