service model 优化

spark/featureEng.py

@@ -881,7 +881,8 @@ if __name__ == '__main__':
     # model columns
     print("model columns to redis...")
     model_columns = user_columns + item_columns
-    featureColumnsToRedis(model_columns)
+    not_model_columns = [col for col in model_columns if not col.endswith("_number")]
+    featureColumnsToRedis(not_model_columns)
 
     print("数据字典save...")
     print("dataVocab:", str(dataVocab.keys()))

train/train_service.py

@@ -83,10 +83,10 @@ def getTrainColumns(train_columns,data_vocab):
             emb_columns.append(col)
             inputs[feature] = tf.keras.layers.Input(name=feature, shape=(), dtype='string')
 
-        elif feature.endswith("_number"):
-            col = tf.feature_column.numeric_column(feature)
-            number_columns.append(col)
-            inputs[feature] = tf.keras.layers.Input(name=feature, shape=(), dtype='float32')
+        # elif feature.endswith("_number"):
+        #     col = tf.feature_column.numeric_column(feature)
+        #     number_columns.append(col)
+        #     inputs[feature] = tf.keras.layers.Input(name=feature, shape=(), dtype='float32')
 
     return emb_columns,number_columns,inputs