统计like项目

eda/feededa/src/main/scala/com/gmei/temp_analysis.scala

@@ -559,7 +559,7 @@ object alpha_ctr {
 
       val click_count_recommend = sc.sql(
         s"""
-           |select '${stat_date}' as stat_date,count(*) as count_recommend
+           |select '${stat_date}' as stat_date,count(*) as click_count_recommend
            |from bl.bl_alpha_et_mg_maidianlog_inc_d
            |where params['tab_name']='recommend'
            |and params['page_name']='home'
@@ -571,7 +571,7 @@ object alpha_ctr {
 
       val click_count_focus = sc.sql(
         s"""
-           |select '${stat_date}' as stat_date,count(*) as count_focus
+           |select '${stat_date}' as stat_date,count(*) as click_count_focus
            |from bl.bl_alpha_et_mg_maidianlog_inc_d
            |where params['tab_name']='focus'
            |and params['page_name']='home'
@@ -594,7 +594,7 @@ object alpha_ctr {
 
       }
 
-      sc.sql(
+      val expoure_cards=sc.sql(
         s"""
            |select params['exposure_cards'] as exposure_cards
            |from bl.bl_alpha_et_mg_maidianlog_inc_d
@@ -603,18 +603,31 @@ object alpha_ctr {
            |and type = 'page_precise_exposure'
            |and partition_day='${partition_date}'
        """.stripMargin
-      ).rdd.map(row => row(0).toString).map(row=>parse_json(row)).toDF().show()
-        /*.rdd
-        .map(row =>{
-        val s = row.getAs[List[String]]("exposure_cards")
-        (stat_date,s)
-      })
-        //.reduceByKey((x,y) => x + y)
-        .toDF("stat_date","count").show()
-*/
+      )
+      val a =expoure_cards.rdd.map(row => row(0).toString).map(row=>{
+        val lenth=parse_json(row)
+        (stat_date,lenth)
+      }).reduceByKey((x,y) => x + y).toDF("stat_date","exposure_count_recommend")
 
+      val expoure_cards2=sc.sql(
+        s"""
+           |select params['exposure_cards'] as exposure_cards
+           |from bl.bl_alpha_et_mg_maidianlog_inc_d
+           |where params['tab_name'] = 'focus'
+           |and params['page_name'] = 'home'
+           |and type = 'page_precise_exposure'
+           |and partition_day='${partition_date}'
+       """.stripMargin
+      )
+      val b =expoure_cards2.rdd.map(row => row(0).toString).map(row=>{
+        val lenth=parse_json(row)
+        (stat_date,lenth)
+      }).reduceByKey((x,y) => x + y).toDF("stat_date","exposure_count_focus")
 
 
+      val result=click_count_recommend.join(click_count_focus,"stat_date")
+        .join(a,"stat_date")
+        .join(b,"stat_date")