Joining an empty DataFrame with 'on' argument can result in an invalid DataFrame
#### Code Sample, a copy-pastable example if possible

```python
import pandas as pd

left = pd.DataFrame(
    [(11, 21, 31),
     (11, 22, 32),
     (11, 23, 33),
     (12, 21, 34),
     (12, 22, 35)],
    columns=['A', 'B', 'C'])

right1 = pd. DataFrame(
    [(11, 22, 41, 51),
     (11, 23, 42, 52),
     (12, 23, 43, 53)],
    columns=['A', 'B', 'D', 'E'])

right2 = pd. DataFrame(
    [(11, 22, 61),
     (12, 21, 62),
     (12, 23, 63)],
    columns=['A', 'B', 'F'])

inner1 = left.join(right1.set_index(['A', 'B']), how='inner', on=['A', 'B'])

print("INNER1")
print(inner1)
print("  INDEX")
print(inner1.index)
print("  JSON")
print(inner1.to_json(orient='table'))
print()

inner1.reset_index()

inner2 = inner1.join(right2.set_index(['A', 'B']), how='inner', on=['A', 'B'])

print("INNER2")
print(inner2)
print("  INDEX")
print(inner2.index)
print("  JSON")
print(inner2.to_json(orient='table'))
print()

empty_left = left.drop(index=left.index)

empty_inner1 = empty_left.join(right1.set_index(['A', 'B']), how='inner', on=['A', 'B'])

print("EMPTY_INNER1")
print(empty_inner1)
print("  INDEX")
print(empty_inner1.index)
print()

# OUTPUT:
#
# EMPTY_INNER1
# Empty DataFrame
# Columns: [A, B, C, D, E]
# Index: []
#   INDEX
# MultiIndex(levels=[[11, 12], [22, 23]],
#           codes=[[], []],
#           names=['A', 'B'])
#
# PROBLEM:
#
# Because of this code in _MergeOperation._get_join_info
#
#            if self.right_index:
#                if len(self.left) > 0:
#                    join_index = self._create_join_index(self.left.index,
#                                                         self.right.index,
#                                                         left_indexer,
#                                                         right_indexer,
#                                                         how='right')
#                else:
#                    join_index = self.right.index.take(right_indexer)
#                    left_indexer = np.array([-1] * len(join_index))
#
# the join_index is based on self.right.index when len(self.left) == 0, but
# the "result" table should have an unnamed default index (like the "left" table),
# not a named MultiIndex.  The 'names' in particular are the bad state because
# those names are still column names in the result table.  This causes the following
# three independent operations, at least, to completely fail because of validation.

# OPERATION 1:
#
# print("  JSON")
# print(empty_inner1.to_json(orient='table'))
#
# FAILS WITH:
#  File ".../pandas/io/json/json.py", line 197, in __init__
#     raise ValueError(msg)
# ValueError: Overlapping names between the index and columns
#

# OPERATION 2:
#
# empty_inner1.reset_index()
#
# FAILS WITH:
#   File ".../pandas/core/internals/managers.py", line 1149, in insert
#     raise ValueError('cannot insert {}, already exists'.format(item))
# ValueError: cannot insert B, already exists
# 

# OPERATION 3:
#
# empty_inner2 = empty_inner1.join(right2.set_index(['A', 'B']), how='inner', on=['A', 'B'])
#
# FAILS WITH:
#   File "...pandas/core/generic.py", line 1656, in _check_label_or_level_ambiguity
#     raise ValueError(msg)
# ValueError: 'A' is both an index level and a column label, which is ambiguous.
```
#### Problem description

Joining an empty dataframe using the 'on' argument, can return a result dataframe that is INVALID because it is incorrectly given an indexed based on the the 'right' table ('join' requires that the 'right' table has an index that corresponds to the 'on' argument).

I verified this on 'master' (0.25.0.dev0), too.

#### Expected Output

```python
EMPTY_INNER1
Empty DataFrame
Columns: [A, B, C, D, E]
Index: []
  INDEX
Int64Index([], dtype='int64')
```

or

```python
EMPTY_INNER1
Empty DataFrame
Columns: [A, B, C, D, E]
Index: []
  INDEX
Index([], dtype='object')
```

Also, the subsequent 'to_json', 'reset_index', and 'join' operations should not raise exceptions.

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.7.3.final.0
python-bits: 64
OS: Darwin
OS-release: 17.5.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.24.1
pytest: 4.3.0
pip: 19.0.3
setuptools: 40.8.0
Cython: None
numpy: 1.16.1
scipy: 1.2.1
pyarrow: None
xarray: None
IPython: None
sphinx: None
patsy: None
dateutil: 2.8.0
pytz: 2018.9
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 3.0.2
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml.etree: 4.3.3
bs4: None
html5lib: 1.0.1
sqlalchemy: 1.2.19
pymysql: None
psycopg2: 2.8.2 (dt dec pq3 ext lo64)
jinja2: 2.10.1
s3fs: None
fastparquet: None
pandas_gbq: 0.10.0
pandas_datareader: None
gcsfs: None

</details>