BUG: Integral truediv and floordiv with pyarrow types overflows with large divisor

[rohanjain101]

Pandas version checks

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

>>> a = pd.Series([0], dtype="int64[pyarrow]")
>>> b = pd.Series([18014398509481983], dtype="int64[pyarrow]")
>>> a / b
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "D:\pandasdev\pandas\core\ops\common.py", line 76, in new_method
    return method(self, other)
           ^^^^^^^^^^^^^^^^^^^
  File "D:\pandasdev\pandas\core\arraylike.py", line 210, in __truediv__
    return self._arith_method(other, operator.truediv)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\pandasdev\pandas\core\series.py", line 5995, in _arith_method
    return base.IndexOpsMixin._arith_method(self, other, op)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\pandasdev\pandas\core\base.py", line 1382, in _arith_method
    result = ops.arithmetic_op(lvalues, rvalues, op)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\pandasdev\pandas\core\ops\array_ops.py", line 273, in arithmetic_op
    res_values = op(left, right)
                 ^^^^^^^^^^^^^^^
  File "D:\pandasdev\pandas\core\ops\common.py", line 76, in new_method
    return method(self, other)
           ^^^^^^^^^^^^^^^^^^^
  File "D:\pandasdev\pandas\core\arraylike.py", line 210, in __truediv__
    return self._arith_method(other, operator.truediv)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\pandasdev\pandas\core\arrays\arrow\array.py", line 764, in _arith_method
    return self._evaluate_op_method(other, op, ARROW_ARITHMETIC_FUNCS)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\pandasdev\pandas\core\arrays\arrow\array.py", line 752, in _evaluate_op_method
    result = pc_func(self._pa_array, other)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\pandasdev\pandas\core\arrays\arrow\array.py", line 145, in <lambda>
    "truediv": lambda x, y: pc.divide(cast_for_truediv(x, y), y),
                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\pd_dev_1203\Lib\site-packages\pyarrow\compute.py", line 246, in wrapper
    return func.call(args, None, memory_pool)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "pyarrow\_compute.pyx", line 385, in pyarrow._compute.Function.call
  File "pyarrow\error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
  File "pyarrow\error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Integer value 18014398509481983 not in range: -9007199254740992 to 9007199254740992
>>> a // b
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "D:\pandasdev\pandas\core\ops\common.py", line 76, in new_method
    return method(self, other)
           ^^^^^^^^^^^^^^^^^^^
  File "D:\pandasdev\pandas\core\arraylike.py", line 218, in __floordiv__
    return self._arith_method(other, operator.floordiv)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\pandasdev\pandas\core\series.py", line 5995, in _arith_method
    return base.IndexOpsMixin._arith_method(self, other, op)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\pandasdev\pandas\core\base.py", line 1382, in _arith_method
    result = ops.arithmetic_op(lvalues, rvalues, op)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\pandasdev\pandas\core\ops\array_ops.py", line 273, in arithmetic_op
    res_values = op(left, right)
                 ^^^^^^^^^^^^^^^
  File "D:\pandasdev\pandas\core\ops\common.py", line 76, in new_method
    return method(self, other)
           ^^^^^^^^^^^^^^^^^^^
  File "D:\pandasdev\pandas\core\arraylike.py", line 218, in __floordiv__
    return self._arith_method(other, operator.floordiv)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\pandasdev\pandas\core\arrays\arrow\array.py", line 764, in _arith_method
    return self._evaluate_op_method(other, op, ARROW_ARITHMETIC_FUNCS)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\pandasdev\pandas\core\arrays\arrow\array.py", line 752, in _evaluate_op_method
    result = pc_func(self._pa_array, other)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\pandasdev\pandas\core\arrays\arrow\array.py", line 147, in <lambda>
    "floordiv": lambda x, y: floordiv_compat(x, y),
                             ^^^^^^^^^^^^^^^^^^^^^
  File "D:\pandasdev\pandas\core\arrays\arrow\array.py", line 133, in floordiv_compat
    result = pc.floor(pc.divide(converted_left, right))
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "D:\pd_dev_1203\Lib\site-packages\pyarrow\compute.py", line 246, in wrapper
    return func.call(args, None, memory_pool)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "pyarrow\_compute.pyx", line 385, in pyarrow._compute.Function.call
  File "pyarrow\error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
  File "pyarrow\error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Integer value 18014398509481983 not in range: -9007199254740992 to 9007199254740992
>>>

Issue Description

An error is raised.

Expected Behavior

Behavior with numpy types:

>>> a = pd.Series([0], dtype="int64")
>>> b = pd.Series([18014398509481983], dtype="int64")
>>> a / b
0    0.0
dtype: float64
>>> a // b
0    0
dtype: int64
>>>

Installed Versions

INSTALLED VERSIONS

commit : f0b61c5
python : 3.11.4.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.22631
machine : AMD64
processor : Intel64 Family 6 Model 151 Stepping 2, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_United States.1252

pandas : 2.1.0.dev0+2318.gf0b61c5618
numpy : 1.26.2
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 68.2.2
pip : 23.3.1
Cython : 3.0.5
pytest : 7.4.4
hypothesis : 6.91.0
sphinx : 6.2.1
blosc : 1.11.1
feather : None
xlsxwriter : 3.1.9
lxml.etree : 4.9.3
html5lib : 1.1
pymysql : 1.4.6
psycopg2 : 2.9.9
jinja2 : 3.1.2
IPython : 8.18.1
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.2
bottleneck : 1.3.7
dataframe-api-compat : None
fastparquet : 2023.10.1
fsspec : 2023.12.0
gcsfs : 2023.12.0
matplotlib : 3.8.2
numba : 0.58.1
numexpr : 2.8.7
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : 14.0.1
pyreadstat : 1.2.5
python-calamine : None
pyxlsb : 1.0.10
s3fs : 2023.12.0
scipy : 1.11.4
sqlalchemy : 2.0.23
tables : 3.9.2
tabulate : 0.9.0
xarray : 2023.11.0
xlrd : 2.0.1
zstandard : 0.22.0
tzdata : 2023.3
qtpy : None
pyqt5 : None