change test file

eda/esmm/Model_pipline/feature_engineering.py

@@ -296,8 +296,7 @@ def get_predict(date,value_map,app_list_map,leve2_map,leve3_map):
           "left join jerry_test.sixin_tag sixin on e.device_id = sixin.device_id " \
           "left join jerry_test.cart_tag cart on e.device_id = cart.device_id " \
           "left join jerry_test.knowledge k on feat.level2 = k.level2_id " \
-          "left join jerry_test.search_doris doris on e.device_id = doris.device_id and e.stat_date = doris.get_date " \
-          "limit 600000"
+          "left join jerry_test.search_doris doris on e.device_id = doris.device_id and e.stat_date = doris.get_date"
 
     features = ["ucity_id", "ccity_name", "device_type", "manufacturer",
                 "channel", "top", "time", "hospital_id",
@@ -334,7 +333,7 @@ def get_predict(date,value_map,app_list_map,leve2_map,leve3_map):
 
 
     rdd.persist(storageLevel= StorageLevel.MEMORY_ONLY_SER)
-    println(rdd.count())
+    print(rdd.count())
 
     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")