change test file

tensnsorflow/feature_test.py

@@ -314,8 +314,8 @@ def get_predict(date,value_map,app_list_map,leve2_map,leve3_map):
 
     rdd.persist(storageLevel= StorageLevel.MEMORY_ONLY_SER)
 
-    native_pre = spark.createDataFrame(rdd.filter(lambda x:x[0] == 0).map(lambda x:(x[3],x[4],x[5])))\
-        .toDF("city","uid","cid_id")
+    native_pre = spark.createDataFrame(rdd.filter(lambda x:x[0] == 0).map(lambda x:(x[3],x[4],x[5],x[17])))\
+        .toDF("city","uid","cid_id","number")
     print("native csv")
     native_pre.toPandas().to_csv(local_path+"native.csv", header=True)
     spark.createDataFrame(rdd.filter(lambda x: x[0] == 0)
@@ -327,8 +327,8 @@ def get_predict(date,value_map,app_list_map,leve2_map,leve3_map):
     h = time.time()
     print((h-f)/60)
 
-    nearby_pre = spark.createDataFrame(rdd.filter(lambda x: x[0] == 1).map(lambda x: (x[3], x[4], x[5]))) \
-        .toDF("city", "uid", "cid_id")
+    nearby_pre = spark.createDataFrame(rdd.filter(lambda x: x[0] == 1).map(lambda x: (x[3], x[4], x[5],x[17]))) \
+        .toDF("city", "uid", "cid_id","number")
     print("nearby csv")
     nearby_pre.toPandas().to_csv(local_path + "nearby.csv", header=True)