@@ -208,19 +208,21 @@ def test_list_jobs_long_table_name(
208208 feast_spark_client : SparkClient ,
209209 batch_source : Union [BigQuerySource , FileSource ],
210210):
211- entity = Entity (name = "s2id" , description = "S2id" , value_type = ValueType .INT64 ,)
211+ entity = Entity (
212+ name = "long_entity_name" * 10 , description = "S2id" , value_type = ValueType .INT64
213+ )
212214
213215 feature_table = FeatureTable (
214216 name = "just1a2featuretable3with4a5really6really7really8really9really10" ,
215- entities = ["s2id" ],
217+ entities = [entity . name ],
216218 features = [Feature ("unique_drivers" , ValueType .INT64 )],
217219 batch_source = batch_source ,
218220 )
219221
220222 feast_client .apply (entity )
221223 feast_client .apply (feature_table )
222224
223- data_sample = generate_data ()
225+ data_sample = generate_data (). rename ( columns = { "s2id" : entity . name })
224226 feast_client .ingest (feature_table , data_sample )
225227
226228 job = feast_spark_client .start_offline_to_online_ingestion (
@@ -242,6 +244,19 @@ def test_list_jobs_long_table_name(
242244 ]
243245 assert job .get_id () in all_job_ids
244246
247+ features = feast_client .get_online_features (
248+ [f"{ feature_table .name } :unique_drivers" ],
249+ entity_rows = [{entity .name : key } for key in data_sample [entity .name ].tolist ()],
250+ ).to_dict ()
251+
252+ ingested = pd .DataFrame .from_dict (features )
253+ pd .testing .assert_frame_equal (
254+ ingested [[entity .name , f"{ feature_table .name } :unique_drivers" ]],
255+ data_sample [[entity .name , "unique_drivers" ]].rename (
256+ columns = {"unique_drivers" : f"{ feature_table .name } :unique_drivers" }
257+ ),
258+ )
259+
245260
246261def avro_schema ():
247262 return json .dumps (
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