[backport] Fix arrow compatibility, hypothesis tests. (#7979)

python-package/xgboost/data.py

@@ -506,7 +506,6 @@ def record_batch_data_iter(data_iter: Iterator) -> Callable:
     """Data iterator used to ingest Arrow columnar record batches. We are not using
     class DataIter because it is only intended for building Device DMatrix and external
     memory DMatrix.
-
     """
     from pyarrow.cffi import ffi
 
@@ -557,13 +556,7 @@ def _from_arrow(
     if enable_categorical:
         raise ValueError("categorical data in arrow is not supported yet.")
 
-    major, _, _ = version.StrictVersion(pa.__version__).version
-    if major == 4:
     rb_iter = iter(data.to_batches())
-    else:
-        # use_async=True to workaround pyarrow 6.0.1 hang,
-        # see Modin-3982 and ARROW-15362
-        rb_iter = iter(data.to_batches(use_async=True))
     it = record_batch_data_iter(rb_iter)
     next_callback = ctypes.CFUNCTYPE(ctypes.c_int, ctypes.c_void_p)(it)
     handle = ctypes.c_void_p()

tests/python/test_updaters.py

@@ -10,10 +10,10 @@ exact_parameter_strategy = strategies.fixed_dictionaries({
     'nthread': strategies.integers(1, 4),
     'max_depth': strategies.integers(1, 11),
     'min_child_weight': strategies.floats(0.5, 2.0),
-    'alpha': strategies.floats(0.0, 2.0),
+    'alpha': strategies.floats(1e-5, 2.0),
     'lambda': strategies.floats(1e-5, 2.0),
     'eta': strategies.floats(0.01, 0.5),
-    'gamma': strategies.floats(0.0, 2.0),
+    'gamma': strategies.floats(1e-5, 2.0),
     'seed': strategies.integers(0, 10),
     # We cannot enable subsampling as the training loss can increase
     # 'subsample': strategies.floats(0.5, 1.0),