Repository: pandas-dev/pandas (python)

Issue:
BUG: regression in read_parquet that raises a `pyarrow.lib.ArrowInvalid: offset overflow while concatenating arrays`
### Pandas version checks

- [X] I have checked that this issue has not already been reported.

- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.

- [ ] I have confirmed this bug exists on the [main branch](https://pandas.pydata.org/docs/dev/getting_started/install.html#installing-the-development-version-of-pandas) of pandas.


### Reproducible Example

```python
import pandas as pd
pd.read_parquet(all_tx_info)
```

The file I am using is 71GB. So I cannot share it easily. If the error is clear from the stack trace, that is fine. If ever it is not clear, I can spend time trying the reproduce this issue with a synthetic dataFrame.



### Issue Description

I have the following parquet stored on disk: 
```
>>> tx.info(memory_usage='deep')
<class 'pandas.core.frame.DataFrame'>
Index: 904346808 entries, 0 to 804503
Data columns (total 11 columns):
 #   Column              Dtype
---  ------              -----
 0   tx_hash             string
 1   block_height        Int64
 2   block_date          datetime64[ns]
 3   tx_version          Int64
 4   is_coinbase         boolean
 5   is_segwit           boolean
 6   total_tx_in_value   Int64
 7   total_tx_out_value  Int64
 8   tx_fee              Int64
 9   nb_in               Int64
 10  nb_out              Int64
dtypes: Int64(7), boolean(2), datetime64[ns](1), string(1)
memory usage: 171.8 GB
```


With pandas 2.0.3, when I load it using `read_parquet`, it works without any issue.

However, with pandas 2.1.1, I have the following exception

```
pd.read_parquet(all_tx_info)
Traceback (most recent call last):
  File "/home/alegout/bc_tools.py", line 694, in load_all_tx_info_to_dataframe
    return pd.read_parquet(all_tx_info)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/user/alegout/home/miniconda3/envs/py3.11/lib/python3.11/site-packages/pandas/io/parquet.py", line 670, in read_parquet
    return impl.read(
           ^^^^^^^^^^
  File "/user/alegout/home/miniconda3/envs/py3.11/lib/python3.11/site-packages/pandas/io/parquet.py", line 279, in read
    result = pa_table.to_pandas(**to_pandas_kwargs)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "pyarrow/array.pxi", line 830, in pyarrow.lib._PandasConvertible.to_pandas
  File "pyarrow/table.pxi", line 3990, in pyarrow.lib.Table._to_pandas
  File "/user/alegout/home/miniconda3/envs/py3.11/lib/python3.11/site-packages/pyarrow/pandas_compat.py", line 820, in table_to_blockmanager
    blocks = _table_to_blocks(options, table, categories, ext_columns_dtypes)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/user/alegout/home/miniconda3/envs/py3.11/lib/python3.11/site-packages/pyarrow/pandas_compat.py", line 1171, in _table_to_blocks
    return [_reconstruct_block(item, columns, extension_columns)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/user/alegout/home/miniconda3/envs/py3.11/lib/python3.11/site-packages/pyarrow/pandas_compat.py", line 1171, in <listcomp>
    return [_reconstruct_block(item, columns, extension_columns)
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/user/alegout/home/miniconda3/envs/py3.11/lib/python3.11/site-packages/pyarrow/pandas_compat.py", line 780, in _reconstruct_block
    pd_ext_arr = pandas_dtype.__from_arrow__(arr)
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/user/alegout/home/miniconda3/envs/py3.11/lib/python3.11/site-packages/pandas/core/arrays/string_.py", line 229, in __from_arrow__
    arr = pyarrow.concat_arrays(chunks).to_numpy(zero_copy_only=False)
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "pyarrow/array.pxi", line 3039, in pyarrow.lib.concat_arrays
  File "pyarrow/error.pxi", line 144, in pyarrow.lib.pyarrow_internal_check_status
  File "pyarrow/error.pxi", line 100, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: offset overflow while concatenating arrays			
```



### Expected Behavior

The dataframe loads from the parquet without an exception

### Installed Versions

Here are the installed version for the environment that works with pandas 2.0.3
<details>
INSTALLED VERSIONS
------------------
commit           : 0f437949513225922d851e9581723d82120684a6
python           : 3.11.5.final.0
python-bits      : 64
OS               : Linux
OS-release       : 6.5.6-200.fc38.x86_64
Version          : #1 SMP PREEMPT_DYNAMIC Fri Oct  6 19:02:35 UTC 2023
machine          : x86_64
processor        :
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 2.0.3
numpy            : 1.24.3
pytz             : 2023.3.post1
dateutil         : 2.8.2
setuptools       : 68.0.0
pip              : 23.3
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : 1.3.5
brotli           : None
fastparquet      : None
fsspec           : None
gcsfs            : None
matplotlib       : 3.7.2
numba            : 0.58.0
numexpr          : 2.8.7
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 11.0.0
pyreadstat       : None
pyxlsb           : None
s3fs             : None
scipy            : None
snappy           : None
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
zstandard        : None
tzdata           : 2023.3
qtpy             : None
pyqt5            : None
</details>

And here is the environment for the version of pandas 2.1.1 that does not work
<details>
INSTALLED VERSIONS
------------------
commit              : e86ed377639948c64c429059127bcf5b359ab6be
python              : 3.11.5.final.0
python-bits         : 64
OS                  : Linux
OS-release          : 6.5.6-200.fc38.x86_64
Version             : #1 SMP PREEMPT_DYNAMIC Fri Oct  6 19:02:35 UTC 2023
machine             : x86_64
processor           :
byteorder           : little
LC_ALL              : None
LANG                : en_US.UTF-8
LOCALE              : en_US.UTF-8

pandas              : 2.1.1
numpy               : 1.24.3
pytz                : 2023.3.post1
dateutil            : 2.8.2
setuptools          : 68.0.0
pip                 : 23.2.1
Cython              : 3.0.0
pytest              : None
hypothesis          : None
sphinx              : None
blosc               : None
feather             : None
xlsxwriter          : None
lxml.etree          : 4.9.3
html5lib            : None
pymysql             : None
psycopg2            : None
jinja2              : 3.1.2
IPython             : 8.15.0
pandas_datareader   : 0.10.0
bs4                 : 4.12.2
bottleneck          : 1.3.5
dataframe-api-compat: None
fastparquet         : None
fsspec              : 2023.9.2
gcsfs               : None
matplotlib          : 3.7.2
numba               : 0.58.0
numexpr             : 2.8.7
odfpy               : None
openpyxl            : None
pandas_gbq          : None
pyarrow             : 11.0.0
pyreadstat          : None
pyxlsb              : None
s3fs                : None
scipy               : 1.11.3
sqlalchemy          : 2.0.21
tables              : None
tabulate            : 0.8.10
xarray              : 2023.6.0
xlrd                : None
zstandard           : None
tzdata              : 2023.3
qtpy                : 2.2.0
pyqt5               : None
</details>

Pull request description:
REGR: fix read_parquet with column of large strings (avoid overflow from concat)
- [x] closes #55606
- [ ] [Tests added and passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#writing-tests) if fixing a bug or adding a new feature
- [ ] All [code checks passed](https://pandas.pydata.org/pandas-docs/dev/development/contributing_codebase.html#pre-commit).
- [x] Added an entry in the latest `doc/source/whatsnew/vX.X.X.rst` file if fixing a bug or adding a new feature.


Patch:
diff --git a/doc/source/whatsnew/v2.1.2.rst b/doc/source/whatsnew/v2.1.2.rst
index 1d2d89e7ea..7758dd7145 100644
--- a/doc/source/whatsnew/v2.1.2.rst
+++ b/doc/source/whatsnew/v2.1.2.rst
@@ -28,7 +28,9 @@ Fixed regressions
 - Fixed regression in :meth:`DataFrameGroupBy.agg` and :meth:`SeriesGroupBy.agg` where if the option ``compute.use_numba`` was set to True, groupby methods not supported by the numba engine would raise a ``TypeError`` (:issue:`55520`)
 - Fixed performance regression with wide DataFrames, typically involving methods where all columns were accessed individually (:issue:`55256`, :issue:`55245`)
 - Fixed regression in :func:`merge_asof` raising ``TypeError`` for ``by`` with datetime and timedelta dtypes (:issue:`55453`)
+- Fixed regression in :func:`read_parquet` when reading a file with a string column consisting of more than 2 GB of string data and using the ``"string"`` dtype (:issue:`55606`)
 - Fixed regression in :meth:`DataFrame.to_sql` not roundtripping datetime columns correctly for sqlite when using ``detect_types`` (:issue:`55554`)
+- Fixed regression in construction of certain DataFrame or Series subclasses (:issue:`54922`)
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_212.bug_fixes:
@@ -36,6 +38,7 @@ Fixed regressions
 Bug fixes
 ~~~~~~~~~
 - Fixed bug in :class:`.DataFrameGroupBy` reductions not preserving object dtype when ``infer_string`` is set (:issue:`55620`)
+- Fixed bug in :meth:`.DataFrameGroupBy.min()` and :meth:`.DataFrameGroupBy.max()` not preserving extension dtype for empty object (:issue:`55619`)
 - Fixed bug in :meth:`.SeriesGroupBy.value_counts` returning incorrect dtype for string columns (:issue:`55627`)
 - Fixed bug in :meth:`Categorical.equals` if other has arrow backed string dtype (:issue:`55364`)
 - Fixed bug in :meth:`DataFrame.__setitem__` not inferring string dtype for zero-dimensional array with ``infer_string=True`` (:issue:`55366`)
diff --git a/pandas/core/arrays/base.py b/pandas/core/arrays/base.py
index 05e6fc09a5..3d97711d5f 100644
--- a/pandas/core/arrays/base.py
+++ b/pandas/core/arrays/base.py
@@ -2352,6 +2352,9 @@ class ExtensionArray:
         # GH#43682
         if isinstance(self.dtype, StringDtype):
             # StringArray
+            if op.how not in ["any", "all"]:
+                # Fail early to avoid conversion to object
+                op._get_cython_function(op.kind, op.how, np.dtype(object), False)
             npvalues = self.to_numpy(object, na_value=np.nan)
         else:
             raise NotImplementedError(
diff --git a/pandas/core/arrays/string_.py b/pandas/core/arrays/string_.py
index a50c95d33d..471b37eac7 100644
--- a/pandas/core/arrays/string_.py
+++ b/pandas/core/arrays/string_.py
@@ -228,11 +228,19 @@ class StringDtype(StorageExtensionDtype):
                 # pyarrow.ChunkedArray
                 chunks = array.chunks
 
+            results = []
+            for arr in chunks:
+                # convert chunk by chunk to numpy and concatenate then, to avoid
+                # overflow for large string data when concatenating the pyarrow arrays
+                arr = arr.to_numpy(zero_copy_only=False)
+                arr = ensure_string_array(arr, na_value=libmissing.NA)
+                results.append(arr)
+
         if len(chunks) == 0:
             arr = np.array([], dtype=object)
         else:
-            arr = pyarrow.concat_arrays(chunks).to_numpy(zero_copy_only=False)
-            arr = ensure_string_array(arr, na_value=libmissing.NA)
+            arr = np.concatenate(results)
+
         # Bypass validation inside StringArray constructor, see GH#47781
         new_string_array = StringArray.__new__(StringArray)
         NDArrayBacked.__init__(
diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 838792ceb4..c8141305e0 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -643,13 +643,12 @@ class DataFrame(NDFrame, OpsMixin):
         return DataFrame
 
     def _constructor_from_mgr(self, mgr, axes):
-        df = self._from_mgr(mgr, axes=axes)
-        if type(self) is DataFrame:
-            # fastpath avoiding constructor call
-            return df
+        if self._constructor is DataFrame:
+            # we are pandas.DataFrame (or a subclass that doesn't override _constructor)
+            return self._from_mgr(mgr, axes=axes)
         else:
             assert axes is mgr.axes
-            return self._constructor(df, copy=False)
+            return self._constructor(mgr)
 
     _constructor_sliced: Callable[..., Series] = Series
 
@@ -657,13 +656,12 @@ class DataFrame(NDFrame, OpsMixin):
         return Series._from_mgr(mgr, axes)
 
     def _constructor_sliced_from_mgr(self, mgr, axes):
-        ser = self._sliced_from_mgr(mgr, axes=axes)
-        ser._name = None  # caller is responsible for setting real name
-        if type(self) is DataFrame:
-            # fastpath avoiding constructor call
+        if self._constructor_sliced is Series:
+            ser = self._sliced_from_mgr(mgr, axes)
+            ser._name = None  # caller is responsible for setting real name
             return ser
         assert axes is mgr.axes
-        return self._constructor_sliced(ser, copy=False)
+        return self._constructor_sliced(mgr)
 
     # ----------------------------------------------------------------------
     # Constructors
diff --git a/pandas/core/groupby/ops.py b/pandas/core/groupby/ops.py
index 607059e518..e4cba7ce8f 100644
--- a/pandas/core/groupby/ops.py
+++ b/pandas/core/groupby/ops.py
@@ -33,6 +33,7 @@ from pandas._typing import (
 from pandas.errors import AbstractMethodError
 from pandas.util._decorators import cache_readonly
 
+from pandas.core.dtypes.base import ExtensionDtype
 from pandas.core.dtypes.cast import (
     maybe_cast_pointwise_result,
     maybe_downcast_to_dtype,
@@ -837,10 +838,8 @@ class BaseGrouper:
         -------
         np.ndarray or ExtensionArray
         """
-        # test_groupby_empty_with_category gets here with self.ngroups == 0
-        #  and len(obj) > 0
 
-        if len(obj) > 0 and not isinstance(obj._values, np.ndarray):
+        if not isinstance(obj._values, np.ndarray):
             # we can preserve a little bit more aggressively with EA dtype
             #  because maybe_cast_pointwise_result will do a try/except
             #  with _from_sequence.  NB we are assuming here that _from_sequence
@@ -849,11 +848,18 @@ class BaseGrouper:
 
         result = self._aggregate_series_pure_python(obj, func)
 
-        npvalues = lib.maybe_convert_objects(result, try_float=False)
-        if preserve_dtype:
-            out = maybe_cast_pointwise_result(npvalues, obj.dtype, numeric_only=True)
+        if len(obj) == 0 and len(result) == 0 and isinstance(obj.dtype, ExtensionDtype):
+            cls = obj.dtype.construct_array_type()
+            out = cls._from_sequence(result)
+
         else:
-            out = npvalues
+            npvalues = lib.maybe_convert_objects(result, try_float=False)
+            if preserve_dtype:
+                out = maybe_cast_pointwise_result(
+                    npvalues, obj.dtype, numeric_only=True
+                )
+            else:
+                out = npvalues
         return out
 
     @final
diff --git a/pandas/core/series.py b/pandas/core/series.py
index c6625eefa2..c5f622a113 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -632,14 +632,14 @@ class Series(base.IndexOpsMixin, NDFrame):  # type: ignore[misc]
         return Series
 
     def _constructor_from_mgr(self, mgr, axes):
-        ser = self._from_mgr(mgr, axes=axes)
-        ser._name = None  # caller is responsible for setting real name
-        if type(self) is Series:
-            # fastpath avoiding constructor call
+        if self._constructor is Series:
+            # we are pandas.Series (or a subclass that doesn't override _constructor)
+            ser = self._from_mgr(mgr, axes=axes)
+            ser._name = None  # caller is responsible for setting real name
             return ser
         else:
             assert axes is mgr.axes
-            return self._constructor(ser, copy=False)
+            return self._constructor(mgr)
 
     @property
     def _constructor_expanddim(self) -> Callable[..., DataFrame]:
@@ -657,10 +657,12 @@ class Series(base.IndexOpsMixin, NDFrame):  # type: ignore[misc]
         return DataFrame._from_mgr(mgr, axes=mgr.axes)
 
     def _constructor_expanddim_from_mgr(self, mgr, axes):
-        df = self._expanddim_from_mgr(mgr, axes)
-        if type(self) is Series:
-            return df
-        return self._constructor_expanddim(df, copy=False)
+        from pandas.core.frame import DataFrame
+
+        if self._constructor_expanddim is DataFrame:
+            return self._expanddim_from_mgr(mgr, axes)
+        assert axes is mgr.axes
+        return self._constructor_expanddim(mgr)
 
     # types
     @property


Test patch:
diff --git a/pandas/tests/frame/test_arithmetic.py b/pandas/tests/frame/test_arithmetic.py
index 1d1a4dbe83..c59edbae05 100644
--- a/pandas/tests/frame/test_arithmetic.py
+++ b/pandas/tests/frame/test_arithmetic.py
@@ -2083,6 +2083,9 @@ def test_frame_sub_nullable_int(any_int_ea_dtype):
     tm.assert_frame_equal(result, expected)
 
 
+@pytest.mark.filterwarnings(
+    "ignore:Passing a BlockManager|Passing a SingleBlockManager:DeprecationWarning"
+)
 def test_frame_op_subclass_nonclass_constructor():
     # GH#43201 subclass._constructor is a function, not the subclass itself
 
diff --git a/pandas/tests/frame/test_subclass.py b/pandas/tests/frame/test_subclass.py
index 37ca52eba6..8e657f197c 100644
--- a/pandas/tests/frame/test_subclass.py
+++ b/pandas/tests/frame/test_subclass.py
@@ -10,6 +10,10 @@ from pandas import (
 )
 import pandas._testing as tm
 
+pytestmark = pytest.mark.filterwarnings(
+    "ignore:Passing a BlockManager|Passing a SingleBlockManager:DeprecationWarning"
+)
+
 
 @pytest.fixture()
 def gpd_style_subclass_df():
@@ -734,8 +738,36 @@ class TestDataFrameSubclassing:
         # https://github.com/pandas-dev/pandas/pull/46018
         df = tm.SubclassedDataFrame({"A": [0, 1, 2]})
         msg = "The 'method' keyword in SubclassedDataFrame.replace is deprecated"
-        with tm.assert_produces_warning(FutureWarning, match=msg):
+        with tm.assert_produces_warning(
+            FutureWarning, match=msg, raise_on_extra_warnings=False
+        ):
             result = df.replace([1, 2], method="ffill")
         expected = tm.SubclassedDataFrame({"A": [0, 0, 0]})
         assert isinstance(result, tm.SubclassedDataFrame)
         tm.assert_frame_equal(result, expected)
+
+
+class MySubclassWithMetadata(DataFrame):
+    _metadata = ["my_metadata"]
+
+    def __init__(self, *args, **kwargs) -> None:
+        super().__init__(*args, **kwargs)
+
+        my_metadata = kwargs.pop("my_metadata", None)
+        if args and isinstance(args[0], MySubclassWithMetadata):
+            my_metadata = args[0].my_metadata  # type: ignore[has-type]
+        self.my_metadata = my_metadata
+
+    @property
+    def _constructor(self):
+        return MySubclassWithMetadata
+
+
+def test_constructor_with_metadata():
+    # https://github.com/pandas-dev/pandas/pull/54922
+    # https://github.com/pandas-dev/pandas/issues/55120
+    df = MySubclassWithMetadata(
+        np.random.default_rng(2).random((5, 3)), columns=["A", "B", "C"]
+    )
+    subset = df[["A", "B"]]
+    assert isinstance(subset, MySubclassWithMetadata)
diff --git a/pandas/tests/groupby/test_groupby_subclass.py b/pandas/tests/groupby/test_groupby_subclass.py
index 601e67bbca..0068f642a4 100644
--- a/pandas/tests/groupby/test_groupby_subclass.py
+++ b/pandas/tests/groupby/test_groupby_subclass.py
@@ -11,6 +11,10 @@ from pandas import (
 import pandas._testing as tm
 from pandas.tests.groupby import get_groupby_method_args
 
+pytestmark = pytest.mark.filterwarnings(
+    "ignore:Passing a BlockManager|Passing a SingleBlockManager:DeprecationWarning"
+)
+
 
 @pytest.mark.parametrize(
     "obj",
@@ -64,7 +68,9 @@ def test_groupby_preserves_metadata():
         return group.testattr
 
     msg = "DataFrameGroupBy.apply operated on the grouping columns"
-    with tm.assert_produces_warning(FutureWarning, match=msg):
+    with tm.assert_produces_warning(
+        FutureWarning, match=msg, raise_on_extra_warnings=False
+    ):
         result = custom_df.groupby("c").apply(func)
     expected = tm.SubclassedSeries(["hello"] * 3, index=Index([7, 8, 9], name="c"))
     tm.assert_series_equal(result, expected)
@@ -104,6 +110,8 @@ def test_groupby_resample_preserves_subclass(obj):
 
     # Confirm groupby.resample() preserves dataframe type
     msg = "DataFrameGroupBy.resample operated on the grouping columns"
-    with tm.assert_produces_warning(FutureWarning, match=msg):
+    with tm.assert_produces_warning(
+        FutureWarning, match=msg, raise_on_extra_warnings=False
+    ):
         result = df.groupby("Buyer").resample("5D").sum()
     assert isinstance(result, obj)
diff --git a/pandas/tests/groupby/test_reductions.py b/pandas/tests/groupby/test_reductions.py
index fdfb211ac2..35ad8e3f5d 100644
--- a/pandas/tests/groupby/test_reductions.py
+++ b/pandas/tests/groupby/test_reductions.py
@@ -575,6 +575,19 @@ def test_groupby_min_max_categorical(func):
     tm.assert_frame_equal(result, expected)
 
 
+@pytest.mark.parametrize("func", ["min", "max"])
+def test_min_empty_string_dtype(func):
+    # GH#55619
+    pytest.importorskip("pyarrow")
+    dtype = "string[pyarrow_numpy]"
+    df = DataFrame({"a": ["a"], "b": "a", "c": "a"}, dtype=dtype).iloc[:0]
+    result = getattr(df.groupby("a"), func)()
+    expected = DataFrame(
+        columns=["b", "c"], dtype=dtype, index=pd.Index([], dtype=dtype, name="a")
+    )
+    tm.assert_frame_equal(result, expected)
+
+
 def test_max_nan_bug():
     raw = """,Date,app,File
 -04-23,2013-04-23 00:00:00,,log080001.log
diff --git a/pandas/tests/io/test_parquet.py b/pandas/tests/io/test_parquet.py
index 581be53145..0a72fd7bbe 100644
--- a/pandas/tests/io/test_parquet.py
+++ b/pandas/tests/io/test_parquet.py
@@ -1141,6 +1141,18 @@ class TestParquetPyArrow(Base):
         )
         tm.assert_frame_equal(result, expected)
 
+    # NOTE: this test is not run by default, because it requires a lot of memory (>5GB)
+    # @pytest.mark.slow
+    # def test_string_column_above_2GB(self, tmp_path, pa):
+    #     # https://github.com/pandas-dev/pandas/issues/55606
+    #     # above 2GB of string data
+    #     v1 = b"x" * 100000000
+    #     v2 = b"x" * 147483646
+    #     df = pd.DataFrame({"strings": [v1] * 20 + [v2] + ["x"] * 20}, dtype="string")
+    #     df.to_parquet(tmp_path / "test.parquet")
+    #     result = read_parquet(tmp_path / "test.parquet")
+    #     assert result["strings"].dtype == "string"
+
 
 class TestParquetFastParquet(Base):
     def test_basic(self, fp, df_full):
diff --git a/pandas/tests/reshape/concat/test_concat.py b/pandas/tests/reshape/concat/test_concat.py
index 1310580108..216422bc12 100644
--- a/pandas/tests/reshape/concat/test_concat.py
+++ b/pandas/tests/reshape/concat/test_concat.py
@@ -591,6 +591,9 @@ def test_duplicate_keys_same_frame():
     tm.assert_frame_equal(result, expected)
 
 
+@pytest.mark.filterwarnings(
+    "ignore:Passing a BlockManager|Passing a SingleBlockManager:DeprecationWarning"
+)
 @pytest.mark.parametrize(
     "obj",
     [
diff --git a/pandas/tests/reshape/merge/test_merge.py b/pandas/tests/reshape/merge/test_merge.py
index 4d779349b5..495fb4536f 100644
--- a/pandas/tests/reshape/merge/test_merge.py
+++ b/pandas/tests/reshape/merge/test_merge.py
@@ -688,6 +688,9 @@ class TestMerge:
         )[["i1", "i2", "i1_", "i3"]]
         tm.assert_frame_equal(result, expected)
 
+    @pytest.mark.filterwarnings(
+        "ignore:Passing a BlockManager|Passing a SingleBlockManager:DeprecationWarning"
+    )
     def test_merge_type(self, df, df2):
         class NotADataFrame(DataFrame):
             @property
diff --git a/pandas/tests/reshape/merge/test_merge_ordered.py b/pandas/tests/reshape/merge/test_merge_ordered.py
index 1d0d4e3eb5..cfb4e92fb4 100644
--- a/pandas/tests/reshape/merge/test_merge_ordered.py
+++ b/pandas/tests/reshape/merge/test_merge_ordered.py
@@ -70,6 +70,9 @@ class TestMergeOrdered:
         result = merge_ordered(left, right, on="key", left_by="group")
         assert result["group"].notna().all()
 
+    @pytest.mark.filterwarnings(
+        "ignore:Passing a BlockManager|Passing a SingleBlockManager:DeprecationWarning"
+    )
     def test_merge_type(self, left, right):
         class NotADataFrame(DataFrame):
             @property
diff --git a/pandas/tests/series/methods/test_to_frame.py b/pandas/tests/series/methods/test_to_frame.py
index 01e547aa34..0eadf696b3 100644
--- a/pandas/tests/series/methods/test_to_frame.py
+++ b/pandas/tests/series/methods/test_to_frame.py
@@ -1,3 +1,5 @@
+import pytest
+
 from pandas import (
     DataFrame,
     Index,
@@ -40,6 +42,9 @@ class TestToFrame:
         )
         tm.assert_frame_equal(rs, xp)
 
+    @pytest.mark.filterwarnings(
+        "ignore:Passing a BlockManager|Passing a SingleBlockManager:DeprecationWarning"
+    )
     def test_to_frame_expanddim(self):
         # GH#9762
 
diff --git a/pandas/tests/series/test_subclass.py b/pandas/tests/series/test_subclass.py
index a3550c6de6..c2d5afcf88 100644
--- a/pandas/tests/series/test_subclass.py
+++ b/pandas/tests/series/test_subclass.py
@@ -4,6 +4,10 @@ import pytest
 import pandas as pd
 import pandas._testing as tm
 
+pytestmark = pytest.mark.filterwarnings(
+    "ignore:Passing a BlockManager|Passing a SingleBlockManager:DeprecationWarning"
+)
+
 
 class TestSeriesSubclassing:
     @pytest.mark.parametrize(