diff --git a/examples/rolling_process_data/README.md b/examples/rolling_process_data/README.md
index 3f1c8768d..6a6af0d3d 100644
--- a/examples/rolling_process_data/README.md
+++ b/examples/rolling_process_data/README.md
@@ -1,2 +1 @@
 # Rolling Process Data
-
diff --git a/examples/rolling_process_data/workflow.py b/examples/rolling_process_data/workflow.py
index d5f7fec10..29b1c19f8 100644
--- a/examples/rolling_process_data/workflow.py
+++ b/examples/rolling_process_data/workflow.py
@@ -38,9 +38,12 @@ class RollingDataWorkflow(object):
                 "start_time": self.start_time,
                 "end_time": self.end_time,
                 "instruments": self.MARKET,
+                "infer_processors": [],
+                "learn_processors": [],
             },
         }
         pre_handler = init_instance_by_config(handler_config)
+        pre_handler.config(dump_all=True)
         pre_handler.to_pickle(path)
 
     def _load_pre_handler(self, path):
@@ -50,8 +53,8 @@ class RollingDataWorkflow(object):
 
     def rolling_process(self):
         self._init_qlib()
-        self._dump_pre_handler("pre_handler.py")
-        pre_handler = self._load_pre_handler("pre_handler.py")
+        self._dump_pre_handler("pre_handler.pkl")
+        pre_handler = self._load_pre_handler("pre_handler.pkl")
 
         train_start_time = (2010, 1, 1)
         train_end_time = (2012, 12, 31)
@@ -72,6 +75,13 @@ class RollingDataWorkflow(object):
                         "end_time": datetime(*test_end_time),
                         "fit_start_time": datetime(*train_start_time),
                         "fit_end_time": datetime(*train_end_time),
+                        "infer_processors": [
+                            {"class":"RobustZScoreNorm", "kwargs": {"fields_group": "feature"}},
+                        ],
+                        "learn_processors": [
+                            {"class": "DropnaLabel"},
+                            {"class": "CSZScoreNorm", "kwargs": {"fields_group": "label"}},
+                        ],
                         "data_loader_kwargs": {
                             "handler_config": pre_handler,
                         },
@@ -87,7 +97,8 @@ class RollingDataWorkflow(object):
 
         dataset = init_instance_by_config(dataset_config)
 
-        for rolling_offset in range(rolling_cnt):
+        for rolling_offset in range(self.rolling_cnt):
+            print(f"===========rolling{rolling_offset} start===========")
             if rolling_offset:
                 dataset.init(
                     handler_kwargs={
@@ -112,6 +123,8 @@ class RollingDataWorkflow(object):
                 )
 
             dtrain, dvalid, dtest = dataset.prepare(["train", "valid", "test"])
+            ## print or dump data
+            print(f"===========rolling{rolling_offset} end===========")
 
 
 if __name__ == "__main__":
diff --git a/qlib/data/dataset/loader.py b/qlib/data/dataset/loader.py
index 539b930ec..1cda5c025 100644
--- a/qlib/data/dataset/loader.py
+++ b/qlib/data/dataset/loader.py
@@ -250,7 +250,9 @@ class DataLoaderDH(DataLoader):
             is_group will be used to describe whether the key of handler_config is group
 
         """
-        if self.is_group:
+        from qlib.data.dataset.handler import DataHandler
+
+        if is_group:
             self.handlers = {
                 grp: init_instance_by_config(config, accept_types=DataHandler) for grp, config in handler_config.items()
             }
@@ -274,5 +276,5 @@ class DataLoaderDH(DataLoader):
                 axis=1,
             )
         else:
-            df = self.handler.fetch(selector=slice(start_time, end_time), level="datetime", **self.fetch_kwargs)
+            df = self.handlers.fetch(selector=slice(start_time, end_time), level="datetime", **self.fetch_kwargs)
         return df