chore: Remove join_keys attribute (feast-dev#3159)

Remove `join_keys` attribute

Signed-off-by: Felix Wang <[email protected]>

Signed-off-by: Felix Wang <[email protected]>

Author: felixwang9817

sdk/python/feast/entity.py

@@ -33,9 +33,6 @@ class Entity:
     Attributes:
         name: The unique name of the entity.
         value_type: The type of the entity, such as string or float.
-        join_keys: A list of properties that uniquely identifies different entities within the
-            collection. This currently only supports a list of size one, but is intended to
-            eventually support multiple join keys.
         join_key: A property that uniquely identifies different entities within the
             collection. The join_key property is typically used for joining entities
             with their associated features. If not specified, defaults to the name.
@@ -48,7 +45,6 @@ class Entity:
 
     name: str
     value_type: ValueType
-    join_keys: List[str]
     join_key: str
     description: str
     tags: Dict[str, str]
@@ -84,21 +80,17 @@ def __init__(
         self.name = name
         self.value_type = ValueType.UNKNOWN
 
-        # For now, both the `join_key` and `join_keys` attributes are set correctly,
-        # so both are usable.
-        # TODO(felixwang9817): Fully remove the usage of `join_key` throughout the codebase,
-        # at which point the `join_key` attribute no longer needs to be set.
         if join_keys and len(join_keys) > 1:
+            # TODO(felixwang9817): When multiple join keys are supported, add a `join_keys` attribute
+            # and deprecate the `join_key` attribute.
             raise ValueError(
-                "An entity may only have single join key. "
+                "An entity may only have a single join key. "
                 "Multiple join keys will be supported in the future."
             )
         elif join_keys and len(join_keys) == 1:
-            self.join_keys = join_keys
             self.join_key = join_keys[0]
         else:
             self.join_key = self.name
-            self.join_keys = [self.join_key]
 
         self.description = description
         self.tags = tags if tags is not None else {}

sdk/python/feast/feature_view.py

@@ -155,10 +155,10 @@ def __init__(
         features: List[Field] = []
         self.entity_columns = []
 
-        join_keys = []
+        join_keys: List[str] = []
         if entities:
             for entity in entities:
-                join_keys += entity.join_keys
+                join_keys.append(entity.join_key)
 
         for field in self.schema:
             if field.name in join_keys:

sdk/python/feast/inference.py

@@ -115,15 +115,11 @@ def update_feature_views_with_inferred_features_and_entities(
         config: The config for the current feature store.
     """
     entity_name_to_entity_map = {e.name: e for e in entities}
-    entity_name_to_join_keys_map = {e.name: e.join_keys for e in entities}
+    entity_name_to_join_key_map = {e.name: e.join_key for e in entities}
 
     for fv in fvs:
         join_keys = set(
-            [
-                join_key
-                for entity_name in fv.entities
-                for join_key in entity_name_to_join_keys_map[entity_name]
-            ]
+            [entity_name_to_join_key_map[entity_name] for entity_name in fv.entities]
         )
 
         # Fields whose names match a join key are considered to be entity columns; all
@@ -164,13 +160,7 @@ def update_feature_views_with_inferred_features_and_entities(
             fv.entity_columns.append(Field(name=DUMMY_ENTITY_ID, dtype=String))
 
         # Run inference for entity columns if there are fewer entity fields than expected.
-        num_expected_join_keys = sum(
-            [
-                len(entity_name_to_join_keys_map[entity_name])
-                for entity_name in fv.entities
-            ]
-        )
-        run_inference_for_entities = len(fv.entity_columns) < num_expected_join_keys
+        run_inference_for_entities = len(fv.entity_columns) < len(join_keys)
 
         # Run inference for feature columns if there are no feature fields.
         run_inference_for_features = len(fv.features) == 0