diff --git a/python/pyspark/sql/worker/plan_data_source_read.py b/python/pyspark/sql/worker/plan_data_source_read.py
index ed1c602b0af4b..32f22c7b03b10 100644
--- a/python/pyspark/sql/worker/plan_data_source_read.py
+++ b/python/pyspark/sql/worker/plan_data_source_read.py
@@ -220,6 +220,11 @@ def data_source_read_func(iterator: Iterable[pa.RecordBatch]) -> Iterable[pa.Rec
 
         return records_to_arrow_batches(output_iter, max_arrow_batch_size, return_type, data_source)
 
+    # Set the module name so UDF worker can recognize that this is a data source function.
+    # This is needed when simple worker is used because the __module__ will be set to
+    # __main__, which confuses the profiler logic.
+    data_source_read_func.__module__ = "pyspark.sql.worker.plan_data_source_read"
+
     command = (data_source_read_func, return_type)
     pickleSer._write_with_length(command, outfile)
 
diff --git a/python/pyspark/sql/worker/utils.py b/python/pyspark/sql/worker/utils.py
index 8a99abe3e4e9a..406894fc275a6 100644
--- a/python/pyspark/sql/worker/utils.py
+++ b/python/pyspark/sql/worker/utils.py
@@ -70,7 +70,15 @@ def worker_run(main: Callable, infile: IO, outfile: IO) -> None:
             SpecialAccumulatorIds.SQL_UDF_PROFIER, None, ProfileResultsParam
         )
 
-        worker_module = main.__module__.split(".")[-1]
+        if main.__module__ == "__main__":
+            try:
+                worker_module = sys.modules["__main__"].__spec__.name  # type: ignore[union-attr]
+            except Exception:
+                worker_module = "__main__"
+        else:
+            worker_module = main.__module__
+        worker_module = worker_module.split(".")[-1]
+
         if conf.profiler == "perf":
             with WorkerPerfProfiler(accumulator, worker_module):
                 main(infile, outfile)
diff --git a/python/pyspark/sql/worker/write_into_data_source.py b/python/pyspark/sql/worker/write_into_data_source.py
index 111829bb7d58f..c808661fedb72 100644
--- a/python/pyspark/sql/worker/write_into_data_source.py
+++ b/python/pyspark/sql/worker/write_into_data_source.py
@@ -228,6 +228,11 @@ def batch_to_rows() -> Iterator[Row]:
         messages = pa.array([pickled])
         yield pa.record_batch([messages], names=[return_col_name])
 
+    # Set the module name so UDF worker can recognize that this is a data source function.
+    # This is needed when simple worker is used because the __module__ will be set to
+    # __main__, which confuses the profiler logic.
+    data_source_write_func.__module__ = "pyspark.sql.worker.write_into_data_source"
+
     # Return the pickled write UDF.
     command = (data_source_write_func, return_type)
     pickleSer._write_with_length(command, outfile)