BUG: groupby.rolling.cov/corr(other) with len(group) != len(other) introduces extra NaN group results

[mroeschke]

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the master branch of pandas.

Reproducible Example

>>> df_a = pd.DataFrame({"value": range(10), "idx1": [1] * 5 + [2] * 5, "idx2": [1, 2, 3, 4, 5] * 2}).set_index(["idx1", "idx2"])
>>> df_b = pd.DataFrame({"value": range(5), "idx2": [1, 2, 3, 4, 5]}).set_index("idx2")
>>> df_a[:-1].groupby(level=0).rolling(2).cov(df_b)
                value
idx1 idx1 idx2       
1    1    1       NaN
          2       0.5
          3       0.5
          4       0.5
          5       0.5
     2    1       NaN
          2       NaN
          3       NaN
          4       NaN
2    1    1       NaN
          2       NaN
          3       NaN
          4       NaN
          5       NaN
     2    1       NaN
          2       0.5
          3       0.5
          4       0.5

Issue Description

xref: #44824 (comment)

Extra groups are introduced.

Expected Behavior

           value
idx1 idx2
1    1       NaN
     2       0.5
     3       0.5
     4       0.5
     5       0.5
2    1       NaN
     2       0.5
     3       0.5
     4       0.5

Installed Versions

INSTALLED VERSIONS

commit : 193ca73
python : 3.8.12.final.0
python-bits : 64
OS : Darwin
OS-release : 19.6.0
Version : Darwin Kernel Version 19.6.0: Tue Oct 12 18:34:05 PDT 2021; root:xnu-6153.141.43~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.4.0.dev0+1365.g193ca730d0
numpy : 1.21.4
pytz : 2021.3
dateutil : 2.8.2
pip : 21.3.1
setuptools : 59.1.0
Cython : 0.29.24
pytest : 6.2.5
hypothesis : 6.27.1
sphinx : 4.3.0
blosc : None
feather : None
xlsxwriter : 3.0.2
lxml.etree : 4.6.4
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.0.3
IPython : 7.29.0
pandas_datareader: None
bs4 : 4.10.0
bottleneck : 1.3.2
fsspec : 2021.11.0
fastparquet : 0.7.1
gcsfs : 2021.11.0
matplotlib : 3.4.3
numexpr : 2.7.3
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : 6.0.0
pyxlsb : None
s3fs : 2021.11.0
scipy : 1.7.2
sqlalchemy : 1.4.27
tables : 3.6.1
tabulate : 0.8.9
xarray : 0.18.2
xlrd : 2.0.1
xlwt : 1.3.0
numba : 0.53.1

[fbourgey]

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