COMPAT: infer larger than unit64 to object dtype
#### Code Sample, a copy-pastable example if possible

```python
# Your code here
querySql = "select col1 from Table1" # col1 is NUMBER(20) in the oracle databse, example: 20124400100030425447
df = pd.read_sql(querySql, db)  # db is the oracle connection
```
#### Problem description
raise "OverflowError: long too big to convert", it may be the uint64 problem?
```
In [1]: import cx_Oracle

In [2]: db = cx_Oracle.connect(user='TEST', password='0000', dsn='localhost:1521/orcl')

In [3]: import pandas as pd

In [4]: df = pd.read_sql('select col1 from TABLE1',db)
---------------------------------------------------------------------------
OverflowError                             Traceback (most recent call last)
<ipython-input-4-318bf64d0a9b> in <module>()
----> 1 df = pd.read_sql('select col1 from TABLE1',db)

C:\Program Files\Anaconda\lib\site-packages\pandas\io\sql.pyc in read_sql(sql, con, index_col, coerce_float, params, parse_dates, colu
mns, chunksize)
    398             sql, index_col=index_col, params=params,
    399             coerce_float=coerce_float, parse_dates=parse_dates,
--> 400             chunksize=chunksize)
    401
    402     try:

C:\Program Files\Anaconda\lib\site-packages\pandas\io\sql.pyc in read_query(self, sql, index_col, coerce_float, params, parse_dates, c
hunksize)
   1456             frame = _wrap_result(data, columns, index_col=index_col,
   1457                                  coerce_float=coerce_float,
-> 1458                                  parse_dates=parse_dates)
   1459             return frame
   1460

C:\Program Files\Anaconda\lib\site-packages\pandas\io\sql.pyc in _wrap_result(data, columns, index_col, coerce_float, parse_dates)
    155
    156     frame = DataFrame.from_records(data, columns=columns,
--> 157                                    coerce_float=coerce_float)
    158
    159     _parse_date_columns(frame, parse_dates)

C:\Program Files\Anaconda\lib\site-packages\pandas\core\frame.pyc in from_records(cls, data, index, exclude, columns, coerce_float, nr
ows)
   1140         else:
   1141             arrays, arr_columns = _to_arrays(data, columns,
-> 1142                                              coerce_float=coerce_float)
   1143
   1144             arr_columns = _ensure_index(arr_columns)

C:\Program Files\Anaconda\lib\site-packages\pandas\core\frame.pyc in _to_arrays(data, columns, coerce_float, dtype)
   6249     if isinstance(data[0], (list, tuple)):
   6250         return _list_to_arrays(data, columns, coerce_float=coerce_float,
-> 6251                                dtype=dtype)
   6252     elif isinstance(data[0], collections.Mapping):
   6253         return _list_of_dict_to_arrays(data, columns,

C:\Program Files\Anaconda\lib\site-packages\pandas\core\frame.pyc in _list_to_arrays(data, columns, coerce_float, dtype)
   6328         content = list(lib.to_object_array(data).T)
   6329     return _convert_object_array(content, columns, dtype=dtype,
-> 6330                                  coerce_float=coerce_float)
   6331
   6332

C:\Program Files\Anaconda\lib\site-packages\pandas\core\frame.pyc in _convert_object_array(content, columns, coerce_float, dtype)
   6394         return arr
   6395
-> 6396     arrays = [convert(arr) for arr in content]
   6397
   6398     return arrays, columns

C:\Program Files\Anaconda\lib\site-packages\pandas\core\frame.pyc in convert(arr)
   6390     def convert(arr):
   6391         if dtype != object and dtype != np.object:
-> 6392             arr = lib.maybe_convert_objects(arr, try_float=coerce_float)
   6393             arr = maybe_cast_to_datetime(arr, dtype)
   6394         return arr

pandas/_libs/src\inference.pyx in pandas._libs.lib.maybe_convert_objects()

OverflowError: long too big to convert
```
#### Expected Output

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.13.final.0
python-bits: 64
OS: Windows
OS-release: 8.1
machine: AMD64
processor: Intel64 Family 6 Model 58 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.21.0
pytest: 3.0.7
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.13.3
scipy: 0.19.0
pyarrow: None
xarray: None
IPython: 5.3.0
sphinx: 1.5.6
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.3
blosc: None
bottleneck: 1.2.1
tables: 3.2.2
numexpr: 2.6.2
feather: None
matplotlib: 2.0.2
openpyxl: 2.4.7
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: 0.9.6
lxml: 3.7.3
bs4: 4.6.0
html5lib: 0.999
sqlalchemy: 1.1.9
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>
