diff --git a/data-processing-lib/spark/src/data_processing_spark/runtime/spark/transform_runtime.py b/data-processing-lib/spark/src/data_processing_spark/runtime/spark/transform_runtime.py
index 1f3d671a5..7b968b1e9 100644
--- a/data-processing-lib/spark/src/data_processing_spark/runtime/spark/transform_runtime.py
+++ b/data-processing-lib/spark/src/data_processing_spark/runtime/spark/transform_runtime.py
@@ -34,9 +34,7 @@ def get_transform_config(
         """
         Get the dictionary of configuration that will be provided to the transform's initializer.
         This is the opportunity for this runtime to create a new set of configuration based on the
-        config/params provided to this instance's initializer.  This may include the addition
-        of new configuration data such as ray shared memory, new actors, etc, that might be needed and
-        expected by the transform in its initializer and/or transform() methods.
+        config/params provided to this instance's initializer.
         :param partition - the partition assigned to this worker, needed by transforms like doc_id
         :param data_access_factory - data access factory class being used by the RayOrchestrator.
         :param statistics - reference to statistics actor
@@ -57,7 +55,8 @@ def get_bcast_params(self, data_access_factory: DataAccessFactoryBase) -> dict[s
     def compute_execution_stats(self, stats: TransformStatistics) -> None:
         """
         Update/augment the given statistics object with runtime-specific additions/modifications.
+        This method does not return a value; the job execution statistics are generally reported
+        as metadata by the Spark Orchestrator.
         :param stats: output of statistics as aggregated across all calls to all transforms.
-        :return: job execution statistics.  These are generally reported as metadata by the Ray Orchestrator.
         """
         pass