push codes

pm/daily_userpost/report/data_by_day.sql

-select *
-from
-(
-    SELECT partition_day as `日期`
-            ,count(post_id) as `帖子数量`
-            ,nvl(concat(round(sum(click_pv_1)/sum(exp_pv_1)*100,2),'%'),0) as `前1日ctr`
-            ,nvl(sum(exp_pv_1),0) as `前1日曝光`
-            ,nvl(round(avg(avg_page_stay_1),2),0) as `前1日平均阅读时长(s)`
-            ,nvl(concat(round(sum(click_pv_3)/sum(exp_pv_3)*100,2),'%'),0) as `前3日ctr`
-            ,nvl(sum(exp_pv_3),0) as `前3日曝光`
-            ,nvl(round(avg(avg_page_stay_3),2),0) as `前3日平均阅读时长(s)`
-            ,nvl(concat(round(sum(click_pv_10)/sum(exp_pv_10)*100,2),'%'),0) as `前10日ctr`
-            ,nvl(sum(exp_pv_10),0) as `前10日曝光`
-            ,nvl(round(avg(avg_page_stay_10),2),0) as `前10日平均阅读时长(s)`
-    FROM pm.tl_pm_userpost_d
-    where partition_day>='20200911' and partition_day<='20200922'
-    group by partition_day
-
-    union all
-
-    SELECT partition_day as `日期`
-            ,count(post_id) as `帖子数量`
-            ,nvl(concat(round(sum(click_pv_1)/sum(exp_pv_1)*100,2),'%'),0) as `前1日ctr`
-            ,nvl(sum(exp_pv_1),0) as `前1日曝光`
-            ,nvl(round(avg(avg_page_stay_1),2),0) as `前1日平均阅读时长(s)`
-            ,nvl(concat(round(sum(click_pv_3)/sum(exp_pv_3)*100,2),'%'),0) as `前3日ctr`
-            ,nvl(sum(exp_pv_3),0) as `前3日曝光`
-            ,nvl(round(avg(avg_page_stay_3),2),0) as `前3日平均阅读时长(s)`
-            ,nvl(concat(round(sum(click_pv_10)/sum(exp_pv_10)*100,2),'%'),0) as `前10日ctr`
-            ,nvl(sum(exp_pv_10),0) as `前10日曝光`
-            ,nvl(round(avg(avg_page_stay_10),2),0) as `前10日平均阅读时长(s)`
-    FROM pm.tl_pm_userpost_d_v2
-    where partition_day>='20200923'
-    group by partition_day
-)a
+SELECT partition_day as `日期`
+    ,count(post_id) as `帖子数量`
+    ,nvl(sum(exp_pv_1),0) as `前1日曝光`
+    ,nvl(concat(round(sum(click_pv_1)/sum(exp_pv_1)*100,2),'%'),0) as `前1日ctr`
+    ,nvl(concat(round(sum(page_pv_20s_1)/sum(exp_pv_1)*100,2),'%'),0) as `日优秀浏览点击ctr`
+    ,nvl(round(avg(avg_page_stay_1),2),0) as `前1日平均阅读时长(s)`
+    ,nvl(sum(exp_pv),0) as `历史曝光`
+    ,nvl(concat(round(sum(click_pv)/sum(exp_pv)*100,2),'%'),0) as `历史ctr`
+    ,nvl(concat(round(sum(page_pv_20s)/sum(exp_pv)*100,2),'%'),0) as `历史优秀浏览点击ctr`
+    ,nvl(round(avg(avg_page_stay),2),0) as `历史平均阅读时长(s)`
+FROM pm.tl_pm_userpost_d_v2
+where partition_day>='20200915'
+group by partition_day
 order by `日期`
\ No newline at end of file

pm/sign_daily/etl/sign_daily.sql

@@ -7,7 +7,7 @@ set hive.auto.convert.join=true;
 SET mapred.reduce.tasks=20;
 SET role admin;
 
---线索日报
+
 ADD JAR hdfs:///user/hive/share/lib/udf/hive-udf-1.0-SNAPSHOT.jar;
 CREATE TEMPORARY FUNCTION convup AS 'com.gmei.hive.common.udf.UDFConvUpgrade';
 CREATE TEMPORARY FUNCTION setencryption AS 'com.gmei.hive.common.udf.UDFStringSetEncryption';

pm/sign_daily/report/sign_daily.sql

@@ -4,6 +4,6 @@ SELECT day_id as `日期`
         ,round((sum(CASE WHEN device_os_type = 'android' AND user_type='非首日签到用户' THEN wel_pv END)/sum(CASE WHEN device_os_type = 'android' and user_type='非首日签到用户' THEN active_num END))/(sum(CASE WHEN device_os_type = 'android' THEN wel_pv END)/sum(CASE WHEN device_os_type = 'android' THEN active_num END)),2) as `单个android非首日签到贡献商品核心页PV/单个android老贡献商品核心页PV`
         ,round((sum(CASE WHEN device_os_type = 'android' AND user_type='非首日签到用户' THEN clue_pv END)/sum(CASE WHEN device_os_type = 'android' AND user_type='非首日签到用户' THEN active_num END))/(sum(CASE WHEN device_os_type = 'android'  THEN clue_pv END)/sum(CASE WHEN device_os_type = 'android' THEN active_num END)),2) as `单个android非首日签到贡献有效线索人次/单个android老贡献有效线索人次`
 FROM pm.tl_pm_sign_deepaction_d
-where partition_day in ('20200831','20200930','20201031','20201130','20201231',regexp_replace(date_sub(current_date,1),'-',''))
+where partition_day in ('20200731','20200831','20200930','20201031','20201130','20201231',regexp_replace(date_sub(current_date,1),'-',''))
 group by day_id
 order by `日期`