BUG: Getting "Out of bounds on buffer access" error when .loc indexing a non-unique index with Int64 dtype

[dalejung]

Pandas version checks

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

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

Reproducible Example

ids = list(range(11))
index = pd.Index(ids * 1000)  # create a non-unique index
df = pd.DataFrame({'val': row_keys * 2}, index=index)
df.index = df.index.astype('Int64')
df.loc[ids]  # Errors

df.loc[ids[:5]]  # does not error since resulting DataFrame is 5k rows.

Issue Description

Indexing a DataFrame with an Int64 index will error with IndexError: Out of bounds on buffer access (axis 0) if the resulting dataframe has more than 10k values.

This does not error when the index is a regular int64 dtype. This does not occur if the index is unique.

Expected Behavior

Return the indexed dataframe. This works on 2.1.4.

Installed Versions

INSTALLED VERSIONS

commit : 5bd2c2e
python : 3.11.3.final.0
python-bits : 64
OS : Linux
OS-release : 6.7.0-arch3-1
Version : #1 SMP PREEMPT_DYNAMIC Sat, 13 Jan 2024 14:37:14 +0000
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 3.0.0.dev0+167.g499662fa3d.dirty
numpy : 1.24.4
pytz : 2023.3
dateutil : 2.8.2
setuptools : 65.3.0
pip : 22.2.2
Cython : 3.0.8
pytest : 7.4.0
hypothesis : 6.47.1
sphinx : 6.2.1
blosc : None
feather : None
xlsxwriter : 3.1.0
lxml.etree : 4.9.2
html5lib : 1.1
pymysql : 1.0.3
psycopg2 : 2.9.6
jinja2 : 3.1.2
IPython : 8.18.0.dev
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.2
bottleneck : 1.3.7
dataframe-api-compat : None
fastparquet : 2023.4.0
fsspec : 2023.5.0
gcsfs : 2023.5.0
matplotlib : 3.7.1
numba : 0.57.0
numexpr : 2.8.4
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : 15.0.0.dev408+g0b5ef14f3
pyreadstat : 1.2.1
python-calamine : None
pyxlsb : 1.0.10
s3fs : 2023.5.0
scipy : 1.10.1
sqlalchemy : 2.0.14
tables : 3.8.0
tabulate : 0.9.0
xarray : 2023.5.0
xlrd : 2.0.1
zstandard : 0.21.0
tzdata : 2023.3
qtpy : 2.4.0
pyqt5 : None