SNOW-715862: fetch_pandas_all for large timestamp get out of bound timestmap error

Please answer these questions before submitting your issue. Thanks!

1. What version of Python are you using?
   Python 3.9

2. What operating system and processor architecture are you using?

Ubuntu

3. What are the component versions in the environment (pip freeze)?

snowflake-connector-python==2.8.3

4. What did you do?
   cur.execute("select TO_TIMESTAMP('9999-01-01T00:00:59Z') as d1")
   df = cur.fetch_pandas_all()
   will throw following exception:

File \"/usr/local/lib/python3.9/site-packages/pyarrow/pandas_compat.py\", line 1153, in _table_to_blocks\n    result = pa.lib.table_to_blocks(options, block_table, categories,\n  File \"pyarrow/table.pxi\", line 2602, in pyarrow.lib.table_to_blocks\n  File \"pyarrow/error.pxi\", line 100, in pyarrow.lib.check_status\npyarrow.lib.ArrowInvalid: Casting from timestamp[us] to timestamp[ns] would result in out of bounds timestamp: 253402300799000000"}

5. What did you expect to see?
   fetch_pands_all() should allow all valid timestamp to loaded, for out of bound timestamp, allow a way to return NaT or max Timestamp value

6. Can you set logging to DEBUG and collect the logs?

   import logging
   import os
   
   for logger_name in ('snowflake.connector',):
       logger = logging.getLogger(logger_name)
       logger.setLevel(logging.DEBUG)
       ch = logging.StreamHandler()
       ch.setLevel(logging.DEBUG)
       ch.setFormatter(logging.Formatter('%(asctime)s - %(threadName)s %(filename)s:%(lineno)d - %(funcName)s() - %(levelname)s - %(message)s'))
       logger.addHandler(ch)
   

Start by reproducing the TO_TIMESTAMP query and fetch_pandas_all() call with the listed Python, connector, Ubuntu, and PyArrow environment. Trace the pandas-fetch conversion path that turns the large timestamp into a pandas value, then define and test the expected handling for valid out-of-bounds timestamps, such as NaT or the maximum timestamp.