Historical field mappings

CONTRIBUTING.md

@@ -50,7 +50,7 @@ Setting up your development environment for Feast Python SDK / CLI:
 3. _Recommended:_ Create a virtual environment to isolate development dependencies to be installed
 ```sh
 # create & activate a virtual environment
-python -v venv venv/
+python -m venv venv/
 source venv/bin/activate
 ```
 

sdk/python/feast/driver_test_data.py

@@ -264,3 +264,29 @@ def create_global_daily_stats_df(start_date, end_date) -> pd.DataFrame:
     # TODO: Remove created timestamp in order to test whether its really optional
     df_daily["created"] = pd.to_datetime(pd.Timestamp.now(tz=None).round("ms"))
     return df_daily
+
+
+def create_field_mapping_df(start_date, end_date) -> pd.DataFrame:
+    """
+    Example df generated by this function:
+    | event_timestamp  | column_name | created          |
+    |------------------+-------------+------------------|
+    | 2021-03-17 19:00 | 99          | 2021-03-24 19:38 |
+    | 2021-03-17 19:00 | 22          | 2021-03-24 19:38 |
+    | 2021-03-17 19:00 | 7           | 2021-03-24 19:38 |
+    | 2021-03-17 19:00 | 45          | 2021-03-24 19:38 |
+    """
+    size = 10
+    df = pd.DataFrame()
+    df["column_name"] = np.random.randint(1, 100, size=size).astype(np.int32)
+    df[DEFAULT_ENTITY_DF_EVENT_TIMESTAMP_COL] = [
+        _convert_event_timestamp(
+            pd.Timestamp(dt, unit="ms", tz="UTC").round("ms"),
+            EventTimestampType(idx % 4),
+        )
+        for idx, dt in enumerate(
+            pd.date_range(start=start_date, end=end_date, periods=size)
+        )
+    ]
+    df["created"] = pd.to_datetime(pd.Timestamp.now(tz=None).round("ms"))
+    return df

sdk/python/feast/infra/offline_stores/bigquery.py

@@ -598,7 +598,7 @@ def _get_bigquery_client(project: Optional[str] = None, location: Optional[str]
         {{ featureview.created_timestamp_column ~ ' as created_timestamp,' if featureview.created_timestamp_column else '' }}
         {{ featureview.entity_selections | join(', ')}}{% if featureview.entity_selections %},{% else %}{% endif %}
         {% for feature in featureview.features %}
-            {{ feature }} as {% if full_feature_names %}{{ featureview.name }}__{{feature}}{% else %}{{ feature }}{% endif %}{% if loop.last %}{% else %}, {% endif %}
+            {{ feature }} as {% if full_feature_names %}{{ featureview.name }}__{{featureview.field_mapping.get(feature, feature)}}{% else %}{{ featureview.field_mapping.get(feature, feature) }}{% endif %}{% if loop.last %}{% else %}, {% endif %}
         {% endfor %}
     FROM {{ featureview.table_subquery }}
     WHERE {{ featureview.event_timestamp_column }} <= '{{ featureview.max_event_timestamp }}'
@@ -699,7 +699,7 @@ def _get_bigquery_client(project: Optional[str] = None, location: Optional[str]
     SELECT
         {{featureview.name}}__entity_row_unique_id
         {% for feature in featureview.features %}
-            ,{% if full_feature_names %}{{ featureview.name }}__{{feature}}{% else %}{{ feature }}{% endif %}
+            ,{% if full_feature_names %}{{ featureview.name }}__{{featureview.field_mapping.get(feature, feature)}}{% else %}{{ featureview.field_mapping.get(feature, feature) }}{% endif %}
         {% endfor %}
     FROM {{ featureview.name }}__cleaned
 ) USING ({{featureview.name}}__entity_row_unique_id)

sdk/python/feast/infra/offline_stores/offline_utils.py

@@ -85,6 +85,7 @@ class FeatureViewQueryContext:
     ttl: int
     entities: List[str]
     features: List[str]  # feature reference format
+    field_mapping: Dict[str, str]
     event_timestamp_column: str
     created_timestamp_column: Optional[str]
     table_subquery: str
@@ -144,7 +145,10 @@ def get_feature_view_query_context(
             name=feature_view.projection.name_to_use(),
             ttl=ttl_seconds,
             entities=join_keys,
-            features=features,
+            features=[
+                reverse_field_mapping.get(feature, feature) for feature in features
+            ],
+            field_mapping=feature_view.input.field_mapping,
             event_timestamp_column=reverse_field_mapping.get(
                 event_timestamp_column, event_timestamp_column
             ),
@@ -175,7 +179,11 @@ def build_point_in_time_query(
     final_output_feature_names = list(entity_df_columns)
     final_output_feature_names.extend(
         [
-            (f"{fv.name}__{feature}" if full_feature_names else feature)
+            (
+                f"{fv.name}__{fv.field_mapping.get(feature, feature)}"
+                if full_feature_names
+                else fv.field_mapping.get(feature, feature)
+            )
             for fv in feature_view_query_contexts
             for feature in fv.features
         ]

sdk/python/feast/infra/offline_stores/redshift.py

@@ -563,7 +563,7 @@ def _get_entity_df_event_timestamp_range(
         {{ featureview.created_timestamp_column ~ ' as created_timestamp,' if featureview.created_timestamp_column else '' }}
         {{ featureview.entity_selections | join(', ')}}{% if featureview.entity_selections %},{% else %}{% endif %}
         {% for feature in featureview.features %}
-            {{ feature }} as {% if full_feature_names %}{{ featureview.name }}__{{feature}}{% else %}{{ feature }}{% endif %}{% if loop.last %}{% else %}, {% endif %}
+            {{ feature }} as {% if full_feature_names %}{{ featureview.name }}__{{featureview.field_mapping.get(feature, feature)}}{% else %}{{ featureview.field_mapping.get(feature, feature) }}{% endif %}{% if loop.last %}{% else %}, {% endif %}
         {% endfor %}
     FROM {{ featureview.table_subquery }}
     WHERE {{ featureview.event_timestamp_column }} <= '{{ featureview.max_event_timestamp }}'
@@ -664,7 +664,7 @@ def _get_entity_df_event_timestamp_range(
     SELECT
         {{featureview.name}}__entity_row_unique_id
         {% for feature in featureview.features %}
-            ,{% if full_feature_names %}{{ featureview.name }}__{{feature}}{% else %}{{ feature }}{% endif %}
+            ,{% if full_feature_names %}{{ featureview.name }}__{{featureview.field_mapping.get(feature, feature)}}{% else %}{{ featureview.field_mapping.get(feature, feature) }}{% endif %}
         {% endfor %}
     FROM {{ featureview.name }}__cleaned
 ) USING ({{featureview.name}}__entity_row_unique_id)

sdk/python/setup.py

@@ -132,7 +132,7 @@
     + AWS_REQUIRED
 )
 
-DEV_REQUIRED = ["mypy-protobuf==1.*", "grpcio-testing==1.*"] + CI_REQUIRED
+DEV_REQUIRED = ["mypy-protobuf>=1.*", "grpcio-testing==1.*"] + CI_REQUIRED
 
 # Get git repo root directory
 repo_root = str(pathlib.Path(__file__).resolve().parent.parent.parent)

sdk/python/tests/integration/feature_repos/repo_configuration.py

@@ -35,6 +35,7 @@
     create_customer_daily_profile_feature_view,
     create_driver_age_request_feature_view,
     create_driver_hourly_stats_feature_view,
+    create_field_mapping_feature_view,
     create_global_stats_feature_view,
     create_location_stats_feature_view,
     create_order_feature_view,
@@ -126,6 +127,7 @@ def construct_universal_datasets(
         order_count=20,
     )
     global_df = driver_test_data.create_global_daily_stats_df(start_time, end_time)
+    field_mapping_df = driver_test_data.create_field_mapping_df(start_time, end_time)
     entity_df = orders_df[
         [
             "customer_id",
@@ -143,6 +145,7 @@ def construct_universal_datasets(
         "location": location_df,
         "orders": orders_df,
         "global": global_df,
+        "field_mapping": field_mapping_df,
         "entity": entity_df,
     }
 
@@ -180,12 +183,20 @@ def construct_universal_data_sources(
         event_timestamp_column="event_timestamp",
         created_timestamp_column="created",
     )
+    field_mapping_ds = data_source_creator.create_data_source(
+        datasets["field_mapping"],
+        destination_name="field_mapping",
+        event_timestamp_column="event_timestamp",
+        created_timestamp_column="created",
+        field_mapping={"column_name": "feature_name"},
+    )
     return {
         "customer": customer_ds,
         "driver": driver_ds,
         "location": location_ds,
         "orders": orders_ds,
         "global": global_ds,
+        "field_mapping": field_mapping_ds,
     }
 
 
@@ -210,6 +221,9 @@ def construct_universal_feature_views(
         "driver_age_request_fv": create_driver_age_request_feature_view(),
         "order": create_order_feature_view(data_sources["orders"]),
         "location": create_location_stats_feature_view(data_sources["location"]),
+        "field_mapping": create_field_mapping_feature_view(
+            data_sources["field_mapping"]
+        ),
     }
 
 

sdk/python/tests/integration/feature_repos/universal/feature_views.py

@@ -217,3 +217,13 @@ def create_location_stats_feature_view(source, infer_features: bool = False):
         ttl=timedelta(days=2),
     )
     return location_stats_feature_view
+
+
+def create_field_mapping_feature_view(source):
+    return FeatureView(
+        name="field_mapping",
+        entities=[],
+        features=[Feature(name="feature_name", dtype=ValueType.INT32)],
+        batch_source=source,
+        ttl=timedelta(days=2),
+    )

sdk/python/tests/integration/offline_store/test_universal_historical_retrieval.py

@@ -82,6 +82,8 @@ def get_expected_training_df(
     location_fv: FeatureView,
     global_df: pd.DataFrame,
     global_fv: FeatureView,
+    field_mapping_df: pd.DataFrame,
+    field_mapping_fv: FeatureView,
     entity_df: pd.DataFrame,
     event_timestamp: str,
     full_feature_names: bool = False,
@@ -102,6 +104,10 @@ def get_expected_training_df(
     global_records = convert_timestamp_records_to_utc(
         global_df.to_dict("records"), global_fv.batch_source.event_timestamp_column
     )
+    field_mapping_records = convert_timestamp_records_to_utc(
+        field_mapping_df.to_dict("records"),
+        field_mapping_fv.batch_source.event_timestamp_column,
+    )
     entity_rows = convert_timestamp_records_to_utc(
         entity_df.to_dict("records"), event_timestamp
     )
@@ -156,6 +162,13 @@ def get_expected_training_df(
             ts_end=order_record[event_timestamp],
         )
 
+        field_mapping_record = find_asof_record(
+            field_mapping_records,
+            ts_key=field_mapping_fv.batch_source.event_timestamp_column,
+            ts_start=order_record[event_timestamp] - field_mapping_fv.ttl,
+            ts_end=order_record[event_timestamp],
+        )
+
         entity_row.update(
             {
                 (
@@ -197,6 +210,16 @@ def get_expected_training_df(
             }
         )
 
+        # get field_mapping_record by column name, but label by feature name
+        entity_row.update(
+            {
+                (
+                    f"field_mapping__{feature}" if full_feature_names else feature
+                ): field_mapping_record.get(column, None)
+                for (column, feature) in field_mapping_fv.input.field_mapping.items()
+            }
+        )
+
     # Convert records back to pandas dataframe
     expected_df = pd.DataFrame(entity_rows)
 
@@ -213,6 +236,7 @@ def get_expected_training_df(
             "customer_profile__current_balance": "float32",
             "customer_profile__avg_passenger_count": "float32",
             "global_stats__avg_ride_length": "float32",
+            "field_mapping__feature_name": "int32",
         }
     else:
         expected_column_types = {
@@ -221,6 +245,7 @@ def get_expected_training_df(
             "current_balance": "float32",
             "avg_passenger_count": "float32",
             "avg_ride_length": "float32",
+            "feature_name": "int32",
         }
 
     for col, typ in expected_column_types.items():
@@ -311,6 +336,8 @@ def test_historical_features(environment, universal_data_sources, full_feature_n
         feature_views["location"],
         datasets["global"],
         feature_views["global"],
+        datasets["field_mapping"],
+        feature_views["field_mapping"],
         entity_df_with_request_data,
         event_timestamp,
         full_feature_names,
@@ -336,6 +363,7 @@ def test_historical_features(environment, universal_data_sources, full_feature_n
             "global_stats:num_rides",
             "global_stats:avg_ride_length",
             "driver_age:driver_age",
+            "field_mapping:feature_name",
         ],
         full_feature_names=full_feature_names,
     )
@@ -404,6 +432,7 @@ def test_historical_features_with_missing_request_data(
                 "conv_rate_plus_100:conv_rate_plus_val_to_add",
                 "global_stats:num_rides",
                 "global_stats:avg_ride_length",
+                "field_mapping:feature_name",
             ],
             full_feature_names=full_feature_names,
         )
@@ -419,6 +448,7 @@ def test_historical_features_with_missing_request_data(
                 "driver_age:driver_age",
                 "global_stats:num_rides",
                 "global_stats:avg_ride_length",
+                "field_mapping:feature_name",
             ],
             full_feature_names=full_feature_names,
         )
@@ -452,6 +482,7 @@ def test_historical_features_with_entities_from_query(
             "order:order_is_success",
             "global_stats:num_rides",
             "global_stats:avg_ride_length",
+            "field_mapping:feature_name",
         ],
         full_feature_names=full_feature_names,
     )
@@ -477,6 +508,8 @@ def test_historical_features_with_entities_from_query(
         feature_views["location"],
         datasets["global"],
         feature_views["global"],
+        datasets["field_mapping"],
+        feature_views["field_mapping"],
         datasets["entity"],
         event_timestamp,
         full_feature_names,
@@ -538,6 +571,7 @@ def test_historical_features_persisting(
             "order:order_is_success",
             "global_stats:num_rides",
             "global_stats:avg_ride_length",
+            "field_mapping:feature_name",
         ],
         full_feature_names=full_feature_names,
     )
@@ -561,6 +595,8 @@ def test_historical_features_persisting(
         feature_views["location"],
         datasets["global"],
         feature_views["global"],
+        datasets["field_mapping"],
+        feature_views["field_mapping"],
         entity_df,
         event_timestamp,
         full_feature_names,