We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
`pd.read_feather(file)` actually reads the file twice!
There's a really strange logic in our Feather dispatcher introduced a long time ago that reads the whole Feather file just to extract its column names:
https://github.com/modin-project/modin/blob/632d724adb013d6f4d18aa2a4f2faa9325d324e8/modin/core/io/column_stores/feather_dispatcher.py#L55-L64

Note that `.build_query_compiler(..)` launch parsing kernels that would also be reading the same parquet file but in a distributed way.

We should be using more smarter way to extract feather's metadata: https://issues.apache.org/jira/browse/ARROW-10344

--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `modin/core/io/column_stores/feather_dispatcher.py`
Content:
```
1 # Licensed to Modin Development Team under one or more contributor license agreements.
2 # See the NOTICE file distributed with this work for additional information regarding
3 # copyright ownership.  The Modin Development Team licenses this file to you under the
4 # Apache License, Version 2.0 (the "License"); you may not use this file except in
5 # compliance with the License.  You may obtain a copy of the License at
6 #
7 #     http://www.apache.org/licenses/LICENSE-2.0
8 #
9 # Unless required by applicable law or agreed to in writing, software distributed under
10 # the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
11 # ANY KIND, either express or implied. See the License for the specific language
12 # governing permissions and limitations under the License.
13 
14 """Module houses `FeatherDispatcher` class, that is used for reading `.feather` files."""
15 
16 from modin.core.io.column_stores.column_store_dispatcher import ColumnStoreDispatcher
17 from modin.utils import import_optional_dependency
18 from modin.core.io.file_dispatcher import OpenFile
19 
20 
21 class FeatherDispatcher(ColumnStoreDispatcher):
22     """Class handles utils for reading `.feather` files."""
23 
24     @classmethod
25     def _read(cls, path, columns=None, **kwargs):
26         """
27         Read data from the file path, returning a query compiler.
28 
29         Parameters
30         ----------
31         path : str or file-like object
32             The filepath of the feather file.
33         columns : array-like, optional
34             Columns to read from file. If not provided, all columns are read.
35         **kwargs : dict
36             `read_feather` function kwargs.
37 
38         Returns
39         -------
40         BaseQueryCompiler
41             Query compiler with imported data for further processing.
42 
43         Notes
44         -----
45         `PyArrow` engine and local files only are supported for now,
46         multi threading is set to False by default.
47         PyArrow feather is used. Please refer to the documentation here
48         https://arrow.apache.org/docs/python/api.html#feather-format
49         """
50         path = cls.get_path(path)
51         if columns is None:
52             import_optional_dependency(
53                 "pyarrow", "pyarrow is required to read feather files."
54             )
55             from pyarrow.feather import read_feather
56 
57             with OpenFile(
58                 path,
59                 **(kwargs.get("storage_options", None) or {}),
60             ) as file:
61                 df = read_feather(file)
62             # pyarrow.feather.read_feather doesn't support columns as pandas.Index
63             columns = list(df.columns)
64         return cls.build_query_compiler(path, columns, use_threads=False)
65
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/modin/core/io/column_stores/feather_dispatcher.py b/modin/core/io/column_stores/feather_dispatcher.py
--- a/modin/core/io/column_stores/feather_dispatcher.py
+++ b/modin/core/io/column_stores/feather_dispatcher.py
@@ -52,13 +52,15 @@
             import_optional_dependency(
                 "pyarrow", "pyarrow is required to read feather files."
             )
-            from pyarrow.feather import read_feather
+            from pyarrow import ipc
 
             with OpenFile(
                 path,
                 **(kwargs.get("storage_options", None) or {}),
             ) as file:
-                df = read_feather(file)
-            # pyarrow.feather.read_feather doesn't support columns as pandas.Index
-            columns = list(df.columns)
+                # Opens the file to extract its metadata
+                reader = ipc.open_file(file)
+            # TODO: pyarrow's schema contains much more metadata than just column names, it also
+            # has dtypes and index information that we could use when building a dataframe
+            columns = reader.schema.names
         return cls.build_query_compiler(path, columns, use_threads=False)

{"golden_diff": "diff --git a/modin/core/io/column_stores/feather_dispatcher.py b/modin/core/io/column_stores/feather_dispatcher.py\n--- a/modin/core/io/column_stores/feather_dispatcher.py\n+++ b/modin/core/io/column_stores/feather_dispatcher.py\n@@ -52,13 +52,15 @@\n             import_optional_dependency(\n                 \"pyarrow\", \"pyarrow is required to read feather files.\"\n             )\n-            from pyarrow.feather import read_feather\n+            from pyarrow import ipc\n \n             with OpenFile(\n                 path,\n                 **(kwargs.get(\"storage_options\", None) or {}),\n             ) as file:\n-                df = read_feather(file)\n-            # pyarrow.feather.read_feather doesn't support columns as pandas.Index\n-            columns = list(df.columns)\n+                # Opens the file to extract its metadata\n+                reader = ipc.open_file(file)\n+            # TODO: pyarrow's schema contains much more metadata than just column names, it also\n+            # has dtypes and index information that we could use when building a dataframe\n+            columns = reader.schema.names\n         return cls.build_query_compiler(path, columns, use_threads=False)\n", "issue": "`pd.read_feather(file)` actually reads the file twice!\nThere's a really strange logic in our Feather dispatcher introduced a long time ago that reads the whole Feather file just to extract its column names:\r\nhttps://github.com/modin-project/modin/blob/632d724adb013d6f4d18aa2a4f2faa9325d324e8/modin/core/io/column_stores/feather_dispatcher.py#L55-L64\r\n\r\nNote that `.build_query_compiler(..)` launch parsing kernels that would also be reading the same parquet file but in a distributed way.\r\n\r\nWe should be using more smarter way to extract feather's metadata: https://issues.apache.org/jira/browse/ARROW-10344\n", "before_files": [{"content": "# Licensed to Modin Development Team under one or more contributor license agreements.\n# See the NOTICE file distributed with this work for additional information regarding\n# copyright ownership.  The Modin Development Team licenses this file to you under the\n# Apache License, Version 2.0 (the \"License\"); you may not use this file except in\n# compliance with the License.  You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software distributed under\n# the License is distributed on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF\n# ANY KIND, either express or implied. See the License for the specific language\n# governing permissions and limitations under the License.\n\n\"\"\"Module houses `FeatherDispatcher` class, that is used for reading `.feather` files.\"\"\"\n\nfrom modin.core.io.column_stores.column_store_dispatcher import ColumnStoreDispatcher\nfrom modin.utils import import_optional_dependency\nfrom modin.core.io.file_dispatcher import OpenFile\n\n\nclass FeatherDispatcher(ColumnStoreDispatcher):\n    \"\"\"Class handles utils for reading `.feather` files.\"\"\"\n\n    @classmethod\n    def _read(cls, path, columns=None, **kwargs):\n        \"\"\"\n        Read data from the file path, returning a query compiler.\n\n        Parameters\n        ----------\n        path : str or file-like object\n            The filepath of the feather file.\n        columns : array-like, optional\n            Columns to read from file. If not provided, all columns are read.\n        **kwargs : dict\n            `read_feather` function kwargs.\n\n        Returns\n        -------\n        BaseQueryCompiler\n            Query compiler with imported data for further processing.\n\n        Notes\n        -----\n        `PyArrow` engine and local files only are supported for now,\n        multi threading is set to False by default.\n        PyArrow feather is used. Please refer to the documentation here\n        https://arrow.apache.org/docs/python/api.html#feather-format\n        \"\"\"\n        path = cls.get_path(path)\n        if columns is None:\n            import_optional_dependency(\n                \"pyarrow\", \"pyarrow is required to read feather files.\"\n            )\n            from pyarrow.feather import read_feather\n\n            with OpenFile(\n                path,\n                **(kwargs.get(\"storage_options\", None) or {}),\n            ) as file:\n                df = read_feather(file)\n            # pyarrow.feather.read_feather doesn't support columns as pandas.Index\n            columns = list(df.columns)\n        return cls.build_query_compiler(path, columns, use_threads=False)\n", "path": "modin/core/io/column_stores/feather_dispatcher.py"}], "after_files": [{"content": "# Licensed to Modin Development Team under one or more contributor license agreements.\n# See the NOTICE file distributed with this work for additional information regarding\n# copyright ownership.  The Modin Development Team licenses this file to you under the\n# Apache License, Version 2.0 (the \"License\"); you may not use this file except in\n# compliance with the License.  You may obtain a copy of the License at\n#\n#     http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software distributed under\n# the License is distributed on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF\n# ANY KIND, either express or implied. See the License for the specific language\n# governing permissions and limitations under the License.\n\n\"\"\"Module houses `FeatherDispatcher` class, that is used for reading `.feather` files.\"\"\"\n\nfrom modin.core.io.column_stores.column_store_dispatcher import ColumnStoreDispatcher\nfrom modin.utils import import_optional_dependency\nfrom modin.core.io.file_dispatcher import OpenFile\n\n\nclass FeatherDispatcher(ColumnStoreDispatcher):\n    \"\"\"Class handles utils for reading `.feather` files.\"\"\"\n\n    @classmethod\n    def _read(cls, path, columns=None, **kwargs):\n        \"\"\"\n        Read data from the file path, returning a query compiler.\n\n        Parameters\n        ----------\n        path : str or file-like object\n            The filepath of the feather file.\n        columns : array-like, optional\n            Columns to read from file. If not provided, all columns are read.\n        **kwargs : dict\n            `read_feather` function kwargs.\n\n        Returns\n        -------\n        BaseQueryCompiler\n            Query compiler with imported data for further processing.\n\n        Notes\n        -----\n        `PyArrow` engine and local files only are supported for now,\n        multi threading is set to False by default.\n        PyArrow feather is used. Please refer to the documentation here\n        https://arrow.apache.org/docs/python/api.html#feather-format\n        \"\"\"\n        path = cls.get_path(path)\n        if columns is None:\n            import_optional_dependency(\n                \"pyarrow\", \"pyarrow is required to read feather files.\"\n            )\n            from pyarrow import ipc\n\n            with OpenFile(\n                path,\n                **(kwargs.get(\"storage_options\", None) or {}),\n            ) as file:\n                # Opens the file to extract its metadata\n                reader = ipc.open_file(file)\n            # TODO: pyarrow's schema contains much more metadata than just column names, it also\n            # has dtypes and index information that we could use when building a dataframe\n            columns = reader.schema.names\n        return cls.build_query_compiler(path, columns, use_threads=False)\n", "path": "modin/core/io/column_stores/feather_dispatcher.py"}]}