Feature Store

Feature store is the top-level entity for a Feature Store.

Define

In an ADS Feature Store module, you can use the Python API or a .yaml file to define a Feature Store.

The following example defines a Feature Store and gives it a name. A FeatureStore instance is created.

• Python
• YAML

from ads.feature_store.feature_store import FeatureStore

feature_store = (
        FeatureStore().
        with_description(<feature_store_description>).
        with_compartment_id("ocid1.compartment..<unique_id>").
        with_name(<feature_store_name>).
        with_offline_config(
            metastore_id=metastoreId
        )
)

from ads.feature_store.feature_store import FeatureStore

yaml_string = """
kind: feature_store
spec:
  compartmentId: ocid1.compartment..<unique_id>
  description: <feature_store_description>
  name: <feature_store_name>
  featureStoreId: <feature_store_id>
type: feature_store
"""

feature_store = FeatureStore.from_yaml(yaml_string)

Create

Use the create() method of the FeatureStore instance to create a Feature Store.

# Create an Feature Store
feature_store.create()

Load

Use the from_id() method from the FeatureStore class to load an existing Feature Store by specifying its OCID. A FeatureStore instance is returned.

from ads.feature_store.feature_store import FeatureStore

feature_store = FeatureStore.from_id("<unique_id>")

Delete

Use the .delete() method on the FeatureStore instance to delete a Feature Store. A Feature Store can only be deleted when its associated entities are all deleted.

feature_store.delete()

SQL

Use the sql() method of the FeatureStore instance to query a Feature Store.

The following example queries a Feature Store using SQL:

# Fetch the entity id. Entity id is used as database name in Feature Store
entity_id = entity.id

# Form a query with entity id and fetch the results
sql = (f"SELECT feature_group_a.* "
     f"FROM {entity_id}.feature_group_a "
     f"JOIN {entity_id}.feature_group_b "
     f"ON {entity_id}.feature_group_a.col_1={entity_id}.feature_group_b.col_2 "
     f"JOIN {entity_id}.feature_group_a.col_1={entity_id}.feature_group_b.col_3 ")

# Run the sql query and fetch the results as data-frame
df = feature_store.sql(sql)

Create an Entity

Use the create_entity() method of the FeatureStore instance to create an Entity.

# Create a Feature Store entity
feature_store.create_entity(name="<ENTITY_NAME>")

Create a Transformation

Transformations in a Feature Store are the operations and processes applied to raw data to create, modify, or derive new features for use as inputs for machine learning models. These transformations are necessary for improving the quality, relevance, and usefulness of features that then enhance the performance of models. You can call the create_transformation() method of the FeatureStore instance to create a Transformation.

# Create a Feature Store entity
feature_store.create_transformation(
    source_code_func="<FUNCTION>",
    transformation_mode="SQL|PANDAS"
    name="<TRANSFORMATION NAME>"
)