Clean up minimum pyarrow version checks

.github/workflows/tests.yaml

@@ -155,7 +155,7 @@ jobs:
           # Increase this value to reset cache if
           # continuous_integration/environment-${{ matrix.environment }}.yaml has not
           # changed. See also same variable in .pre-commit-config.yaml
-          CACHE_NUMBER: 0
+          CACHE_NUMBER: 2
         id: cache
 
       - name: Update environment

distributed/protocol/arrow.py

@@ -4,11 +4,6 @@
 
 from distributed.protocol.serialize import dask_deserialize, dask_serialize
 
-if int(pyarrow.__version__.split(".")[0]) < 16:
-    raise ImportError(
-        "Need pyarrow >=16.0. See https://arrow.apache.org/docs/python/install.html"
-    )
-
 
 @dask_serialize.register(pyarrow.RecordBatch)
 def serialize_batch(batch):

distributed/shuffle/__init__.py

@@ -1,12 +1,10 @@
 from __future__ import annotations
 
-from distributed.shuffle._arrow import check_minimal_arrow_version
 from distributed.shuffle._rechunk import rechunk_p2p
 from distributed.shuffle._scheduler_plugin import ShuffleSchedulerPlugin
 from distributed.shuffle._worker_plugin import ShuffleWorkerPlugin
 
 __all__ = [
-    "check_minimal_arrow_version",
     "rechunk_p2p",
     "ShuffleSchedulerPlugin",
     "ShuffleWorkerPlugin",

distributed/shuffle/_arrow.py

@@ -4,8 +4,6 @@
 from pathlib import Path
 from typing import TYPE_CHECKING
 
-from packaging.version import parse
-
 from dask.utils import parse_bytes
 
 if TYPE_CHECKING:
@@ -31,24 +29,6 @@ def check_dtype_support(meta_input: pd.DataFrame) -> None:
             raise TypeError("p2p does not support sparse data found in column '{name}'")
 
 
-def check_minimal_arrow_version() -> None:
-    """Verify that the the correct version of pyarrow is installed to support
-    the P2P extension.
-
-    Raises a ModuleNotFoundError if pyarrow is not installed or an
-    ImportError if the installed version is not recent enough.
-    """
-    minversion = "14.0.1"
-    try:
-        import pyarrow as pa
-    except ModuleNotFoundError:
-        raise ModuleNotFoundError(f"P2P shuffling requires pyarrow>={minversion}")
-    if parse(pa.__version__) < parse(minversion):
-        raise ImportError(
-            f"P2P shuffling requires pyarrow>={minversion} but only found {pa.__version__}"
-        )
-
-
 def concat_tables(tables: Iterable[pa.Table]) -> pa.Table:
     import pyarrow as pa
 

distributed/tests/test_client.py

@@ -86,7 +86,6 @@
 from distributed.diagnostics.plugin import UploadDirectory, WorkerPlugin
 from distributed.metrics import time
 from distributed.scheduler import CollectTaskMetaDataPlugin, KilledWorker, Scheduler
-from distributed.shuffle import check_minimal_arrow_version
 from distributed.sizeof import sizeof
 from distributed.utils import get_mp_context, is_valid_xml, open_port, sync, tmp_text
 from distributed.utils_test import (
@@ -3417,17 +3416,16 @@ async def test_cancel_clears_processing(c, s, *workers):
 
 
 def test_default_get(loop_in_thread):
-    has_pyarrow = False
     try:
-        check_minimal_arrow_version()
-        has_pyarrow = True
-    except ImportError:
-        pass
+        from dask.dataframe._compat import HAS_PYARROW
+    except ImportError:  # No pandas
+        HAS_PYARROW = False
+
     loop = loop_in_thread
     with cluster() as (s, [a, b]):
         pre_get = dask.base.get_scheduler()
         # These may change in the future but the selection below should not
-        distributed_default = "p2p" if has_pyarrow else "tasks"
+        distributed_default = "p2p" if HAS_PYARROW else "tasks"
         local_default = "disk"
         assert get_default_shuffle_method() == local_default
         with Client(s["address"], set_as_default=True, loop=loop) as c: