feat: Implement date_partition_column for SparkSource (feast-dev#4844)

Author: niklasvm

sdk/python/feast/infra/offline_stores/contrib/spark_offline_store/spark.py

@@ -99,6 +99,8 @@ def pull_latest_from_table_or_query(
         fields_as_string = ", ".join(fields_with_aliases)
         aliases_as_string = ", ".join(aliases)
 
+        date_partition_column = data_source.date_partition_column
+
         start_date_str = _format_datetime(start_date)
         end_date_str = _format_datetime(end_date)
         query = f"""
@@ -109,7 +111,7 @@ def pull_latest_from_table_or_query(
                     SELECT {fields_as_string},
                     ROW_NUMBER() OVER({partition_by_join_key_string} ORDER BY {timestamp_desc_string}) AS feast_row_
                     FROM {from_expression} t1
-                    WHERE {timestamp_field} BETWEEN TIMESTAMP('{start_date_str}') AND TIMESTAMP('{end_date_str}')
+                    WHERE {timestamp_field} BETWEEN TIMESTAMP('{start_date_str}') AND TIMESTAMP('{end_date_str}'){" AND "+date_partition_column+" >= '"+start_date.strftime('%Y-%m-%d')+"' AND "+date_partition_column+" <= '"+end_date.strftime('%Y-%m-%d')+"' " if date_partition_column != "" and date_partition_column is not None else ''}
                 ) t2
                 WHERE feast_row_ = 1
                 """
@@ -641,8 +643,15 @@ def _cast_data_frame(
             {% endfor %}
         FROM {{ featureview.table_subquery }}
         WHERE {{ featureview.timestamp_field }} <= '{{ featureview.max_event_timestamp }}'
+        {% if featureview.date_partition_column != "" and featureview.date_partition_column is not none %}
+        AND {{ featureview.date_partition_column }} <= '{{ featureview.max_event_timestamp[:10] }}'
+        {% endif %}
+
         {% if featureview.ttl == 0 %}{% else %}
         AND {{ featureview.timestamp_field }} >= '{{ featureview.min_event_timestamp }}'
+        {% if featureview.date_partition_column != "" and featureview.date_partition_column is not none %}
+          AND {{ featureview.date_partition_column }} >= '{{ featureview.min_event_timestamp[:10] }}'
+        {% endif %}
         {% endif %}
     ),
 

sdk/python/feast/infra/offline_stores/contrib/spark_offline_store/spark_source.py

@@ -45,6 +45,7 @@ def __init__(
         tags: Optional[Dict[str, str]] = None,
         owner: Optional[str] = "",
         timestamp_field: Optional[str] = None,
+        date_partition_column: Optional[str] = None,
     ):
         """Creates a SparkSource object.
 
@@ -64,6 +65,8 @@ def __init__(
                 maintainer.
             timestamp_field: Event timestamp field used for point-in-time joins of
                 feature values.
+            date_partition_column: The column to partition the data on for faster
+                retrieval. This is useful for large tables and will limit the number ofi
         """
         # If no name, use the table as the default name.
         if name is None and table is None:
@@ -77,6 +80,7 @@ def __init__(
             created_timestamp_column=created_timestamp_column,
             field_mapping=field_mapping,
             description=description,
+            date_partition_column=date_partition_column,
             tags=tags,
             owner=owner,
         )
@@ -135,6 +139,7 @@ def from_proto(data_source: DataSourceProto) -> Any:
             query=spark_options.query,
             path=spark_options.path,
             file_format=spark_options.file_format,
+            date_partition_column=data_source.date_partition_column,
             timestamp_field=data_source.timestamp_field,
             created_timestamp_column=data_source.created_timestamp_column,
             description=data_source.description,
@@ -148,6 +153,7 @@ def to_proto(self) -> DataSourceProto:
             type=DataSourceProto.BATCH_SPARK,
             data_source_class_type="feast.infra.offline_stores.contrib.spark_offline_store.spark_source.SparkSource",
             field_mapping=self.field_mapping,
+            date_partition_column=self.date_partition_column,
             spark_options=self.spark_options.to_proto(),
             description=self.description,
             tags=self.tags,

sdk/python/tests/unit/infra/offline_stores/contrib/spark_offline_store/test_spark.py

@@ -71,6 +71,68 @@ def test_pull_latest_from_table_with_nested_timestamp_or_query(mock_get_spark_se
     assert retrieval_job.query.strip() == expected_query.strip()
 
 
+@patch(
+    "feast.infra.offline_stores.contrib.spark_offline_store.spark.get_spark_session_or_start_new_with_repoconfig"
+)
+def test_pull_latest_from_table_with_nested_timestamp_or_query_and_date_partition_column_set(
+    mock_get_spark_session,
+):
+    mock_spark_session = MagicMock()
+    mock_get_spark_session.return_value = mock_spark_session
+
+    test_repo_config = RepoConfig(
+        project="test_project",
+        registry="test_registry",
+        provider="local",
+        offline_store=SparkOfflineStoreConfig(type="spark"),
+    )
+
+    test_data_source = SparkSource(
+        name="test_nested_batch_source",
+        description="test_nested_batch_source",
+        table="offline_store_database_name.offline_store_table_name",
+        timestamp_field="nested_timestamp",
+        field_mapping={
+            "event_header.event_published_datetime_utc": "nested_timestamp",
+        },
+        date_partition_column="effective_date",
+    )
+
+    # Define the parameters for the method
+    join_key_columns = ["key1", "key2"]
+    feature_name_columns = ["feature1", "feature2"]
+    timestamp_field = "event_header.event_published_datetime_utc"
+    created_timestamp_column = "created_timestamp"
+    start_date = datetime(2021, 1, 1)
+    end_date = datetime(2021, 1, 2)
+
+    # Call the method
+    retrieval_job = SparkOfflineStore.pull_latest_from_table_or_query(
+        config=test_repo_config,
+        data_source=test_data_source,
+        join_key_columns=join_key_columns,
+        feature_name_columns=feature_name_columns,
+        timestamp_field=timestamp_field,
+        created_timestamp_column=created_timestamp_column,
+        start_date=start_date,
+        end_date=end_date,
+    )
+
+    expected_query = """SELECT
+                    key1, key2, feature1, feature2, nested_timestamp, created_timestamp
+                    
+                FROM (
+                    SELECT key1, key2, feature1, feature2, event_header.event_published_datetime_utc AS nested_timestamp, created_timestamp,
+                    ROW_NUMBER() OVER(PARTITION BY key1, key2 ORDER BY event_header.event_published_datetime_utc DESC, created_timestamp DESC) AS feast_row_
+                    FROM `offline_store_database_name`.`offline_store_table_name` t1
+                    WHERE event_header.event_published_datetime_utc BETWEEN TIMESTAMP('2021-01-01 00:00:00.000000') AND TIMESTAMP('2021-01-02 00:00:00.000000') AND effective_date >= '2021-01-01' AND effective_date <= '2021-01-02' 
+                ) t2
+                WHERE feast_row_ = 1"""  # noqa: W293, W291
+
+    assert isinstance(retrieval_job, RetrievalJob)
+    assert retrieval_job.query.strip() == expected_query.strip()
+
+
 @patch(
     "feast.infra.offline_stores.contrib.spark_offline_store.spark.get_spark_session_or_start_new_with_repoconfig"
 )
@@ -127,3 +189,62 @@ def test_pull_latest_from_table_without_nested_timestamp_or_query(
 
     assert isinstance(retrieval_job, RetrievalJob)
     assert retrieval_job.query.strip() == expected_query.strip()
+
+
+@patch(
+    "feast.infra.offline_stores.contrib.spark_offline_store.spark.get_spark_session_or_start_new_with_repoconfig"
+)
+def test_pull_latest_from_table_without_nested_timestamp_or_query_and_date_partition_column_set(
+    mock_get_spark_session,
+):
+    mock_spark_session = MagicMock()
+    mock_get_spark_session.return_value = mock_spark_session
+
+    test_repo_config = RepoConfig(
+        project="test_project",
+        registry="test_registry",
+        provider="local",
+        offline_store=SparkOfflineStoreConfig(type="spark"),
+    )
+
+    test_data_source = SparkSource(
+        name="test_batch_source",
+        description="test_nested_batch_source",
+        table="offline_store_database_name.offline_store_table_name",
+        timestamp_field="event_published_datetime_utc",
+        date_partition_column="effective_date",
+    )
+
+    # Define the parameters for the method
+    join_key_columns = ["key1", "key2"]
+    feature_name_columns = ["feature1", "feature2"]
+    timestamp_field = "event_published_datetime_utc"
+    created_timestamp_column = "created_timestamp"
+    start_date = datetime(2021, 1, 1)
+    end_date = datetime(2021, 1, 2)
+
+    # Call the method
+    retrieval_job = SparkOfflineStore.pull_latest_from_table_or_query(
+        config=test_repo_config,
+        data_source=test_data_source,
+        join_key_columns=join_key_columns,
+        feature_name_columns=feature_name_columns,
+        timestamp_field=timestamp_field,
+        created_timestamp_column=created_timestamp_column,
+        start_date=start_date,
+        end_date=end_date,
+    )
+
+    expected_query = """SELECT
+                    key1, key2, feature1, feature2, event_published_datetime_utc, created_timestamp
+                    
+                FROM (
+                    SELECT key1, key2, feature1, feature2, event_published_datetime_utc, created_timestamp,
+                    ROW_NUMBER() OVER(PARTITION BY key1, key2 ORDER BY event_published_datetime_utc DESC, created_timestamp DESC) AS feast_row_
+                    FROM `offline_store_database_name`.`offline_store_table_name` t1
+                    WHERE event_published_datetime_utc BETWEEN TIMESTAMP('2021-01-01 00:00:00.000000') AND TIMESTAMP('2021-01-02 00:00:00.000000') AND effective_date >= '2021-01-01' AND effective_date <= '2021-01-02' 
+                ) t2
+                WHERE feast_row_ = 1"""  # noqa: W293, W291
+
+    assert isinstance(retrieval_job, RetrievalJob)
+    assert retrieval_job.query.strip() == expected_query.strip()