cloudpickle.patch

diff --git a/python/pyspark/cloudpickle.py b/python/pyspark/cloudpickle.py
index 88519d7311..f7ab821b97 100644
--- a/python/pyspark/cloudpickle.py
+++ b/python/pyspark/cloudpickle.py
@@ -72,77 +72,16 @@ else:
     PY3 = True
 
 
-def _make_cell_set_template_code():
-    """Get the Python compiler to emit LOAD_FAST(arg); STORE_DEREF
+def f():
+   cell = None
 
-    Notes
-    -----
-    In Python 3, we could use an easier function:
+   def _stub(value):
+       nonlocal cell
+       cell = value
 
-    .. code-block:: python
+   return _stub
 
-       def f():
-           cell = None
-
-           def _stub(value):
-               nonlocal cell
-               cell = value
-
-           return _stub
-
-        _cell_set_template_code = f()
-
-    This function is _only_ a LOAD_FAST(arg); STORE_DEREF, but that is
-    invalid syntax on Python 2. If we use this function we also don't need
-    to do the weird freevars/cellvars swap below
-    """
-    def inner(value):
-        lambda: cell  # make ``cell`` a closure so that we get a STORE_DEREF
-        cell = value
-
-    co = inner.__code__
-
-    # NOTE: we are marking the cell variable as a free variable intentionally
-    # so that we simulate an inner function instead of the outer function. This
-    # is what gives us the ``nonlocal`` behavior in a Python 2 compatible way.
-    if not PY3:
-        return types.CodeType(
-            co.co_argcount,
-            co.co_nlocals,
-            co.co_stacksize,
-            co.co_flags,
-            co.co_code,
-            co.co_consts,
-            co.co_names,
-            co.co_varnames,
-            co.co_filename,
-            co.co_name,
-            co.co_firstlineno,
-            co.co_lnotab,
-            co.co_cellvars,  # this is the trickery
-            (),
-        )
-    else:
-        return types.CodeType(
-            co.co_argcount,
-            co.co_kwonlyargcount,
-            co.co_nlocals,
-            co.co_stacksize,
-            co.co_flags,
-            co.co_code,
-            co.co_consts,
-            co.co_names,
-            co.co_varnames,
-            co.co_filename,
-            co.co_name,
-            co.co_firstlineno,
-            co.co_lnotab,
-            co.co_cellvars,  # this is the trickery
-            (),
-        )
-
-
-_cell_set_template_code = _make_cell_set_template_code()
+_cell_set_template_code = f()
 
 
 def cell_set(cell, value):

Hi, this solves the error in cloudpickle.py thanks! But when map-reduce functions are used, in serializers.py the error given below comes out :

in loads
return pickle.loads(obj, encoding=encoding)
TypeError: an integer is required (got type bytes)

how can I solve this problem? (Python 3.8.2 with spark-hadoop 2.4.5 )

like in this case https://stackoverflow.com/a/60660577/12100307