Feast batch materialization operations (materialize and materialize-incremental) execute through a BatchMaterializationEngine.
Custom batch materialization engines allow Feast users to extend Feast to customize the materialization process. Examples include:
Setting up custom materialization-specific infrastructure during feast apply (e.g. setting up Spark clusters or Lambda Functions)
Launching custom batch ingestion (materialization) jobs (Spark, Beam, AWS Lambda)
Tearing down custom materialization-specific infrastructure during feast teardown (e.g. tearing down Spark clusters, or deleting Lambda Functions)
Feast comes with built-in materialization engines, e.g, LocalMaterializationEngine, and an experimental LambdaMaterializationEngine. However, users can develop their own materialization engines by creating a class that implements the contract in the .
Guide
The fastest way to add custom logic to Feast is to extend an existing materialization engine. The most generic engine is the LocalMaterializationEngine which contains no cloud-specific logic. The guide that follows will extend the LocalProvider with operations that print text to the console. It is up to you as a developer to add your custom code to the engine methods, but the guide below will provide the necessary scaffolding to get you started.
Step 1: Define an Engine class
The first step is to define a custom materialization engine class. We've created the MyCustomEngine below.
from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple, Union
from feast.entity import Entity
from feast.feature_view import FeatureView
from feast.batch_feature_view import BatchFeatureView
from feast.stream_feature_view import StreamFeatureView
from feast.infra.materialization import LocalMaterializationEngine, LocalMaterializationJob, MaterializationTask
from feast.infra.offline_stores.offline_store import OfflineStore
from feast.infra.online_stores.online_store import OnlineStore
from feast.repo_config import RepoConfig
class MyCustomEngine(LocalMaterializationEngine):
def __init__(
self,
*,
repo_config: RepoConfig,
offline_store: OfflineStore,
online_store: OnlineStore,
**kwargs,
):
super().__init__(
repo_config=repo_config,
offline_store=offline_store,
online_store=online_store,
**kwargs,
)
def update(
self,
project: str,
views_to_delete: Sequence[
Union[BatchFeatureView, StreamFeatureView, FeatureView]
],
views_to_keep: Sequence[
Union[BatchFeatureView, StreamFeatureView, FeatureView]
],
entities_to_delete: Sequence[Entity],
entities_to_keep: Sequence[Entity],
):
print("Creating new infrastructure is easy here!")
pass
def materialize(
self, registry, tasks: List[MaterializationTask]
) -> List[LocalMaterializationJob]:
print("Launching custom batch jobs or multithreading things is pretty easy...")
return [
self._materialize_one(
registry,
task.feature_view,
task.start_time,
task.end_time,
task.project,
task.tqdm_builder,
)
for task in tasks
]
Notice how in the above engine we have only overwritten two of the methods on the LocalMaterializatinEngine, namely update and materialize. These two methods are convenient to replace if you are planning to launch custom batch jobs.
