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# coding: utf-8
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
"""
FILE: ml_samples_featurestore.py
DESCRIPTION:
These samples demonstrate different ways to configure Feature Store and related resources.
USAGE:
python ml_samples_featurestore.py
"""
import os
class FeatureStoreConfigurationOptions(object):
def feature_store(self):
from azure.ai.ml import MLClient
from azure.identity import DefaultAzureCredential
subscription_id = os.environ["AZUREML_ARM_SUBSCRIPTION"]
resource_group = os.environ["AZUREML_ARM_RESOURCEGROUP"]
storage_account_name = "<FEATURE_STORAGE_ACCOUNT_NAME>"
storage_file_system_name = "offlinestore"
redis_cache_name = "onlinestore"
credential = DefaultAzureCredential()
ml_client = MLClient(
credential=credential,
subscription_id=subscription_id,
resource_group_name=resource_group,
)
# [START configure_feature_store_settings]
from azure.ai.ml.entities import ComputeRuntime, FeatureStoreSettings
offline_store_target = f"/subscriptions/{subscription_id}/resourceGroups/{resource_group}/providers/Microsoft.Storage/storageAccounts/{storage_account_name}/blobServices/default/containers/{storage_file_system_name}"
online_store_target = f"/subscriptions/{subscription_id}/resourceGroups/{resource_group}/providers/Microsoft.Cache/Redis/{redis_cache_name}"
FeatureStoreSettings(
compute_runtime=ComputeRuntime(spark_runtime_version="3.4.0"),
offline_store_connection_name=offline_store_target,
online_store_connection_name=online_store_target,
)
# [END configure_feature_store_settings]
# [START create_feature_store]
from azure.ai.ml.entities import FeatureStore
featurestore_name = "my-featurestore"
featurestore_location = "eastus"
featurestore = FeatureStore(name=featurestore_name, location=featurestore_location)
# wait for featurestore creation
fs_poller = ml_client.feature_stores.begin_create(featurestore, update_dependent_resources=True)
print(fs_poller.result())
# [END create_feature_store]
featurestore_client = MLClient(
credential=credential,
subscription_id=subscription_id,
resource_group_name=resource_group,
workspace_name=featurestore_name,
)
# [START configure_feature_store_entity]
from azure.ai.ml.entities import DataColumn, DataColumnType, FeatureStoreEntity
account_column = DataColumn(name="accountID", type=DataColumnType.STRING)
account_entity_config = FeatureStoreEntity(
name="account",
version="1",
index_columns=[account_column],
stage="Development",
description="This entity represents user account index key accountID.",
tags={"data_type": "nonPII"},
)
# wait for featurestore entity creation
fs_entity_poller = featurestore_client.feature_store_entities.begin_create_or_update(account_entity_config)
print(fs_entity_poller.result())
# [END configure_feature_store_entity]
# [START configure_feature_set]
from azure.ai.ml.entities import FeatureSet, FeatureSetSpecification
transaction_fset_config = FeatureSet(
name="transactions",
version="1",
description="7-day and 3-day rolling aggregation of transactions featureset",
entities=["azureml:account:1"],
stage="Development",
specification=FeatureSetSpecification(path="../azure-ai-ml/tests/test_configs/feature_set/code_sample/"),
tags={"data_type": "nonPII"},
)
feature_set_poller = featurestore_client.feature_sets.begin_create_or_update(transaction_fset_config)
print(feature_set_poller.result())
# [END configure_feature_set]
# [START configure_materialization_store]
from azure.ai.ml.entities import ManagedIdentityConfiguration, MaterializationStore
gen2_container_arm_id = "/subscriptions/{sub_id}/resourceGroups/{rg}/providers/Microsoft.Storage/storageAccounts/{account}/blobServices/default/containers/{container}".format(
sub_id=subscription_id,
rg=resource_group,
account=storage_account_name,
container=storage_file_system_name,
)
offline_store = MaterializationStore(
type="azure_data_lake_gen2",
target=gen2_container_arm_id,
)
# Must define materialization identity when defining offline/online store.
fs = FeatureStore(
name=featurestore_name,
offline_store=offline_store,
materialization_identity=ManagedIdentityConfiguration(
client_id="<YOUR-UAI-CLIENT-ID>",
resource_id="<YOUR-UAI-RESOURCE-ID>",
principal_id="<YOUR-UAI-PRINCIPAL-ID>",
),
)
# [END configure_materialization_store]
# Clean up created feature store for sample
ml_client.feature_stores.begin_delete(featurestore.name, delete_dependent_resources=True)
if __name__ == "__main__":
sample = FeatureStoreConfigurationOptions()
sample.feature_store()
|
