新统计需求

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

@@ -76,7 +76,7 @@ object app_list {
       //获取策略命中用户device_id
       val app_list = sc.sql(
         s"""
-           |select distinct(cl_id) as device_id,params['installed_app_info'] as app_list
+           |select distinct(cl_id) as device_id, user_id as user_id, params['installed_app_info'] as app_list
            |from online.tl_hdfs_maidian_view
            |where action="user_installed_all_app_info"
            |and partition_date = '${partition_date}'
@@ -84,8 +84,8 @@ object app_list {
       )
       //app_list.show()
       import sc.implicits._
-      val rdd_df = app_list.rdd.map(x =>(x(0).toString,x(1).toString))
-        .filter(x => x._2.contains("新氧美容")).map(x => x._1).collect().toList.toDF("device_id")
+      val rdd_df = app_list.rdd.map(x =>(x(0).toString,x(1).toString,x(2).toString))
+        .filter(x => x._3.contains("新氧美容")).map(x => (x._1,x._2)).collect().toList.toDF("device_id","user_id")
       rdd_df.show()
       //rdd_df.withColumn("stat_date",addCol(rdd_df("device_id")))
       rdd_df.createOrReplaceTempView("device_id")
@@ -100,7 +100,7 @@ object app_list {
 
       temp.show()
 
-      GmeiConfig.writeToJDBCTable(tempp, "device_id_contain", SaveMode.Append)
+      GmeiConfig.writeToJDBCTable(tempp, "device_id_coincidence", SaveMode.Append)
 
     }