BUG: The frequency of a DatetimeIndex is lost when using to_parquet with pyarrow
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [x] (optional) I have confirmed this bug exists on the master branch of pandas.

---

#### Code Sample

```python
import pandas as pd

df = pd.DataFrame(
    [1, 2, 3], 
    columns=['a'],
    index=pd.date_range(
        freq="1T", 
        start="2021-01-01 00:00:00", 
        end="2021-01-01 00:02:00"
    )
)

df.to_parquet("test.parquet", engine="pyarrow")

pd.testing.assert_frame_equal(pd.read_parquet("test.parquet", engine="pyarrow"), df)
```
```
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File ".../lib/python3.8/site-packages/pandas/_testing.py", line 1704, in assert_frame_equal
    assert_series_equal(
  File ".../python3.8/site-packages/pandas/_testing.py", line 1389, in assert_series_equal
    assert lidx.freq == ridx.freq, (lidx.freq, ridx.freq)
AssertionError: (None, <Minute>)
```
#### Problem description

With the following versions:
- pandas: 1.2.4
- pyarrow: 4.0.0

The bug is different with fastparquet, but there seem to be also a consistency issue (the index name). 

Which I didn't see in earlier versions of pandas/fastparquet (0.25.3/0.4.1), I didn't try other combinations.
EDIT: _It wasn't happening before most likely because assert_frame_equal wasn't checking the index frequency, not because it was there._

It seems that the index frequency is not passed in the pandas metadata within the table.

Maybe I'm missing a pyarrow option to make this happen, but I still feel like the index should be either discarded completely or kept in a compatible manner.

#### Expected Output

No exception raised and an index with the same attributes as the original one.

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : 2cb96529396d93b46abab7bbc73a208e708c642e
python           : 3.8.8.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.4.0-72-generic
Version          : #80~18.04.1-Ubuntu SMP Mon Apr 12 23:26:25 UTC 2021
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.2.4
numpy            : 1.20.3
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 21.0.1
setuptools       : 52.0.0.post20210125
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : 2021.05.0
fastparquet      : 0.6.3
gcsfs            : None
matplotlib       : None
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 4.0.0
pyxlsb           : None
s3fs             : None
scipy            : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
