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Feature repository

Feast users use Feast to manage two important sets of configuration:

Configuration about how to run Feast on your infrastructure
Feature definitions

With Feast, the above configuration can be written declaratively and stored as code in a central location. This central location is called a feature repository. The feature repository is the declarative source of truth for what the desired state of a feature store should be.

feature_store.yaml

Overview

feature_store.yaml is used to configure a feature store. The file must be located at the root of a feature repository. An example feature_store.yaml is shown below:

feature_store.yaml

project: loyal_spider
registry: data/registry.db
provider: local
online_store:
    type: sqlite
    path: data/online_store.db

Options

The following top-level configuration options exist in the feature_store.yaml file.

provider — Configures the environment in which Feast will deploy and operate.
registry — Configures the location of the feature registry.
online_store — Configures the online store.

Please see the API reference for the full list of configuration options.

.feastignore

Overview

.feastignore is a file that is placed at the root of the Feature Repository. This file contains paths that should be ignored when running feast apply. An example .feastignore is shown below:

.feastignore

# Ignore virtual environment
venv

# Ignore a specific Python file
scripts/foo.py

# Ignore all Python files directly under scripts directory
scripts/*.py

# Ignore all "foo.py" anywhere under scripts directory
scripts/**/foo.py

.feastignore file is optional. If the file can not be found, every Python file in the feature repo directory will be parsed by feast apply.

Feast Ignore Patterns

Pattern

Example matches

Explanation

feature_store.yaml

Overview

feature_store.yaml is used to configure a feature store. The file must be located at the root of a feature repository. An example feature_store.yaml is shown below:

feature_store.yaml

project: loyal_spider
registry: data/registry.db
provider: local
online_store:
    type: sqlite
    path: data/online_store.db

Options

The following top-level configuration options exist in the feature_store.yaml file.

provider — Configures the environment in which Feast will deploy and operate.
registry — Configures the location of the feature registry.
online_store — Configures the online store.

Please see the API reference for the full list of configuration options.

.feastignore

Overview

.feastignore is a file that is placed at the root of the Feature Repository. This file contains paths that should be ignored when running feast apply. An example .feastignore is shown below:

.feastignore

# Ignore virtual environment
venv

# Ignore a specific Python file
scripts/foo.py

# Ignore all Python files directly under scripts directory
scripts/*.py

# Ignore all "foo.py" anywhere under scripts directory
scripts/**/foo.py

.feastignore file is optional. If the file can not be found, every Python file in the feature repo directory will be parsed by feast apply.

Feast Ignore Patterns

Pattern

Example matches

Explanation

driver_features.py

from datetime import timedelta

from feast import BigQuerySource, Entity, Feature, FeatureView, Field, ValueType
from feast.types import Float32, String

driver_locations_source = BigQuerySource(
    table_ref="rh_prod.ride_hailing_co.drivers",
    timestamp_field="event_timestamp",
    created_timestamp_column="created_timestamp",
)

driver = Entity(
    name="driver",
    value_type=ValueType.INT64,
    description="driver id",
)

driver_locations = FeatureView(
    name="driver_locations",
    entities=["driver"],
    ttl=timedelta(days=1),
    schema=[
        Field(name="lat", dtype=Float32),
        Field(name="lon", dtype=String),
    ],
    source=driver_locations_source,
)

driver_features.py

from datetime import timedelta

from feast import BigQuerySource, Entity, Feature, FeatureView, Field, ValueType
from feast.types import Float32, String

driver_locations_source = BigQuerySource(
    table_ref="rh_prod.ride_hailing_co.drivers",
    timestamp_field="event_timestamp",
    created_timestamp_column="created_timestamp",
)

driver = Entity(
    name="driver",
    value_type=ValueType.INT64,
    description="driver id",
)

driver_locations = FeatureView(
    name="driver_locations",
    entities=["driver"],
    ttl=timedelta(days=1),
    schema=[
        Field(name="lat", dtype=Float32),
        Field(name="lon", dtype=String),
    ],
    source=driver_locations_source,
)

Feature repository

feature_store.yaml

Overview

Options

.feastignore

Overview

Feast Ignore Patterns

feature_store.yaml

Overview

Options

.feastignore

Overview

Feast Ignore Patterns

Feature repository

What is a feature repository?

Structure of a feature repository

The feature_store.yaml configuration file

The .feastignore file

Feature definitions

Next steps

Feature repository

feature_store.yaml

hashtagOverview

hashtagOptions

.feastignore

hashtagOverview

hashtagFeast Ignore Patterns

feature_store.yaml

hashtagOverview

hashtagOptions

.feastignore

hashtagOverview

hashtagFeast Ignore Patterns

Feature repository

hashtagWhat is a feature repository?

hashtagStructure of a feature repository

hashtagThe feature_store.yaml configuration file

hashtagThe .feastignore file

hashtagFeature definitions

hashtagNext steps

Overview

Options

Overview

Feast Ignore Patterns

Overview

Options

Overview

Feast Ignore Patterns

What is a feature repository?

Structure of a feature repository

The feature_store.yaml configuration file

The .feastignore file

Feature definitions

Next steps