def materialize_single_feature_view(
self,
config: RepoConfig,
feature_view: FeatureView,
start_date: datetime,
end_date: datetime,
registry: Registry,
project: str,
tqdm_builder: Callable[[int], tqdm],
) -> None:
set_usage_attribute("provider", self.__class__.__name__)
entities = []
for entity_name in feature_view.entities:
entities.append(registry.get_entity(entity_name, project))
(
join_key_columns,
feature_name_columns,
event_timestamp_column,
created_timestamp_column,
) = _get_column_names(feature_view, entities)
offline_job = self.offline_store.pull_latest_from_table_or_query(
config=config,
data_source=feature_view.batch_source,
join_key_columns=join_key_columns,
feature_name_columns=feature_name_columns,
event_timestamp_column=event_timestamp_column,
created_timestamp_column=created_timestamp_column,
start_date=start_date,
end_date=end_date,
)
table = offline_job.to_arrow()
if feature_view.batch_source.field_mapping is not None:
table = _run_field_mapping(table,
feature_view.batch_source.field_mapping)
join_keys = {entity.join_key: entity.value_type for entity in entities}
with tqdm_builder(table.num_rows) as pbar:
for batch in table.to_batches(DEFAULT_BATCH_SIZE):
rows_to_write = _convert_arrow_to_proto(
batch, feature_view, join_keys)
self.online_write_batch(
self.repo_config,
feature_view,
rows_to_write,
lambda x: pbar.update(x),
)
def benchmark_writes():
project_id = "test" + "".join(
random.choice(string.ascii_lowercase + string.digits) for _ in range(10)
)
with tempfile.TemporaryDirectory() as temp_dir:
store = FeatureStore(
config=RepoConfig(
registry=os.path.join(temp_dir, "registry.db"),
project=project_id,
provider="gcp",
)
)
# This is just to set data source to something, we're not reading from parquet source here.
parquet_path = os.path.join(temp_dir, "data.parquet")
driver = Entity(name="driver_id", value_type=ValueType.INT64)
table = create_driver_hourly_stats_feature_view(
create_driver_hourly_stats_source(parquet_path=parquet_path)
)
store.apply([table, driver])
provider = store._get_provider()
end_date = datetime.utcnow()
start_date = end_date - timedelta(days=14)
customers = list(range(100))
data = create_driver_hourly_stats_df(customers, start_date, end_date)
# Show the data for reference
print(data)
proto_data = _convert_arrow_to_proto(
pa.Table.from_pandas(data), table, ["driver_id"]
)
# Write it
with tqdm(total=len(proto_data)) as progress:
provider.online_write_batch(
project=store.project,
table=table,
data=proto_data,
progress=progress.update,
)
registry_tables = store.list_feature_views()
registry_entities = store.list_entities()
provider.teardown_infra(
store.project, tables=registry_tables, entities=registry_entities
)
def ingest_df(
self, feature_view: FeatureView, entities: List[Entity], df: pandas.DataFrame,
):
table = pa.Table.from_pandas(df)
if feature_view.batch_source.field_mapping is not None:
table = _run_field_mapping(table, feature_view.batch_source.field_mapping)
join_keys = [entity.join_key for entity in entities]
rows_to_write = _convert_arrow_to_proto(table, feature_view, join_keys)
self.online_write_batch(
self.repo_config, feature_view, rows_to_write, progress=None
)
def materialize_single_feature_view(
self,
feature_view: FeatureView,
start_date: datetime,
end_date: datetime,
registry: Registry,
project: str,
tqdm_builder: Callable[[int], tqdm],
) -> None:
entities = []
for entity_name in feature_view.entities:
entities.append(registry.get_entity(entity_name, project))
(
join_key_columns,
feature_name_columns,
event_timestamp_column,
created_timestamp_column,
) = _get_column_names(feature_view, entities)
start_date = utils.make_tzaware(start_date)
end_date = utils.make_tzaware(end_date)
table = self.offline_store.pull_latest_from_table_or_query(
data_source=feature_view.input,
join_key_columns=join_key_columns,
feature_name_columns=feature_name_columns,
event_timestamp_column=event_timestamp_column,
created_timestamp_column=created_timestamp_column,
start_date=start_date,
end_date=end_date,
)
if feature_view.input.field_mapping is not None:
table = _run_field_mapping(table, feature_view.input.field_mapping)
join_keys = [entity.join_key for entity in entities]
rows_to_write = _convert_arrow_to_proto(table, feature_view, join_keys)
with tqdm_builder(len(rows_to_write)) as pbar:
self.online_write_batch(
project, feature_view, rows_to_write, lambda x: pbar.update(x)
)
feature_view.materialization_intervals.append((start_date, end_date))
registry.apply_feature_view(feature_view, project)
def materialize_single_feature_view(
self,
feature_view: FeatureView,
start_date: datetime,
end_date: datetime,
registry: Registry,
project: str,
) -> None:
assert isinstance(feature_view.input, BigQuerySource)
entities = []
for entity_name in feature_view.entities:
entities.append(registry.get_entity(entity_name, project))
(
join_key_columns,
feature_name_columns,
event_timestamp_column,
created_timestamp_column,
) = _get_column_names(feature_view, entities)
start_date = utils.make_tzaware(start_date)
end_date = utils.make_tzaware(end_date)
offline_store = get_offline_store_from_sources([feature_view.input])
table = offline_store.pull_latest_from_table_or_query(
data_source=feature_view.input,
join_key_columns=join_key_columns,
feature_name_columns=feature_name_columns,
event_timestamp_column=event_timestamp_column,
created_timestamp_column=created_timestamp_column,
start_date=start_date,
end_date=end_date,
)
if feature_view.input.field_mapping is not None:
table = _run_field_mapping(table, feature_view.input.field_mapping)
join_keys = [entity.join_key for entity in entities]
rows_to_write = _convert_arrow_to_proto(table, feature_view, join_keys)
self.online_write_batch(project, feature_view, rows_to_write, None)
feature_view.materialization_intervals.append((start_date, end_date))
registry.apply_feature_view(feature_view, project)
def materialize_single_feature_view(
self,
config: RepoConfig,
feature_view: FeatureView,
start_date: datetime,
end_date: datetime,
registry: Registry,
project: str,
tqdm_builder: Callable[[int], tqdm],
) -> None:
entities = []
for entity_name in feature_view.entities:
entities.append(registry.get_entity(entity_name, project))
(
join_key_columns,
feature_name_columns,
event_timestamp_column,
created_timestamp_column,
) = _get_column_names(feature_view, entities)
offline_job = self.offline_store.pull_latest_from_table_or_query(
config=config,
data_source=feature_view.batch_source,
join_key_columns=join_key_columns,
feature_name_columns=feature_name_columns,
event_timestamp_column=event_timestamp_column,
created_timestamp_column=created_timestamp_column,
start_date=start_date,
end_date=end_date,
)
table = offline_job.to_arrow()
if feature_view.batch_source.field_mapping is not None:
table = _run_field_mapping(table,
feature_view.batch_source.field_mapping)
join_keys = [entity.join_key for entity in entities]
rows_to_write = _convert_arrow_to_proto(table, feature_view, join_keys)
with tqdm_builder(len(rows_to_write)) as pbar:
self.online_write_batch(self.repo_config, feature_view,
rows_to_write, lambda x: pbar.update(x))
def ingest_df(
self,
feature_view: FeatureView,
entities: List[Entity],
df: pandas.DataFrame,
):
set_usage_attribute("provider", self.__class__.__name__)
table = pa.Table.from_pandas(df)
if feature_view.batch_source.field_mapping is not None:
table = _run_field_mapping(table,
feature_view.batch_source.field_mapping)
join_keys = {entity.join_key: entity.value_type for entity in entities}
rows_to_write = _convert_arrow_to_proto(table, feature_view, join_keys)
self.online_write_batch(self.repo_config,
feature_view,
rows_to_write,
progress=None)
