fix: Added Redshift and Spark typecheck to data_source event_timestam…

…p_col inference (#2389)

* added Redshift typecheck to data_source event_timestamp_col inference

Signed-off-by: Shai Bruhis <shaibruhis@gmail.com>

* address comments

Signed-off-by: Shai Bruhis <shaibruhis@gmail.com>

* moved non file data sources into their own test

Signed-off-by: Shai Bruhis <shaibruhis@gmail.com>

* addressed comments

Signed-off-by: Shai Bruhis <shaibruhis@gmail.com>

* fixed texts

Signed-off-by: Shai Bruhis <shaibruhis@gmail.com>

* remove previously defined event_timestamp_column from data_source to allow for inference

Signed-off-by: Shai Bruhis <shaibruhis@gmail.com>

* made a deepcopy of data_sources to not affect other tests

Signed-off-by: Shai Bruhis <shaibruhis@gmail.com>

* linter

Signed-off-by: Shai Bruhis <shaibruhis@gmail.com>

sdk/python/feast/inference.py

@@ -111,7 +111,9 @@ def update_data_sources_with_inferred_event_timestamp_col(
             assert (
                 isinstance(data_source, FileSource)
                 or isinstance(data_source, BigQuerySource)
+                or isinstance(data_source, RedshiftSource)
                 or isinstance(data_source, SnowflakeSource)
+                or "SparkSource" == data_source.__class__.__name__
             )
 
             # loop through table columns to find singular match

sdk/python/tests/integration/feature_repos/repo_configuration.py

@@ -203,6 +203,9 @@ class UniversalDataSources:
     global_ds: DataSource
     field_mapping: DataSource
 
+    def values(self):
+        return dataclasses.asdict(self).values()
+
 
 def construct_universal_data_sources(
     datasets: UniversalDatasets, data_source_creator: DataSourceCreator

sdk/python/tests/integration/registration/test_inference.py

@@ -1,3 +1,5 @@
+from copy import deepcopy
+
 import pandas as pd
 import pytest
 
@@ -111,7 +113,7 @@ def test_infer_datasource_names_dwh():
 
 
 @pytest.mark.integration
-def test_update_data_sources_with_inferred_event_timestamp_col(simple_dataset_1):
+def test_update_file_data_source_with_inferred_event_timestamp_col(simple_dataset_1):
     df_with_two_viable_timestamp_cols = simple_dataset_1.copy(deep=True)
     df_with_two_viable_timestamp_cols["ts_2"] = simple_dataset_1["ts_1"]
 
@@ -138,6 +140,28 @@ def test_update_data_sources_with_inferred_event_timestamp_col(simple_dataset_1)
             )
 
 
+@pytest.mark.integration
+@pytest.mark.universal
+def test_update_data_sources_with_inferred_event_timestamp_col(universal_data_sources):
+    (_, _, data_sources) = universal_data_sources
+    data_sources_copy = deepcopy(data_sources)
+
+    # remove defined event_timestamp_column to allow for inference
+    for data_source in data_sources_copy.values():
+        data_source.event_timestamp_column = None
+
+    update_data_sources_with_inferred_event_timestamp_col(
+        data_sources_copy.values(), RepoConfig(provider="local", project="test"),
+    )
+    actual_event_timestamp_cols = [
+        source.event_timestamp_column for source in data_sources_copy.values()
+    ]
+
+    assert actual_event_timestamp_cols == ["event_timestamp"] * len(
+        data_sources_copy.values()
+    )
+
+
 def test_on_demand_features_type_inference():
     # Create Feature Views
     date_request = RequestDataSource(