Merge pull request feast-dev#10 from tmihalac/implement-remaining-off…

…line-methods

Implement remaining Remote Offline Store methods

sdk/python/feast/offline_server.py

@@ -2,13 +2,17 @@
 import json
 import logging
 import traceback
+from datetime import datetime
 from typing import Any, Dict, List
 
 import pyarrow as pa
 import pyarrow.flight as fl
 
-from feast import FeatureStore, FeatureView
+from feast import FeatureStore, FeatureView, utils
+from feast.feature_logging import FeatureServiceLoggingSource
 from feast.feature_view import DUMMY_ENTITY_NAME
+from feast.infra.offline_stores.offline_utils import get_offline_store_from_config
+from feast.saved_dataset import SavedDatasetStorage
 
 logger = logging.getLogger(__name__)
 
@@ -20,6 +24,7 @@ def __init__(self, store: FeatureStore, location: str, **kwargs):
         # A dictionary of configured flights, e.g. API calls received and not yet served
         self.flights: Dict[str, Any] = {}
         self.store = store
+        self.offline_store = get_offline_store_from_config(store.config.offline_store)
 
     @classmethod
     def descriptor_to_key(self, descriptor):
@@ -126,67 +131,167 @@ def do_get(self, context, ticket):
         api = command["api"]
         logger.debug(f"get command is {command}")
         logger.debug(f"requested api is {api}")
-        if api == "get_historical_features":
-            # Extract parameters from the internal flights dictionary
-            entity_df_value = self.flights[key]
-            entity_df = pa.Table.to_pandas(entity_df_value)
-            logger.debug(f"do_get: entity_df is {entity_df}")
-
-            feature_view_names = command["feature_view_names"]
-            logger.debug(f"do_get: feature_view_names is {feature_view_names}")
-            name_aliases = command["name_aliases"]
-            logger.debug(f"do_get: name_aliases is {name_aliases}")
-            feature_refs = command["feature_refs"]
-            logger.debug(f"do_get: feature_refs is {feature_refs}")
-            project = command["project"]
-            logger.debug(f"do_get: project is {project}")
-            full_feature_names = command["full_feature_names"]
-            feature_views = self.list_feature_views_by_name(
-                feature_view_names=feature_view_names,
-                name_aliases=name_aliases,
-                project=project,
-            )
-            logger.debug(f"do_get: feature_views is {feature_views}")
+        try:
+            if api == OfflineServer.get_historical_features.__name__:
+                df = self.get_historical_features(command, key).to_df()
+            elif api == OfflineServer.pull_all_from_table_or_query.__name__:
+                df = self.pull_all_from_table_or_query(command).to_df()
+            elif api == OfflineServer.pull_latest_from_table_or_query.__name__:
+                df = self.pull_latest_from_table_or_query(command).to_df()
+            else:
+                raise NotImplementedError
+        except Exception as e:
+            logger.exception(e)
+            traceback.print_exc()
+            raise e
 
-            logger.info(
-                f"get_historical_features for: entity_df from {entity_df.index[0]} to {entity_df.index[len(entity_df)-1]}, "
-                f"feature_views is {[(fv.name, fv.entities) for fv in feature_views]}"
-                f"feature_refs is {feature_refs}"
-            )
+        table = pa.Table.from_pandas(df)
 
-            try:
-                training_df = (
-                    self.store._get_provider()
-                    .get_historical_features(
-                        config=self.store.config,
-                        feature_views=feature_views,
-                        feature_refs=feature_refs,
-                        entity_df=entity_df,
-                        registry=self.store._registry,
-                        project=project,
-                        full_feature_names=full_feature_names,
-                    )
-                    .to_df()
-                )
-                logger.debug(f"Len of training_df is {len(training_df)}")
-                table = pa.Table.from_pandas(training_df)
-            except Exception as e:
-                logger.exception(e)
-                traceback.print_exc()
-                raise e
+        # Get service is consumed, so we clear the corresponding flight and data
+        del self.flights[key]
+        return fl.RecordBatchStream(table)
 
-            # Get service is consumed, so we clear the corresponding flight and data
-            del self.flights[key]
+    def offline_write_batch(self, command, key):
+        feature_view_names = command["feature_view_names"]
+        assert (
+            len(feature_view_names) == 1
+        ), "feature_view_names list should only have one item"
+        name_aliases = command["name_aliases"]
+        assert len(name_aliases) == 1, "name_aliases list should only have one item"
+        project = self.store.config.project
+        feature_views = self.list_feature_views_by_name(
+            feature_view_names=feature_view_names,
+            name_aliases=name_aliases,
+            project=project,
+        )
 
-            return fl.RecordBatchStream(table)
-        else:
-            raise NotImplementedError
+        assert len(feature_views) == 1
+        table = self.flights[key]
+        self.offline_store.offline_write_batch(
+            self.store.config, feature_views[0], table, command["progress"]
+        )
+
+    def write_logged_features(self, command, key):
+        table = self.flights[key]
+        feature_service = self.store.get_feature_service(
+            command["feature_service_name"]
+        )
+
+        self.offline_store.write_logged_features(
+            config=self.store.config,
+            data=table,
+            source=FeatureServiceLoggingSource(
+                feature_service, self.store.config.project
+            ),
+            logging_config=feature_service.logging_config,
+            registry=self.store.registry,
+        )
+
+    def pull_all_from_table_or_query(self, command):
+        return self.offline_store.pull_all_from_table_or_query(
+            self.store.config,
+            self.store.get_data_source(command["data_source_name"]),
+            command["join_key_columns"],
+            command["feature_name_columns"],
+            command["timestamp_field"],
+            utils.make_tzaware(datetime.fromisoformat(command["start_date"])),
+            utils.make_tzaware(datetime.fromisoformat(command["end_date"])),
+        )
+
+    def pull_latest_from_table_or_query(self, command):
+        return self.offline_store.pull_latest_from_table_or_query(
+            self.store.config,
+            self.store.get_data_source(command["data_source_name"]),
+            command["join_key_columns"],
+            command["feature_name_columns"],
+            command["timestamp_field"],
+            command["created_timestamp_column"],
+            utils.make_tzaware(datetime.fromisoformat(command["start_date"])),
+            utils.make_tzaware(datetime.fromisoformat(command["end_date"])),
+        )
 
     def list_actions(self, context):
-        return []
+        return [
+            (
+                OfflineServer.offline_write_batch.__name__,
+                "Writes the specified arrow table to the data source underlying the specified feature view.",
+            ),
+            (
+                OfflineServer.write_logged_features.__name__,
+                "Writes logged features to a specified destination in the offline store.",
+            ),
+            (
+                OfflineServer.persist.__name__,
+                "Synchronously executes the underlying query and persists the result in the same offline store at the "
+                "specified destination.",
+            ),
+        ]
+
+    def get_historical_features(self, command, key):
+        # Extract parameters from the internal flights dictionary
+        entity_df_value = self.flights[key]
+        entity_df = pa.Table.to_pandas(entity_df_value)
+        feature_view_names = command["feature_view_names"]
+        name_aliases = command["name_aliases"]
+        feature_refs = command["feature_refs"]
+        project = command["project"]
+        full_feature_names = command["full_feature_names"]
+        feature_views = self.list_feature_views_by_name(
+            feature_view_names=feature_view_names,
+            name_aliases=name_aliases,
+            project=project,
+        )
+        retJob = self.offline_store.get_historical_features(
+            config=self.store.config,
+            feature_views=feature_views,
+            feature_refs=feature_refs,
+            entity_df=entity_df,
+            registry=self.store.registry,
+            project=project,
+            full_feature_names=full_feature_names,
+        )
+        return retJob
+
+    def persist(self, command, key):
+        try:
+            api = command["api"]
+            if api == OfflineServer.get_historical_features.__name__:
+                ret_job = self.get_historical_features(command, key)
+            elif api == OfflineServer.pull_latest_from_table_or_query.__name__:
+                ret_job = self.pull_latest_from_table_or_query(command)
+            elif api == OfflineServer.pull_all_from_table_or_query.__name__:
+                ret_job = self.pull_all_from_table_or_query(command)
+            else:
+                raise NotImplementedError
+
+            data_source = self.store.get_data_source(command["data_source_name"])
+            storage = SavedDatasetStorage.from_data_source(data_source)
+            ret_job.persist(storage, command["allow_overwrite"], command["timeout"])
+        except Exception as e:
+            logger.exception(e)
+            traceback.print_exc()
+            raise e
 
     def do_action(self, context, action):
-        raise NotImplementedError
+        command_descriptor = fl.FlightDescriptor.deserialize(action.body.to_pybytes())
+
+        key = OfflineServer.descriptor_to_key(command_descriptor)
+        command = json.loads(key[1])
+        logger.info(f"do_action command is {command}")
+
+        try:
+            if action.type == OfflineServer.offline_write_batch.__name__:
+                self.offline_write_batch(command, key)
+            elif action.type == OfflineServer.write_logged_features.__name__:
+                self.write_logged_features(command, key)
+            elif action.type == OfflineServer.persist.__name__:
+                self.persist(command, key)
+            else:
+                raise NotImplementedError
+        except Exception as e:
+            logger.exception(e)
+            traceback.print_exc()
+            raise e
 
     def do_drop_dataset(self, dataset):
         pass

sdk/python/feast/templates/local/bootstrap.py

@@ -24,6 +24,7 @@ def bootstrap():
 
     example_py_file = repo_path / "example_repo.py"
     replace_str_in_file(example_py_file, "%PARQUET_PATH%", str(driver_stats_path))
+    replace_str_in_file(example_py_file, "%LOGGING_PATH%", str(data_path))
 
 
 if __name__ == "__main__":

sdk/python/feast/templates/local/feature_repo/example_repo.py

@@ -13,6 +13,8 @@
     PushSource,
     RequestSource,
 )
+from feast.feature_logging import LoggingConfig
+from feast.infra.offline_stores.file_source import FileLoggingDestination
 from feast.on_demand_feature_view import on_demand_feature_view
 from feast.types import Float32, Float64, Int64
 
@@ -88,6 +90,9 @@ def transformed_conv_rate(inputs: pd.DataFrame) -> pd.DataFrame:
         driver_stats_fv[["conv_rate"]],  # Sub-selects a feature from a feature view
         transformed_conv_rate,  # Selects all features from the feature view
     ],
+    logging_config=LoggingConfig(
+        destination=FileLoggingDestination(path="%LOGGING_PATH%")
+    ),
 )
 driver_activity_v2 = FeatureService(
     name="driver_activity_v2", features=[driver_stats_fv, transformed_conv_rate]

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

@@ -34,8 +34,6 @@ def test_feature_service_logging(environment, universal_data_sources, pass_as_pa
     (_, datasets, data_sources) = universal_data_sources
 
     feature_views = construct_universal_feature_views(data_sources)
-    store.apply([customer(), driver(), location(), *feature_views.values()])
-
     feature_service = FeatureService(
         name="test_service",
         features=[
@@ -49,6 +47,17 @@ def test_feature_service_logging(environment, universal_data_sources, pass_as_pa
         ),
     )
 
+    store.apply(
+        [customer(), driver(), location(), *feature_views.values()], feature_service
+    )
+
+    # Added to handle the case that the offline store is remote
+    store.registry.apply_feature_service(feature_service, store.config.project)
+    store.registry.apply_data_source(
+        feature_service.logging_config.destination.to_data_source(),
+        store.config.project,
+    )
+
     driver_df = datasets.driver_df
     driver_df["val_to_add"] = 50
     driver_df = driver_df.join(conv_rate_plus_100(driver_df))

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

@@ -19,6 +19,9 @@
     construct_universal_feature_views,
     table_name_from_data_source,
 )
+from tests.integration.feature_repos.universal.data_sources.file import (
+    RemoteOfflineStoreDataSourceCreator,
+)
 from tests.integration.feature_repos.universal.data_sources.snowflake import (
     SnowflakeDataSourceCreator,
 )
@@ -157,22 +160,25 @@ def test_historical_features_main(
         timestamp_precision=timedelta(milliseconds=1),
     )
 
-    assert_feature_service_correctness(
-        store,
-        feature_service,
-        full_feature_names,
-        entity_df_with_request_data,
-        expected_df,
-        event_timestamp,
-    )
-    assert_feature_service_entity_mapping_correctness(
-        store,
-        feature_service_entity_mapping,
-        full_feature_names,
-        entity_df_with_request_data,
-        full_expected_df,
-        event_timestamp,
-    )
+    if not isinstance(
+        environment.data_source_creator, RemoteOfflineStoreDataSourceCreator
+    ):
+        assert_feature_service_correctness(
+            store,
+            feature_service,
+            full_feature_names,
+            entity_df_with_request_data,
+            expected_df,
+            event_timestamp,
+        )
+        assert_feature_service_entity_mapping_correctness(
+            store,
+            feature_service_entity_mapping,
+            full_feature_names,
+            entity_df_with_request_data,
+            full_expected_df,
+            event_timestamp,
+        )
     table_from_df_entities: pd.DataFrame = job_from_df.to_arrow().to_pandas()
 
     validate_dataframes(
@@ -375,8 +381,13 @@ def test_historical_features_persisting(
     (entities, datasets, data_sources) = universal_data_sources
     feature_views = construct_universal_feature_views(data_sources)
 
+    storage = environment.data_source_creator.create_saved_dataset_destination()
+
     store.apply([driver(), customer(), location(), *feature_views.values()])
 
+    # Added to handle the case that the offline store is remote
+    store.registry.apply_data_source(storage.to_data_source(), store.config.project)
+
     entity_df = datasets.entity_df.drop(
         columns=["order_id", "origin_id", "destination_id"]
     )
@@ -398,7 +409,7 @@ def test_historical_features_persisting(
     saved_dataset = store.create_saved_dataset(
         from_=job,
         name="saved_dataset",
-        storage=environment.data_source_creator.create_saved_dataset_destination(),
+        storage=storage,
         tags={"env": "test"},
         allow_overwrite=True,
     )