adding warnings for transformation functions in external feature grou…

…p and updating logger message
logicalclocks · Oct 25, 2024 · ebeba91 · ebeba91
1 parent 45fa5bb
commit ebeba91
Show file tree

Hide file tree

Showing 2 changed files with 13 additions and 8 deletions.
diff --git a/python/hsfs/core/feature_group_engine.py b/python/hsfs/core/feature_group_engine.py
@@ -82,13 +82,18 @@ def save(
         )
 
         # Currently on-demand transformation functions not supported in external feature groups.
-        if (
-            not isinstance(feature_group, fg.ExternalFeatureGroup)
-            and feature_group.transformation_functions
-        ):
-            feature_dataframe = engine.get_instance()._apply_transformation_function(
-                feature_group.transformation_functions, feature_dataframe
-            )
+        if feature_group.transformation_functions:
+            if not isinstance(feature_group, fg.ExternalFeatureGroup):
+                feature_dataframe = (
+                    engine.get_instance()._apply_transformation_function(
+                        feature_group.transformation_functions, feature_dataframe
+                    )
+                )
+            else:
+                warnings.warn(
+                    "On-Demand features were not created because On-Demand Transformations are not supported for External Feature Groups.",
+                    stacklevel=1,
+                )
 
         util.validate_embedding_feature_type(
             feature_group.embedding_index, dataframe_features

diff --git a/python/hsfs/core/vector_server.py b/python/hsfs/core/vector_server.py
@@ -1326,7 +1326,7 @@ def identify_missing_features_pre_fetch(
             if self._on_demand_feature_names and len(self._on_demand_feature_names) > 0:
                 # Remove on-demand features from validation check as they would be computed.
                 _logger.debug(
-                    "_on_demand_feature_names for pre-fetch missing : %s",
+                    "Appending on_demand_feature_names to passed_feature_names for pre-fetch missing : %s",
                     vector_db_features,
                 )
                 passed_feature_names = passed_feature_names.union(