change test file

tensnsorflow/multi.py

@@ -17,7 +17,6 @@ def app_list_func(x,l):
         else:
             e.append(0)
     return e
-    # return ",".join([str(j) for j in e])
 
 
 def multi_hot(df,column,n):
@@ -32,7 +31,7 @@ def multi_hot(df,column,n):
     return number,app_list_map
 
 
-def feature_engineer():
+def feature():
     db = pymysql.connect(host='172.16.40.158', port=4000, user='root', passwd='3SYz54LS9#^9sBvC', db='jerry_test')
     sql = "select max(stat_date) from esmm_train_data"
     validate_date = con_sql(db, sql)[0].values.tolist()[0]
@@ -99,9 +98,9 @@ def get_predict(date,value_map,app_list_map):
     native_pre = spark.createDataFrame(rdd.filter(lambda x:x[4] == 0).map(lambda x:(x[1],x[2],x[3])))\
         .toDF("city","uid","cid_id")
     print("native")
-    # native_pre.toPandas().to_csv(local_path+"native.csv", header=True)
-
-    native_pre.coalesce(1).write.format('com.databricks.spark.csv').save(path+"hello.csv",header = 'true')
+    native_pre.toPandas().to_csv(local_path+"native.csv", header=True)
+# TODO 写成csv文件改成下面这样
+    # native_pre.coalesce(1).write.format('com.databricks.spark.csv').save(path+"native/",header = 'true')
 
     # 预测的tfrecord必须写成一个文件，这样可以摆保证顺序
     spark.createDataFrame(rdd.filter(lambda x: x[4] == 0).map(lambda x: (x[0],x[5],x[6],x[7]))) \
@@ -145,7 +144,7 @@ if __name__ == '__main__':
     path = "hdfs:///strategy/esmm/"
     local_path = "/home/gmuser/esmm/"
 
-    validate_date, value_map, app_list_map = feature_engineer()
+    validate_date, value_map, app_list_map = feature()
     get_predict(validate_date, value_map, app_list_map)
 
     # df = spark.read.format("tfrecords").option("recordType", "Example").load("/strategy/va.tfrecord")