Merge branch 'master' of http://git.wanmeizhensuo.com/ML/ffm-baseline

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

@@ -396,7 +396,7 @@ object EsmmPredData {
            |where tmp1.device_id in (select distinct device_id from data_feed_click where stat_date='${yesteday_have_seq}')
          """.stripMargin
       )
-      raw_data.show()
+//      raw_data.show()
 
 
       val raw_data1 = raw_data.rdd.groupBy(_.getAs[String]("device_city")).map {
@@ -406,7 +406,7 @@ object EsmmPredData {
           val cids = Try(cid_data.toSeq.map(_.getAs[String]("merge_queue").split(",")).flatMap(_.zipWithIndex).sortBy(_._2).map(_._1).distinct.take(500).mkString(",")).getOrElse("")
           (device_id,city_id ,s"$cids")
       }.filter(_._3!="").toDF("device_id","city_id","merge_queue")
-      println("nearby_device_count",raw_data1.count())
+//      println("nearby_device_count",raw_data1.count())
 
       val start= LocalDate.now().minusDays(14).toString
       import sc.implicits._
@@ -443,7 +443,7 @@ object EsmmPredData {
          """.stripMargin
       ).withColumn("label",lit(1))
       raw_data2.createOrReplaceTempView("raw_data2")
-      println("nearby_explode_count",raw_data2.count())
+//      println("nearby_explode_count",raw_data2.count())
 
 
       // native_data
@@ -455,7 +455,7 @@ object EsmmPredData {
            |where a.stat_date='${yesteday_have_seq}' and b.native_queue != ""
          """.stripMargin
       )
-      println("native_device_count",native_data.count())
+//      println("native_device_count",native_data.count())
 
       if (history.take(1).nonEmpty){
         native_data.createOrReplaceTempView("temp")
@@ -479,9 +479,7 @@ object EsmmPredData {
           """.stripMargin
       ).withColumn("label",lit(0))
       native_data1.createOrReplaceTempView("native_data1")
-      println("native_explode_count",native_data1.count())
-
-
+//      println("native_explode_count",native_data1.count())
 
       //union
       val union_data = sc.sql(
@@ -492,7 +490,7 @@ object EsmmPredData {
          """.stripMargin
       )
       union_data.createOrReplaceTempView("raw_data")
-      println("union_count",union_data.count())
+//      println("union_count",union_data.count())
 
 
       //join feat
@@ -508,7 +506,7 @@ object EsmmPredData {
          """.stripMargin
       )
 //      sid_data.show()
-      println(sid_data.count())
+//      println(sid_data.count())
 
       val sid_data_label = sid_data.withColumn("y",lit(0)).withColumn("z",lit(0))
       sid_data_label.createOrReplaceTempView("union_data")
@@ -556,10 +554,29 @@ object EsmmPredData {
       union_data_ccity_name.createOrReplaceTempView("union_data_ccity_name")
       //      union_data_ccity_name.show()
 
+      val jdbcDF = sc.read
+        .format("jdbc")
+        .option("driver", "com.mysql.jdbc.Driver")
+        .option("url", "jdbc:mysql://rdsfewzdmf0jfjp9un8xj.mysql.rds.aliyuncs.com:3306/zhengxing")
+        .option("dbtable", "api_punishment")
+        .option("user", "work")
+        .option("password", "BJQaT9VzDcuPBqkd")
+        .load()
+      jdbcDF.createOrReplaceTempView("api_punishment")
+      val now = LocalDate.now().toString
+      val punish_doctor = sc.sql(
+        s"""
+           |select doctor_id from api_punishment
+           |where end_time > '$now'
+        """.stripMargin).collect().map(x => x(0).toString).distinct
+
+      println("punish_doctor")
+      println(punish_doctor.length)
+
       val union_data_scity_id = sc.sql(
         s"""
            |select a.stat_date,a.device_id,a.ucity_id,a.cid_id,a.label,a.diary_service_id,a.y,a.z,a.clevel1_id,a.slevel1_id,a.ccity_name,
-           |  d.city_id as scity_id
+           |  d.city_id as scity_id,b.doctor_id,c.hospital_id
            |from union_data_ccity_name a
            |left join online.tl_meigou_service_view b on a.diary_service_id=b.id
            |left join online.tl_hdfs_doctor_view c on b.doctor_id=c.id
@@ -567,20 +584,22 @@ object EsmmPredData {
            |where b.partition_date='${yesteday}'
            |and c.partition_date='${yesteday}'
            |and d.partition_date='${yesteday}'
+           |and b.doctor_id not in (${punish_doctor.map(x => s"'$x'").mkString(",")})
          """.stripMargin
       )
+
       union_data_scity_id.createOrReplaceTempView("union_data_scity_id")
 
       val union_data_scity_id2 = sc.sql(
         s"""
            |select device_id,cid_id,first(stat_date) stat_date,first(ucity_id) ucity_id,label,first(diary_service_id)diary_service_id,first(y) y,
-           |first(z) z,first(clevel1_id) clevel1_id,first(slevel1_id) slevel1_id,first(ccity_name) ccity_name,first(scity_id) scity_id
+           |first(z) z,first(clevel1_id) clevel1_id,first(slevel1_id) slevel1_id,first(ccity_name) ccity_name,
+           |first(scity_id) scity_id,first(hospital_id) hospital_id
            |from union_data_scity_id
            |group by device_id,cid_id,label
          """.stripMargin
       )
 
-
       //      union_data_scity_id.createOrReplaceTempView("union_data_scity_id")
 //      println(union_data_scity_id2.count())
       union_data_scity_id2.persist()

tensnsorflow/es/feature.py

@@ -37,11 +37,11 @@ def get_data():
     validate_date = con_sql(db, sql)[0].values.tolist()[0]
     print("validate_date:" + validate_date)
     temp = datetime.datetime.strptime(validate_date, "%Y-%m-%d")
-    start = (temp - datetime.timedelta(days=300)).strftime("%Y-%m-%d")
+    start = (temp - datetime.timedelta(days=30)).strftime("%Y-%m-%d")
     print(start)
     db = pymysql.connect(host='10.66.157.22', port=4000, user='root', passwd='3SYz54LS9#^9sBvC', db='jerry_test')
-    sql = "select e.y,e.z,e.stat_date,e.ucity_id,feat.level2_ids,e.ccity_name," \
-          "u.device_type,u.manufacturer,u.channel,c.top,e.device_id,cut.time,dl.app_list " \
+    sql = "select e.y,e.z,e.stat_date,e.ucity_id,feat.level2_ids,e.ccity_name,u.device_type,u.manufacturer," \
+          "u.channel,c.top,e.device_id,cut.time,dl.app_list,e.diary_service_id,feat.level3_ids " \
           "from {} e left join user_feature u on e.device_id = u.device_id " \
           "left join cid_type_top c on e.device_id = c.device_id " \
           "left join cid_time_cut cut on e.cid_id = cut.cid " \
@@ -52,31 +52,31 @@ def get_data():
     # print(df.shape)
     df = df.rename(columns={0: "y", 1: "z", 2: "stat_date", 3: "ucity_id", 4: "clevel2_id", 5: "ccity_name",
                             6: "device_type", 7: "manufacturer", 8: "channel", 9: "top", 10: "device_id",
-                            11: "time",12:"app_list"})
+                            11: "time",12:"app_list",13:"service_id",14:"level3_ids"})
     print("esmm data ok")
+    print(df.shape)
     # print(df.head(2)
+    service_id = tuple(df["service_id"].unique())
+    db = pymysql.connect(host='rdsfewzdmf0jfjp9un8xj.mysql.rds.aliyuncs.com', port=3306, user='work', passwd='BJQaT9VzDcuPBqkd', db='zhengxing')
+    sql = "select s.id,d.hospital_id from api_service s left join api_doctor d on s.doctor_id = d.id where s.id in {}".format(service_id)
+    hospital = con_sql(db, sql)
+    hospital = hospital.rename(columns={0: "service_id", 1: "hospital_id"})
+    df = pd.merge(df, hospital, on='service_id', how='left')
+
     print("before")
     print(df.shape)
     print("after")
     df = df.drop_duplicates()
     df = df.drop_duplicates(["ucity_id", "clevel2_id", "ccity_name", "device_type", "manufacturer",
-                             "channel", "top", "time", "stat_date","app_list"])
+                             "channel", "top", "time", "stat_date","app_list","hospital_id","level3_ids"])
 
     app_list_number,app_list_map = multi_hot(df,"app_list",1)
     level2_number,level2_map = multi_hot(df,"clevel2_id",1+app_list_number)
-    # df["app_list"] = df["app_list"].fillna("lost_na")
-    # app_list_value = [i.split(",") for i in df["app_list"].unique()]
-    # app_list_unique = []
-    # for i in app_list_value:
-    #     app_list_unique.extend(i)
-    # app_list_unique = list(set(app_list_unique))
-    # app_list_map = dict(zip(app_list_unique, list(range(1, len(app_list_unique) + 1))))
-    # df["app_list"] = df["app_list"].apply(app_list_func,args=(app_list_map,))
-
+    level3_number,level3_ids = multi_hot(df, "hospital_id", 1 + app_list_number + level2_number)
 
     unique_values = []
     features = ["ucity_id", "ccity_name", "device_type", "manufacturer",
-                "channel", "top", "time", "stat_date"]
+                "channel", "top", "time", "stat_date","hospital_id"]
     for i in features:
         df[i] = df[i].astype("str")
         df[i] = df[i].fillna("lost")
@@ -84,14 +84,14 @@ def get_data():
         df[i] = df[i] + i
         unique_values.extend(list(df[i].unique()))
 
-    temp = list(range(1+app_list_number+level2_number, 1 + app_list_number+level2_number + len(unique_values)))
+    temp = list(range(1+app_list_number+level2_number + level3_number, 1 + app_list_number+level2_number + level3_number + len(unique_values)))
     value_map = dict(zip(unique_values,temp))
 
     df = df.drop("device_id", axis=1)
     train = df[df["stat_date"] != validate_date+"stat_date"]
     test = df[df["stat_date"] == validate_date+"stat_date"]
     for i in ["ucity_id", "ccity_name", "device_type", "manufacturer",
-                "channel", "top", "time", "stat_date"]:
+                "channel", "top", "time", "stat_date","hospital_id"]:
         train[i] = train[i].map(value_map)
         test[i] = test[i].map(value_map)
 
@@ -193,5 +193,5 @@ if __name__ == '__main__':
     train_data_set = "esmm_train_data"
     path = "/data/esmm/"
     date,value,app_list,level2 = get_data()
-    get_predict(date, value,app_list,level2)
+    # get_predict(date, value,app_list,level2)