fix: Updated snowflake template

sdk/python/feast/templates/snowflake/README.md

@@ -2,7 +2,7 @@
 A quick view of what's in this repository:
 
 * `data/` contains raw demo parquet data
-* `example_repo.py` contains demo feature definitions
+* `driver_repo.py` contains demo feature definitions
 * `feature_store.yaml` contains a demo setup configuring where data sources are
 * `test_workflow.py` showcases how to run all key Feast commands, including defining, retrieving, and pushing features.
 
@@ -14,6 +14,6 @@ You can run the overall workflow with `python test_workflow.py`.
 2. Setup CI/CD + dev vs staging vs prod environments to automatically update the registry as you change Feast feature definitions. See [docs](https://docs.feast.dev/how-to-guides/running-feast-in-production#1.-automatically-deploying-changes-to-your-feature-definitions).
 3. (optional) Regularly scheduled materialization to power low latency feature retrieval (e.g. via Airflow). See [Batch data ingestion](https://docs.feast.dev/getting-started/concepts/data-ingestion#batch-data-ingestion)
    for more details.
-4. (optional) Deploy feature server instances with `feast serve` to expose endpoints to retrieve online features. 
-    - See [Python feature server](https://docs.feast.dev/reference/feature-servers/python-feature-server) for details. 
-    - Use cases can also directly call the Feast client to fetch features as per [Feature retrieval](https://docs.feast.dev/getting-started/concepts/feature-retrieval) 
+4. (optional) Deploy feature server instances with `feast serve` to expose endpoints to retrieve online features.
+    - See [Python feature server](https://docs.feast.dev/reference/feature-servers/python-feature-server) for details.
+    - Use cases can also directly call the Feast client to fetch features as per [Feature retrieval](https://docs.feast.dev/getting-started/concepts/feature-retrieval)

sdk/python/feast/templates/snowflake/bootstrap.py

@@ -75,6 +75,11 @@ def bootstrap():
             execute_snowflake_statement(
                 conn, f'DROP TABLE IF EXISTS "{project_name}_feast_driver_hourly_stats"'
             )
+            execute_snowflake_statement(
+                conn,
+                f'ALTER WAREHOUSE IF EXISTS "{snowflake_warehouse}" RESUME IF SUSPENDED',
+            )
+
             write_pandas(
                 conn,
                 driver_df,

sdk/python/feast/templates/snowflake/feature_repo/feature_store.yaml

@@ -1,39 +1,28 @@
 project: my_project
-# By default, the registry is a file (but can be turned into a more scalable SQL-backed registry)
-# On GCP/AWS, minimally you should create a GCS/S3 bucket for a remote file registry
-# See https://docs.feast.dev/getting-started/concepts/registry for details
-registry: data/registry.db
-provider: gcp
+registry: registry.db
+provider: local
 offline_store:
-  type: snowflake.offline
-  account: SNOWFLAKE_DEPLOYMENT_URL
-  user: SNOWFLAKE_USER
-  password: SNOWFLAKE_PASSWORD
-  role: SNOWFLAKE_ROLE
-  warehouse: SNOWFLAKE_WAREHOUSE
-  database: SNOWFLAKE_DATABASE
+    type: snowflake.offline
+    account: SNOWFLAKE_DEPLOYMENT_URL
+    user: SNOWFLAKE_USER
+    password: SNOWFLAKE_PASSWORD
+    role: SNOWFLAKE_ROLE
+    warehouse: SNOWFLAKE_WAREHOUSE
+    database: SNOWFLAKE_DATABASE
+batch_engine:
+    type: snowflake.engine
+    account: SNOWFLAKE_DEPLOYMENT_URL
+    user: SNOWFLAKE_USER
+    password: SNOWFLAKE_PASSWORD
+    role: SNOWFLAKE_ROLE
+    warehouse: SNOWFLAKE_WAREHOUSE
+    database: SNOWFLAKE_DATABASE
 online_store:
-  type: snowflake.online
-  account: SNOWFLAKE_DEPLOYMENT_URL
-  user: SNOWFLAKE_USER
-  password: SNOWFLAKE_PASSWORD
-  role: SNOWFLAKE_ROLE
-  warehouse: SNOWFLAKE_WAREHOUSE
-  database: SNOWFLAKE_DATABASE
-# Use GCP Datastore
-# See https://docs.feast.dev/reference/online-stores/datastore
-#online_store:
-#   type: datastore
-#   project_id: my_gcp_project
-#   namespace: my_datastore_namespace
-# Use AWS DynamoDB
-# See https://docs.feast.dev/reference/online-stores/dynamodb
-#online_store:
-#    type: dynamodb
-#    region: %AWS_REGION%
-# Use Redis
-# See https://docs.feast.dev/reference/online-stores/redis
-#online_store:
-#   type: redis
-#   connection_string: "localhost:6379"
+    type: snowflake.online
+    account: SNOWFLAKE_DEPLOYMENT_URL
+    user: SNOWFLAKE_USER
+    password: SNOWFLAKE_PASSWORD
+    role: SNOWFLAKE_ROLE
+    warehouse: SNOWFLAKE_WAREHOUSE
+    database: SNOWFLAKE_DATABASE
 entity_key_serialization_version: 2

sdk/python/feast/templates/snowflake/feature_repo/test_workflow.py → sdk/python/feast/templates/snowflake/test_workflow.py

@@ -8,9 +8,10 @@
 
 
 def run_demo():
-    store = FeatureStore(repo_path=".")
+    store = FeatureStore(repo_path="./feature_repo")
     print("\n--- Run feast apply to setup feature store on Snowflake ---")
-    subprocess.run(["feast", "apply"])
+    command = "cd feature_repo; feast apply"
+    subprocess.run(command, shell=True)
 
     print("\n--- Historical features for training ---")
     fetch_historical_features_entity_df(store, for_batch_scoring=False)
@@ -49,7 +50,8 @@ def run_demo():
     fetch_online_features(store, use_feature_service=True)
 
     print("\n--- Run feast teardown ---")
-    subprocess.run(["feast", "teardown"])
+    command = "cd feature_repo; feast teardown"
+    subprocess.run(command, shell=True)
 
 
 def fetch_historical_features_entity_df(store: FeatureStore, for_batch_scoring: bool):