BUG: Wrong result after comparison SparseArray with arrays

[bdrum]

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• 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

s = pd.arrays.SparseArray([1, 2, 3, 4, np.nan, np.nan], fill_value=np.nan)
s > [3,3,4,1,0,0]
# [False, False, False, True, False, False]
# Fill: False
# IntIndex
# Indices: array([0, 1, 2, 3, 4, 5], dtype=int32)

Issue Description

This issue is the consequence of global problem described in #45126.

The other part of the issue (comparison with scalars) already solved and merged: #44956, #45110.

I've separated this issue due to discussion in #45125.

In the mentioned pr I've also added two test and marked their as xfail in tests/extension/test_sparse.py:
TestComparisonOps::test_array
TestComparisonOps::test_sparse_array

Please pay attention that now boolean mask for SparseArray based on indices, i.e. such construction:

s = pd.arrays.SparseArray([1, 2, 3, 4, np.nan, np.nan], fill_value=np.nan)
s[s > [3,3,4,1,0,0]]

will return wrong result:

[1.0, 2.0, 3.0, 4.0, nan, nan]
Fill: nan
IntIndex
Indices: array([0, 1, 2, 3], dtype=int32)

instead of

[4.0]
Fill: nan
IntIndex
Indices: array([0], dtype=int32)

Expected Behavior

s = pd.arrays.SparseArray([1, 2, 3, 4, np.nan, np.nan], fill_value=np.nan)
s > [3,3,4,1,0,0]
# [False, False, False, True, False, False]
# Fill: False
# IntIndex
# Indices: array([3], dtype=int32)

Installed Versions

INSTALLED VERSIONS

commit : ccb25ab
python : 3.8.12.final.0
python-bits : 64
OS : Linux
OS-release : 5.10.60.1-microsoft-standard-WSL2
Version : #1 SMP Wed Aug 25 23:20:18 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : C.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.4.0.dev0+1613.gccb25ab1d2
numpy : 1.22.0
pytz : 2021.3
dateutil : 2.8.2
pip : 21.3.1
setuptools : 58.0.4
Cython : 0.29.26
pytest : 6.2.5
hypothesis : 6.34.2
sphinx : 4.3.2
blosc : None
feather : None
xlsxwriter : 3.0.2
lxml.etree : 4.7.1
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.0.3
IPython : 7.30.1
pandas_datareader: None
bs4 : 4.10.0
bottleneck : 1.3.2
fsspec : 2021.11.0
fastparquet : None
gcsfs : 2021.11.0
matplotlib : 3.5.1
numexpr : 2.8.0
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : 6.0.1
pyxlsb : None
s3fs : 2021.11.0
scipy : 1.7.3
sqlalchemy : 1.4.29
tables : 3.6.1
tabulate : 0.8.9
xarray : None
xlrd : 2.0.1
xlwt : 1.3.0
numba : 0.53.1
zstandard : None

[bdrum]

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