MultiIndex.is_unique is unbearably slow

[toobaz]

Code Sample, a copy-pastable example if possible

class Integer(object):

    goal_time = 0.2

    def setup(self):
        self.mi_int = MultiIndex.from_product([np.arange(1000),
                                               np.arange(1000)],
                                              names=['one', 'two'])
        self.obj_index = np.array([(0, 10), (0, 11), (0, 12),
                                   (0, 13), (0, 14), (0, 15),
                                   (0, 16), (0, 17), (0, 18),
                                   (0, 19)], dtype=object)

    def time_get_indexer(self):
        self.mi_int.get_indexer(self.obj_index)

Problem description

Code above is from asv. Running in ipython

i = Integer()
i.setup()
%lprun -f pd.MultiIndex.get_indexer i.time_get_indexer()

shows that half of the time is spent checking uniqueness. This is because MultiIndex.is_unique does not rely on the engine to check uniqueness (while it could).

Will push a fix in few minutes.

Output of pd.show_versions()

INSTALLED VERSIONS

commit: 9e982e1
python: 3.5.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.9.0-6-amd64
machine: x86_64
processor:
byteorder: little
LC_ALL: None
LANG: it_IT.UTF-8
LOCALE: it_IT.UTF-8

pandas: 0.24.0.dev0+116.g9e982e186
pytest: 3.5.0
pip: 9.0.1
setuptools: 39.2.0
Cython: 0.25.2
numpy: 1.14.3
scipy: 0.19.0
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: 1.5.6
patsy: 0.5.0
dateutil: 2.7.3
pytz: 2018.4
blosc: None
bottleneck: 1.2.0dev
tables: 3.3.0
numexpr: 2.6.1
feather: 0.3.1
matplotlib: 2.2.2.post1153+gff6786446
openpyxl: 2.3.0
xlrd: 1.0.0
xlwt: 1.3.0
xlsxwriter: 0.9.6
lxml: 4.1.1
bs4: 4.5.3
html5lib: 0.999999999
sqlalchemy: 1.0.15
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: 0.2.1