how to keep nanosecond timestamps?
Hello there, 

I apologize if this a very simple question but what is the best way to store nanoseconds timestamps with `pandas` and `pyarrow`? 

Right now it seems that using the `flavor = 'spark'` keeps the nanosecond precision while the other flavors do not. 

Is that the right way to see things?

Consider this:
```
import pyarrow as pa
import pandas as pd
import numpy as np

pa.__version__

pa.__version__
Out[131]: '0.13.0'

pd.__version__

pd.__version__
Out[128]: '0.24.2'

mydf = pd.DataFrame({'mytime' : [pd.to_datetime('2020-01-01 10:10:10.123456'),
                                pd.to_datetime('2020-01-01 10:10:10.234567')],
                     'value' : [1,2]})

mydf.to_parquet('testfile_spark.pq', engine = 'pyarrow', flavor = 'spark')

mydf.to_parquet('testfile_regular.pq', engine = 'pyarrow', allow_truncated_timestamps = True)

one = pd.read_parquet('testfile_spark.pq')

one.head()
Out[134]: 
                      mytime  value
0 2020-01-01 10:10:10.123456      1
1 2020-01-01 10:10:10.234567      2

two = pd.read_parquet('testfile_regular.pq')

two.head()
Out[136]: 
                   mytime  value
0 2020-01-01 10:10:10.123      1
1 2020-01-01 10:10:10.234      2

```

EDIT
@wesm asked me to post here from https://github.com/apache/arrow/issues/6536
