ERR: pivot_table when number of levels larger than int32 range
#### Code Sample, a copy-pastable example if possible

```
import pandas as pd
dat = pd.DataFrame({'ind1':list(range(1337600))*2,'ind2':list(range(3040))*2*440,'count':[1]*2*1337600})
dat.pivot_table(index='ind1',columns='ind2',values='count',aggfunc='count')
```

#### Problem description

Above code raises the following error:

```
  File "..\pandas\core\reshape\reshape.py", line 144, in _make_selectors
    mask = np.zeros(np.prod(self.full_shape), dtype=bool)

ValueError: negative dimensions are not allowed
```

np.prod(self.full_shape) appears to be returning a negative value because the number of unique index combinations is larger than the largest int32 value.

If line 144 were changed to the following, the issue could be fixed:
```
mask = np.zeros(np.prod(self.full_shape,dtype=np.int64), dtype=bool)
```

#### Expected Output
1337600 x 3040 dataframe.

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.4.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 37 Stepping 1, GenuineIntel
byteorder: little
LC_ALL: None
LANG: en
LOCALE: None.None

pandas: 0.22.0
pytest: 3.3.2
pip: 9.0.1
setuptools: 38.4.0
Cython: 0.27.3
numpy: 1.12.1
scipy: 1.0.0
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: 1.6.6
patsy: 0.5.0
dateutil: 2.6.1
pytz: 2017.3
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.4
feather: None
matplotlib: 2.1.2
openpyxl: 2.4.10
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.2
lxml: 4.1.1
bs4: 4.6.0
html5lib: 1.0.1
sqlalchemy: 1.2.1
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>
