Add test for SFV online retrieval

Signed-off-by: Felix Wang <wangfelix98@gmail.com>

sdk/python/tests/integration/online_store/test_universal_online.py

@@ -441,6 +441,82 @@ def test_online_retrieval_with_event_timestamps(
     )
 
 
+@pytest.mark.integration
+@pytest.mark.universal_online_stores
+@pytest.mark.goserver
+@pytest.mark.parametrize("full_feature_names", [True, False], ids=lambda v: str(v))
+def test_stream_feature_view_online_retrieval(
+    environment, universal_data_sources, feature_server_endpoint, full_feature_names
+):
+    """
+    Tests materialization and online retrieval for stream feature views.
+
+    This test is separate from test_online_retrieval since combining feature views and
+    stream feature views into a single test resulted in test flakiness. This is tech
+    debt that should be resolved soon.
+    """
+    # Set up feature store.
+    fs = environment.feature_store
+    entities, datasets, data_sources = universal_data_sources
+    feature_views = construct_universal_feature_views(data_sources)
+    pushable_feature_view = feature_views.pushed_locations
+    fs.apply([location(), pushable_feature_view])
+
+    # Materialize.
+    fs.materialize(
+        environment.start_date - timedelta(days=1),
+        environment.end_date + timedelta(days=1),
+    )
+
+    # Get online features by randomly sampling 10 entities that exist in the batch source.
+    sample_locations = datasets.location_df.sample(10)["location_id"]
+    entity_rows = [
+        {"location_id": sample_location} for sample_location in sample_locations
+    ]
+
+    feature_refs = [
+        "pushable_location_stats:temperature",
+    ]
+    unprefixed_feature_refs = [f.rsplit(":", 1)[-1] for f in feature_refs if ":" in f]
+
+    online_features_dict = get_online_features_dict(
+        environment=environment,
+        endpoint=feature_server_endpoint,
+        features=feature_refs,
+        entity_rows=entity_rows,
+        full_feature_names=full_feature_names,
+    )
+
+    # Check that the response has the expected set of keys.
+    keys = set(online_features_dict.keys())
+    expected_keys = set(
+        f.replace(":", "__") if full_feature_names else f.split(":")[-1]
+        for f in feature_refs
+    ) | {"location_id"}
+    assert (
+        keys == expected_keys
+    ), f"Response keys are different from expected: {keys - expected_keys} (extra) and {expected_keys - keys} (missing)"
+
+    # Check that the feature values match.
+    tc = unittest.TestCase()
+    for i, entity_row in enumerate(entity_rows):
+        df_features = get_latest_feature_values_from_location_df(
+            entity_row, datasets.location_df
+        )
+
+        assert df_features["location_id"] == online_features_dict["location_id"][i]
+        for unprefixed_feature_ref in unprefixed_feature_refs:
+            tc.assertAlmostEqual(
+                df_features[unprefixed_feature_ref],
+                online_features_dict[
+                    response_feature_name(
+                        unprefixed_feature_ref, feature_refs, full_feature_names
+                    )
+                ][i],
+                delta=0.0001,
+            )
+
+
 @pytest.mark.integration
 @pytest.mark.universal_online_stores
 @pytest.mark.goserver
@@ -859,6 +935,10 @@ def get_latest_feature_values_for_location_df(entity_row, origin_df, destination
     }
 
 
+def get_latest_feature_values_from_location_df(entity_row, location_df):
+    return get_latest_row(entity_row, location_df, "location_id", "location_id")
+
+
 def assert_feature_service_correctness(
     environment,
     endpoint,