[SPARK-33983][PYTHON] Update cloudpickle to v1.6.0

### What changes were proposed in this pull request?

This PR proposes to upgrade cloudpickle from 1.5.0 to 1.6.0.
It virtually contains one fix:

cloudpipe/cloudpickle@4510be8

From a cursory look, this isn't a regression, and not even properly supported in Python:

```python
>>> import pickle
>>> pickle.dumps({}.keys())
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: cannot pickle 'dict_keys' object
```

So it seems fine not to backport.

### Why are the changes needed?

To leverage bug fixes from the cloudpickle upstream.

### Does this PR introduce _any_ user-facing change?

No.

### How was this patch tested?

Jenkins build and GitHub actions build will test it out.

Closes #31007 from HyukjinKwon/cloudpickle-upgrade.

Authored-by: HyukjinKwon <gurwls223@apache.org>
Signed-off-by: Dongjoon Hyun <dhyun@apple.com>

python/pyspark/cloudpickle/__init__.py

@@ -4,4 +4,8 @@
 from pyspark.cloudpickle.cloudpickle import *  # noqa
 from pyspark.cloudpickle.cloudpickle_fast import CloudPickler, dumps, dump  # noqa
 
-__version__ = '1.5.0'
+# Conform to the convention used by python serialization libraries, which
+# expose their Pickler subclass at top-level under the  "Pickler" name.
+Pickler = CloudPickler
+
+__version__ = '1.6.0'

python/pyspark/cloudpickle/cloudpickle.py

@@ -88,7 +88,7 @@ def g():
 DEFAULT_PROTOCOL = pickle.HIGHEST_PROTOCOL
 
 # Track the provenance of reconstructed dynamic classes to make it possible to
-# reconstruct instances from the matching singleton class definition when
+# recontruct instances from the matching singleton class definition when
 # appropriate and preserve the usual "isinstance" semantics of Python objects.
 _DYNAMIC_CLASS_TRACKER_BY_CLASS = weakref.WeakKeyDictionary()
 _DYNAMIC_CLASS_TRACKER_BY_ID = weakref.WeakValueDictionary()
@@ -236,7 +236,7 @@ def _extract_code_globals(co):
         out_names = {names[oparg] for _, oparg in _walk_global_ops(co)}
 
         # Declaring a function inside another one using the "def ..."
-        # syntax generates a constant code object corresponding to the one
+        # syntax generates a constant code object corresonding to the one
         # of the nested function's As the nested function may itself need
         # global variables, we need to introspect its code, extract its
         # globals, (look for code object in it's co_consts attribute..) and
@@ -457,7 +457,7 @@ def _is_parametrized_type_hint(obj):
         is_typing = getattr(obj, '__origin__', None) is not None
 
         # typing_extensions.Literal
-        is_literal = getattr(obj, '__values__', None) is not None
+        is_litteral = getattr(obj, '__values__', None) is not None
 
         # typing_extensions.Final
         is_final = getattr(obj, '__type__', None) is not None
@@ -469,7 +469,7 @@ def _is_parametrized_type_hint(obj):
             getattr(obj, '__result__', None) is not None and
             getattr(obj, '__args__', None) is not None
         )
-        return any((is_typing, is_literal, is_final, is_union, is_tuple,
+        return any((is_typing, is_litteral, is_final, is_union, is_tuple,
                     is_callable))
 
     def _create_parametrized_type_hint(origin, args):
@@ -699,7 +699,7 @@ def _make_skel_func(code, cell_count, base_globals=None):
     """
     # This function is deprecated and should be removed in cloudpickle 1.7
     warnings.warn(
-        "A pickle file created using an old (<=1.4.1) version of cloudpickle "
+        "A pickle file created using an old (<=1.4.1) version of cloudpicke "
         "is currently being loaded. This is not supported by cloudpickle and "
         "will break in cloudpickle 1.7", category=UserWarning
     )
@@ -828,3 +828,15 @@ def _get_bases(typ):
         # For regular class objects
         bases_attr = '__bases__'
     return getattr(typ, bases_attr)
+
+
+def _make_dict_keys(obj):
+    return dict.fromkeys(obj).keys()
+
+
+def _make_dict_values(obj):
+    return {i: _ for i, _ in enumerate(obj)}.values()
+
+
+def _make_dict_items(obj):
+    return obj.items()

python/pyspark/cloudpickle/cloudpickle_fast.py

@@ -6,10 +6,11 @@
 is only available for Python versions 3.8+, a lot of backward-compatibility
 code is also removed.
 
-Note that the C Pickler subclassing API is CPython-specific. Therefore, some
+Note that the C Pickler sublassing API is CPython-specific. Therefore, some
 guards present in cloudpickle.py that were written to handle PyPy specificities
 are not present in cloudpickle_fast.py
 """
+import _collections_abc
 import abc
 import copyreg
 import io
@@ -33,8 +34,8 @@
     _typevar_reduce, _get_bases, _make_cell, _make_empty_cell, CellType,
     _is_parametrized_type_hint, PYPY, cell_set,
     parametrized_type_hint_getinitargs, _create_parametrized_type_hint,
-    builtin_code_type
-
+    builtin_code_type,
+    _make_dict_keys, _make_dict_values, _make_dict_items,
 )
 
 
@@ -179,7 +180,7 @@ def _class_getstate(obj):
     clsdict.pop('__weakref__', None)
 
     if issubclass(type(obj), abc.ABCMeta):
-        # If obj is an instance of an ABCMeta subclass, don't pickle the
+        # If obj is an instance of an ABCMeta subclass, dont pickle the
         # cache/negative caches populated during isinstance/issubclass
         # checks, but pickle the list of registered subclasses of obj.
         clsdict.pop('_abc_cache', None)
@@ -400,14 +401,32 @@ def _class_reduce(obj):
     return NotImplemented
 
 
+def _dict_keys_reduce(obj):
+    # Safer not to ship the full dict as sending the rest might
+    # be unintended and could potentially cause leaking of
+    # sensitive information
+    return _make_dict_keys, (list(obj), )
+
+
+def _dict_values_reduce(obj):
+    # Safer not to ship the full dict as sending the rest might
+    # be unintended and could potentially cause leaking of
+    # sensitive information
+    return _make_dict_values, (list(obj), )
+
+
+def _dict_items_reduce(obj):
+    return _make_dict_items, (dict(obj), )
+
+
 # COLLECTIONS OF OBJECTS STATE SETTERS
 # ------------------------------------
 # state setters are called at unpickling time, once the object is created and
 # it has to be updated to how it was at unpickling time.
 
 
 def _function_setstate(obj, state):
-    """Update the state of a dynamic function.
+    """Update the state of a dynaamic function.
 
     As __closure__ and __globals__ are readonly attributes of a function, we
     cannot rely on the native setstate routine of pickle.load_build, that calls
@@ -473,6 +492,10 @@ class CloudPickler(Pickler):
     _dispatch_table[types.MappingProxyType] = _mappingproxy_reduce
     _dispatch_table[weakref.WeakSet] = _weakset_reduce
     _dispatch_table[typing.TypeVar] = _typevar_reduce
+    _dispatch_table[_collections_abc.dict_keys] = _dict_keys_reduce
+    _dispatch_table[_collections_abc.dict_values] = _dict_values_reduce
+    _dispatch_table[_collections_abc.dict_items] = _dict_items_reduce
+
 
     dispatch_table = ChainMap(_dispatch_table, copyreg.dispatch_table)
 
@@ -556,7 +579,7 @@ def dump(self, obj):
         # `dispatch` attribute.  Earlier versions of the protocol 5 CloudPickler
         # used `CloudPickler.dispatch` as a class-level attribute storing all
         # reducers implemented by cloudpickle, but the attribute name was not a
-        # great choice given the meaning of `CloudPickler.dispatch` when
+        # great choice given the meaning of `Cloudpickler.dispatch` when
         # `CloudPickler` extends the pure-python pickler.
         dispatch = dispatch_table
 
@@ -630,7 +653,7 @@ def reducer_override(self, obj):
                 return self._function_reduce(obj)
             else:
                 # fallback to save_global, including the Pickler's
-                # dispatch_table
+                # distpatch_table
                 return NotImplemented
 
     else: