diff --git a/sdk/python/feast/templates/spark/bootstrap.py b/sdk/python/feast/templates/spark/bootstrap.py
index fc0be4ea0ab..7a397e31571 100644
--- a/sdk/python/feast/templates/spark/bootstrap.py
+++ b/sdk/python/feast/templates/spark/bootstrap.py
@@ -21,6 +21,7 @@ def bootstrap():
     driver_stats_df.to_parquet(
         path=str(data_path / "driver_hourly_stats.parquet"),
         allow_truncated_timestamps=True,
+        coerce_timestamps="us",
     )
 
     customer_entities = [201, 202, 203]
@@ -30,6 +31,7 @@ def bootstrap():
     customer_profile_df.to_parquet(
         path=str(data_path / "customer_daily_profile.parquet"),
         allow_truncated_timestamps=True,
+        coerce_timestamps="us",
     )
 
 
diff --git a/sdk/python/feast/templates/spark/feature_repo/example_repo.py b/sdk/python/feast/templates/spark/feature_repo/example_repo.py
index 8ad48f53fc4..826e9db0d0c 100644
--- a/sdk/python/feast/templates/spark/feature_repo/example_repo.py
+++ b/sdk/python/feast/templates/spark/feature_repo/example_repo.py
@@ -5,25 +5,21 @@
 from datetime import timedelta
 from pathlib import Path
 
-from feast import Entity, FeatureService, FeatureView, Field
+import pandas as pd
+from feast.on_demand_feature_view import on_demand_feature_view
+from feast import Entity, FeatureService, FeatureView, Field, RequestSource
 from feast.infra.offline_stores.contrib.spark_offline_store.spark_source import (
     SparkSource,
 )
-from feast.types import Float32, Int64
+from feast.types import Float32, Float64, Int64
 
 # Constants related to the generated data sets
 CURRENT_DIR = Path(__file__).parent
 
 
 # Entity definitions
-driver = Entity(
-    name="driver",
-    description="driver id",
-)
-customer = Entity(
-    name="customer",
-    description="customer id",
-)
+driver = Entity(name="driver", description="driver id", join_keys=["driver_id"])
+customer = Entity(name="customer", description="customer id", join_keys=["customer_id"])
 
 # Sources
 driver_hourly_stats = SparkSource(
@@ -55,6 +51,17 @@
     source=driver_hourly_stats,
     tags={},
 )
+
+# Define a request data source which encodes features / information only
+# available at request time (e.g. part of the user initiated HTTP request)
+input_request = RequestSource(
+    name="vals_to_add",
+    schema=[
+        Field(name="val_to_add", dtype=Int64),
+        Field(name="val_to_add_2", dtype=Int64),
+    ],
+)
+
 customer_daily_profile_view = FeatureView(
     name="customer_daily_profile",
     entities=[customer],
@@ -73,3 +80,19 @@
     name="driver_activity",
     features=[driver_hourly_stats_view, customer_daily_profile_view],
 )
+
+
+# Define an on demand feature view which can generate new features based on
+# existing feature views and RequestSource features
+@on_demand_feature_view(
+    sources=[driver_hourly_stats_view, input_request],
+    schema=[
+        Field(name="conv_rate_plus_val1", dtype=Float64),
+        Field(name="conv_rate_plus_val2", dtype=Float64),
+    ],
+)
+def transformed_conv_rate(inputs: pd.DataFrame) -> pd.DataFrame:
+    df = pd.DataFrame()
+    df["conv_rate_plus_val1"] = inputs["conv_rate"] + inputs["val_to_add"]
+    df["conv_rate_plus_val2"] = inputs["conv_rate"] + inputs["val_to_add_2"]
+    return df
diff --git a/sdk/python/feast/templates/spark/feature_repo/test_workflow.py b/sdk/python/feast/templates/spark/feature_repo/test_workflow.py
index 08d493fc54f..484b91eea6f 100644
--- a/sdk/python/feast/templates/spark/feature_repo/test_workflow.py
+++ b/sdk/python/feast/templates/spark/feature_repo/test_workflow.py
@@ -4,7 +4,6 @@
 import pandas as pd
 
 from feast import FeatureStore
-from feast.data_source import PushMode
 
 
 def run_demo():
@@ -27,27 +26,6 @@ def run_demo():
     print("\n--- Online features retrieved (instead) through a feature service---")
     fetch_online_features(store, use_feature_service=True)
 
-    print("\n--- Simulate a stream event ingestion of the hourly stats df ---")
-    event_df = pd.DataFrame.from_dict(
-        {
-            "driver_id": [1001],
-            "event_timestamp": [
-                datetime(2021, 5, 13, 10, 59, 42),
-            ],
-            "created": [
-                datetime(2021, 5, 13, 10, 59, 42),
-            ],
-            "conv_rate": [1.0],
-            "acc_rate": [1.0],
-            "avg_daily_trips": [1000],
-        }
-    )
-    print(event_df)
-    store.push("driver_stats_push_source", event_df, to=PushMode.ONLINE)
-
-    print("\n--- Online features again with updated values from a stream push---")
-    fetch_online_features(store, use_feature_service=True)
-
     print("\n--- Run feast teardown ---")
     subprocess.run(["feast", "teardown"])
 
@@ -82,8 +60,6 @@ def fetch_historical_features_entity_df(store: FeatureStore, for_batch_scoring:
             "driver_hourly_stats:conv_rate",
             "driver_hourly_stats:acc_rate",
             "driver_hourly_stats:avg_daily_trips",
-            "transformed_conv_rate:conv_rate_plus_val1",
-            "transformed_conv_rate:conv_rate_plus_val2",
         ],
     ).to_df()
     print(training_df.head())
@@ -94,23 +70,24 @@ def fetch_online_features(store, use_feature_service: bool):
         # {join_key: entity_value}
         {
             "driver_id": 1001,
+            "customer_id": 201,
             "val_to_add": 1000,
             "val_to_add_2": 2000,
         },
         {
             "driver_id": 1002,
+            "customer_id": 202,
             "val_to_add": 1001,
             "val_to_add_2": 2002,
         },
     ]
     if use_feature_service:
-        features_to_fetch = store.get_feature_service("driver_activity_v1")
+        features_to_fetch = store.get_feature_service("driver_activity")
     else:
         features_to_fetch = [
             "driver_hourly_stats:acc_rate",
             "driver_hourly_stats:avg_daily_trips",
             "transformed_conv_rate:conv_rate_plus_val1",
-            "transformed_conv_rate:conv_rate_plus_val2",
         ]
     returned_features = store.get_online_features(
         features=features_to_fetch,