BUG: read_sas segfault
### 

- [X] I have checked that this issue has not already been reported.

- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.

- [X] I have confirmed this bug exists on the master branch of pandas.


### Reproducible Example

```python
import pandas as pd

data = pd.read_sas('testdata4_nocompress.sas7bdat', format='sas7bdat', encoding='big5', chunksize=5000)

for d in data:
    print(d)
```


### Issue Description

Hi teams, when I use read_sas to  read my SAS dataset, it always occur segmentation fault in for loop
![error picture](https://user-images.githubusercontent.com/10277744/139206498-d9d080f2-3b7a-4cd7-aef2-3de0b5d604d0.PNG)
 

### Expected Behavior

It should print every chunksize with 5,000 rows in for loop.

### Installed Versions

<details>

INSTALLED VERSIONS
commit : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python : 3.9.1.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.17763
machine : AMD64
processor : Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
byteorder : little
LC_ALL : None
LANG : zh_TW.UTF-8
LOCALE : Chinese (Traditional)_Taiwan.950

pandas : 1.3.4
numpy : 1.21.0
pytz : 2021.1
dateutil : 2.8.1
pip : 20.2.3
setuptools : 49.2.1
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.2
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : None
numexpr : None
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None

</details>
