diff --git a/qlib/data/dataset/handler.py b/qlib/data/dataset/handler.py
index eab889e85..bb1da2754 100644
--- a/qlib/data/dataset/handler.py
+++ b/qlib/data/dataset/handler.py
@@ -257,7 +257,7 @@ class DataHandler(Serializable):
                     selector=selector, level=level, col_set=col_set, fetch_orig=self.fetch_orig, proc_func=proc_func
                 )
         else:
-            raise TypeError(f"data_storage should be pd.DataFrame|HasingStockStorage, not {type(data_storage)}")
+            raise TypeError(f"data_storage should be pd.DataFrame|HashingStockStorage, not {type(data_storage)}")
 
         if squeeze:
             # squeeze columns
diff --git a/qlib/data/dataset/processor.py b/qlib/data/dataset/processor.py
index ec3fa5506..6381937d3 100644
--- a/qlib/data/dataset/processor.py
+++ b/qlib/data/dataset/processor.py
@@ -349,6 +349,6 @@ class HashStockFormat(Processor):
     """Process the storage of from df into hasing stock format"""
 
     def __call__(self, df: pd.DataFrame):
-        from .storage import HasingStockStorage  # pylint: disable=C0415
+        from .storage import HashingStockStorage  # pylint: disable=C0415
 
-        return HasingStockStorage.from_df(df)
+        return HashingStockStorage.from_df(df)
diff --git a/qlib/data/dataset/storage.py b/qlib/data/dataset/storage.py
index 42f003269..a8ccdadaa 100644
--- a/qlib/data/dataset/storage.py
+++ b/qlib/data/dataset/storage.py
@@ -59,11 +59,11 @@ class BaseHandlerStorage:
         raise NotImplementedError("is_proc_func_supported method is not implemented!")
 
 
-class HasingStockStorage(BaseHandlerStorage):
-    """Hasing data storage for datahanlder
+class HashingStockStorage(BaseHandlerStorage):
+    """Hashing data storage for datahanlder
     - The default data storage pandas.DataFrame is too slow when randomly accessing one stock's data
-    - HasingStockStorage hashes the multiple stocks' data(pandas.DataFrame) by the key `stock_id`.
-    - HasingStockStorage hashes the pandas.DataFrame into a dict, whose key is the stock_id(str) and value this stock data(panda.DataFrame), it has the following format:
+    - HashingStockStorage hashes the multiple stocks' data(pandas.DataFrame) by the key `stock_id`.
+    - HashingStockStorage hashes the pandas.DataFrame into a dict, whose key is the stock_id(str) and value this stock data(panda.DataFrame), it has the following format:
         {
             stock1_id: stock1_data,
             stock2_id: stock2_data,
@@ -82,7 +82,7 @@ class HasingStockStorage(BaseHandlerStorage):
 
     @staticmethod
     def from_df(df):
-        return HasingStockStorage(df)
+        return HashingStockStorage(df)
 
     def _fetch_hash_df_by_stock(self, selector, level):
         """fetch the data with stock selector
@@ -153,5 +153,5 @@ class HasingStockStorage(BaseHandlerStorage):
             return pd.concat(fetch_stock_df_list, sort=False, copy=~fetch_orig)
 
     def is_proc_func_supported(self):
-        """the arg `proc_func` in `fetch` method is not supported in HasingStockStorage"""
+        """the arg `proc_func` in `fetch` method is not supported in HashingStockStorage"""
         return False
diff --git a/tests/test_handler_storage.py b/tests/test_handler_storage.py
index 056595063..0d8ad4d57 100644
--- a/tests/test_handler_storage.py
+++ b/tests/test_handler_storage.py
@@ -95,7 +95,7 @@ class TestHandlerStorage(TestAutoData):
                 fetch_stocks = [instruments[_index] for _index in random_indexs]
                 data_handler.fetch(selector=(fetch_stocks, slice(fetch_start_time, fetch_end_time)), level=None)
 
-        with TimeInspector.logt("random fetch with HasingStock Storage"):
+        with TimeInspector.logt("random fetch with HashingStock Storage"):
 
             # single stock
             for i in range(100):