PERF: Index joins slower than expected
I was playing around with indexes today and noticed something a bit unusual.  When joining two `Int64Indexes` containing random integers, a left join is an order of magnitude _faster_ than an inner join (I would expect either no difference or the opposite).  Maybe a bit more surprising, joining two `RangeIndexes` takes _longer_ than joining two `Int64Indexes`.  I find this odd because `RangeIndexes` could in theory be joined instantly by looking only at their endpoints and step sizes.

```
import numpy as np
import pandas as pd

np.random.seed(2357)

idx0 = pd.Index(np.random.permutation(10**6))
idx1 = pd.Index(np.random.permutation(10**6))
idx2 = pd.RangeIndex(10**6)
idx3 = pd.RangeIndex(10**6)

%timeit idx0.join(idx1, how="left")
%timeit idx0.join(idx1, how="inner")

%timeit idx2.join(idx3, how="left")
%timeit idx2.join(idx3, how="inner")
```

<details>

[paste the output of ``pd.show_versions()`` here below this line]
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.5.final.0
python-bits: 64
OS: Darwin
OS-release: 17.7.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.23.4
pytest: 3.7.2
pip: 18.1
setuptools: 40.2.0
Cython: 0.28.2
numpy: 1.14.4
scipy: 1.1.0
pyarrow: 0.11.0
xarray: None
IPython: 6.4.0
sphinx: 1.8.0
patsy: 0.5.0
dateutil: 2.7.3
pytz: 2018.4
blosc: None
bottleneck: 1.2.1
tables: 3.4.3
numexpr: 2.6.5
feather: None
matplotlib: 3.0.0
openpyxl: 2.5.3
xlrd: 1.1.0
xlwt: 1.2.0
xlsxwriter: 1.0.4
lxml: 4.2.1
bs4: 4.6.0
html5lib: 1.0.1
sqlalchemy: 1.1.13
pymysql: 0.8.1
psycopg2: 2.7.5 (dt dec pq3 ext lo64)
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>