Expose sorted groupby parameters to pylibcudf

python/cudf/cudf/_lib/pylibcudf/groupby.pxd

@@ -16,6 +16,7 @@ from cudf._lib.pylibcudf.libcudf.groupby cimport (
     scan_request,
 )
 from cudf._lib.pylibcudf.libcudf.table.table cimport table
+from cudf._lib.pylibcudf.libcudf.types cimport null_order, order
 
 from .column cimport Column
 from .table cimport Table
@@ -38,6 +39,9 @@ cdef class GroupByRequest:
 cdef class GroupBy:
     cdef unique_ptr[groupby] c_obj
     cdef Table _keys
+    cdef unique_ptr[vector[order]] _column_order
+    cdef unique_ptr[vector[null_order]] _null_precedence
+
     cpdef tuple aggregate(self, list requests)
     cpdef tuple scan(self, list requests)
     cpdef tuple shift(self, Table values, list offset, list fill_values)

python/cudf/cudf/_lib/pylibcudf/groupby.pyx

@@ -2,7 +2,7 @@
 
 from cython.operator cimport dereference
 from libcpp.functional cimport reference_wrapper
-from libcpp.memory cimport unique_ptr
+from libcpp.memory cimport make_unique, unique_ptr
 from libcpp.pair cimport pair
 from libcpp.utility cimport move
 from libcpp.vector cimport vector
@@ -22,7 +22,7 @@ from cudf._lib.pylibcudf.libcudf.types cimport size_type
 from .aggregation cimport Aggregation
 from .column cimport Column
 from .table cimport Table
-from .types cimport null_policy, sorted
+from .types cimport null_order, null_policy, order, sorted
 from .utils cimport _as_vector
 
 
@@ -87,17 +87,43 @@ cdef class GroupBy:
     keys : Table
         The columns to group by.
     null_handling : null_policy, optional
-        Whether or not to include null rows in ``keys``. Default is null_policy.EXCLUDE.
+        Whether or not to include null rows in `keys`.
+        Default is ``null_policy.EXCLUDE``.
     keys_are_sorted : sorted, optional
-        Whether the keys are already sorted. Default is sorted.NO.
+        Whether the keys are already sorted. Default is ``sorted.NO``.
+    column_order : list[order]
+        Indicates the order of each column. Default is ``order.ASCENDING``.
+        Ignored if `keys_are_sorted` is ``sorted.NO``.
+    null_precedence : list[null_order]
+        Indicates the ordering of null values in each column.
+        Default is ``null_order.AFTER``. Ignored if `keys_are_sorted` is ``sorted.NO``.
     """
     def __init__(
         self,
         Table keys,
         null_policy null_handling=null_policy.EXCLUDE,
-        sorted keys_are_sorted=sorted.NO
+        sorted keys_are_sorted=sorted.NO,
+        list column_order=None,
+        list null_precedence=None,
     ):
-        self.c_obj.reset(new groupby(keys.view(), null_handling, keys_are_sorted))
+        self._column_order = make_unique[vector[order]]()
+        self._null_precedence = make_unique[vector[null_order]]()
+        if column_order is not None:
+            for o in column_order:
+                dereference(self._column_order).push_back(<order?>o)
+        if null_precedence is not None:
+            for o in null_precedence:
+                dereference(self._null_precedence).push_back(<null_order?>o)
+
+        self.c_obj.reset(
+            new groupby(
+                keys.view(),
+                null_handling,
+                keys_are_sorted,
+                dereference(self._column_order.get()),
+                dereference(self._null_precedence.get()),
+            )
+        )
         # keep a reference to the keys table so it doesn't get
         # deallocated from under us:
         self._keys = keys

python/cudf_polars/cudf_polars/containers/column.py

@@ -13,6 +13,8 @@
 if TYPE_CHECKING:
     from typing_extensions import Self
 
+    import polars as pl
+
 __all__: list[str] = ["Column", "NamedColumn"]
 
 
@@ -76,12 +78,49 @@ def sorted_like(self, like: Column, /) -> Self:
 
         See Also
         --------
-        set_sorted
+        set_sorted, copy_metadata
         """
         return self.set_sorted(
             is_sorted=like.is_sorted, order=like.order, null_order=like.null_order
         )
 
+    def copy_metadata(self, from_: pl.Series, /) -> Self:
+        """
+        Copy metadata from a host series onto self.
+
+        Parameters
+        ----------
+        from_
+            Polars series to copy metadata from
+
+        Returns
+        -------
+        Self with metadata set.
+
+        See Also
+        --------
+        set_sorted, sorted_like
+        """
+        if len(from_) <= 1:
+            return self
+        ascending = from_.flags["SORTED_ASC"]
+        descending = from_.flags["SORTED_DESC"]
+        if ascending or descending:
+            has_null_first = from_.item(0) is None
+            has_null_last = from_.item(-1) is None
+            order = (
+                plc.types.Order.ASCENDING if ascending else plc.types.Order.DESCENDING
+            )
+            null_order = plc.types.NullOrder.BEFORE
+            if (descending and has_null_first) or (ascending and has_null_last):
+                null_order = plc.types.NullOrder.AFTER
+            return self.set_sorted(
+                is_sorted=plc.types.Sorted.YES,
+                order=order,
+                null_order=null_order,
+            )
+        return self
+
     def set_sorted(
         self,
         *,

python/cudf_polars/cudf_polars/containers/dataframe.py

@@ -9,16 +9,18 @@
 from functools import cached_property
 from typing import TYPE_CHECKING, cast
 
+import pyarrow as pa
+
 import polars as pl
 
 import cudf._lib.pylibcudf as plc
 
 from cudf_polars.containers.column import NamedColumn
+from cudf_polars.utils import dtypes
 
 if TYPE_CHECKING:
     from collections.abc import Mapping, Sequence, Set
 
-    import pyarrow as pa
     from typing_extensions import Self
 
     import cudf
@@ -50,8 +52,16 @@ def to_polars(self) -> pl.DataFrame:
             self.table,
             [plc.interop.ColumnMetadata(name=c.name) for c in self.columns],
         )
-
-        return cast(pl.DataFrame, pl.from_arrow(table))
+        return cast(pl.DataFrame, pl.from_arrow(table)).with_columns(
+            *(
+                pl.col(c.name).set_sorted(
+                    descending=c.order == plc.types.Order.DESCENDING
+                )
+                if c.is_sorted
+                else pl.col(c.name)
+                for c in self.columns
+            )
+        )
 
     @cached_property
     def column_names_set(self) -> frozenset[str]:
@@ -83,6 +93,35 @@ def from_cudf(cls, df: cudf.DataFrame) -> Self:
             ]
         )
 
+    @classmethod
+    def from_polars(cls, df: pl.DataFrame) -> Self:
+        """
+        Create from a polars dataframe.
+
+        Parameters
+        ----------
+        df
+            Polars dataframe to convert
+
+        Returns
+        -------
+        New dataframe representing the input.
+        """
+        table = df.to_arrow()
+        schema = table.schema
+        for i, field in enumerate(schema):
+            schema = schema.set(
+                i, pa.field(field.name, dtypes.downcast_arrow_lists(field.type))
+            )
+        # No-op if the schema is unchanged.
+        d_table = plc.interop.from_arrow(table.cast(schema))
+        return cls(
+            [
+                NamedColumn(column, h_col.name).copy_metadata(h_col)
+                for column, h_col in zip(d_table.columns(), df.iter_columns())
+            ]
+        )
+
     @classmethod
     def from_table(cls, table: plc.Table, names: Sequence[str]) -> Self:
         """

python/cudf_polars/cudf_polars/dsl/expr.py

@@ -867,7 +867,7 @@ def __init__(
         self.name = name
         self.options = options
         self.children = children
-        if self.name not in ("round", "unique"):
+        if self.name not in ("round", "unique", "setsorted"):
             raise NotImplementedError(f"Unary function {name=}")
 
     def do_evaluate(
@@ -923,6 +923,33 @@ def do_evaluate(
             if maintain_order:
                 return Column(column).sorted_like(values)
             return Column(column)
+        elif self.name == "setsorted":
+            (column,) = (
+                child.evaluate(df, context=context, mapping=mapping)
+                for child in self.children
+            )
+            (asc,) = self.options
+            order = (
+                plc.types.Order.ASCENDING
+                if asc == "ascending"
+                else plc.types.Order.DESCENDING
+            )
+            null_order = plc.types.NullOrder.BEFORE
+            if column.obj.null_count() > 0 and (n := column.obj.size()) > 1:
+                # PERF: This invokes four stream synchronisations!
+                has_nulls_first = not plc.copying.get_element(column.obj, 0).is_valid()
+                has_nulls_last = not plc.copying.get_element(
+                    column.obj, n - 1
+                ).is_valid()
+                if (order == plc.types.Order.DESCENDING and has_nulls_first) or (
+                    order == plc.types.Order.ASCENDING and has_nulls_last
+                ):
+                    null_order = plc.types.NullOrder.AFTER
+            return column.set_sorted(
+                is_sorted=plc.types.Sorted.YES,
+                order=order,
+                null_order=null_order,
+            )
         raise NotImplementedError(
             f"Unimplemented unary function {self.name=}"
         )  # pragma: no cover; init trips first

python/cudf_polars/cudf_polars/dsl/ir.py

@@ -30,7 +30,7 @@
 
 import cudf_polars.dsl.expr as expr
 from cudf_polars.containers import DataFrame, NamedColumn
-from cudf_polars.utils import dtypes, sorting
+from cudf_polars.utils import sorting
 
 if TYPE_CHECKING:
     from collections.abc import MutableMapping
@@ -385,17 +385,7 @@ def evaluate(self, *, cache: MutableMapping[int, DataFrame]) -> DataFrame:
         pdf = pl.DataFrame._from_pydf(self.df)
         if self.projection is not None:
             pdf = pdf.select(self.projection)
-        table = pdf.to_arrow()
-        schema = table.schema
-        for i, field in enumerate(schema):
-            schema = schema.set(
-                i, pa.field(field.name, dtypes.downcast_arrow_lists(field.type))
-            )
-        # No-op if the schema is unchanged.
-        table = table.cast(schema)
-        df = DataFrame.from_table(
-            plc.interop.from_arrow(table), list(self.schema.keys())
-        )
+        df = DataFrame.from_polars(pdf)
         assert all(
             c.obj.type() == dtype for c, dtype in zip(df.columns, self.schema.values())
         )
@@ -542,16 +532,17 @@ def evaluate(self, *, cache: MutableMapping[int, DataFrame]) -> DataFrame:
         keys = broadcast(
             *(k.evaluate(df) for k in self.keys), target_length=df.num_rows
         )
-        # TODO: use sorted information, need to expose column_order
-        # and null_precedence in pylibcudf groupby constructor
-        # sorted = (
-        #     plc.types.Sorted.YES
-        #     if all(k.is_sorted for k in keys)
-        #     else plc.types.Sorted.NO
-        # )
+        sorted = (
+            plc.types.Sorted.YES
+            if all(k.is_sorted for k in keys)
+            else plc.types.Sorted.NO
+        )
         grouper = plc.groupby.GroupBy(
             plc.Table([k.obj for k in keys]),
             null_handling=plc.types.NullPolicy.INCLUDE,
+            keys_are_sorted=sorted,
+            column_order=[k.order for k in keys],
+            null_precedence=[k.null_order for k in keys],
         )
         # TODO: uniquify
         requests = []

python/cudf_polars/tests/containers/test_dataframe.py

@@ -5,6 +5,8 @@
 
 import pytest
 
+import polars as pl
+
 import cudf._lib.pylibcudf as plc
 
 from cudf_polars.containers import DataFrame, NamedColumn
@@ -90,3 +92,52 @@ def test_shallow_copy():
     )
     assert df.columns[0].is_sorted == plc.types.Sorted.YES
     assert copy.columns[0].is_sorted == plc.types.Sorted.NO
+
+
+def test_sorted_flags_preserved_empty():
+    df = pl.DataFrame({"a": pl.Series([], dtype=pl.Int8())})
+    df.select(pl.col("a").sort())
+
+    gf = DataFrame.from_polars(df)
+
+    (a,) = gf.columns
+
+    assert a.is_sorted == plc.types.Sorted.YES
+
+    assert df.flags == gf.to_polars().flags
+
+
+@pytest.mark.parametrize("nulls_last", [True, False])
+def test_sorted_flags_preserved(with_nulls, nulls_last):
+    values = [1, 2, -1, 2, 4, 5]
+    if with_nulls:
+        values[4] = None
+    df = pl.DataFrame({"a": values, "b": values, "c": values})
+
+    df = df.select(
+        pl.col("a").sort(descending=False, nulls_last=nulls_last),
+        pl.col("b").sort(descending=True, nulls_last=nulls_last),
+        pl.col("c"),
+    )
+
+    gf = DataFrame.from_polars(df)
+
+    a_null_order = (
+        plc.types.NullOrder.AFTER
+        if nulls_last and with_nulls
+        else plc.types.NullOrder.BEFORE
+    )
+    b_null_order = (
+        plc.types.NullOrder.AFTER
+        if not nulls_last and with_nulls
+        else plc.types.NullOrder.BEFORE
+    )
+    a, b, c = gf.columns
+    assert a.is_sorted == plc.types.Sorted.YES
+    assert a.order == plc.types.Order.ASCENDING
+    assert a.null_order == a_null_order
+    assert b.is_sorted == plc.types.Sorted.YES
+    assert b.order == plc.types.Order.DESCENDING
+    assert b.null_order == b_null_order
+    assert c.is_sorted == plc.types.Sorted.NO
+    assert df.flags == gf.to_polars().flags

python/cudf_polars/tests/expressions/test_agg.py

@@ -20,13 +20,7 @@ def dtype(request):
     return request.param
 
 
-@pytest.fixture(
-    params=[
-        False,
-        pytest.param(True, marks=pytest.mark.xfail(reason="No handler for set_sorted")),
-    ],
-    ids=["unsorted", "sorted"],
-)
+@pytest.fixture(params=[False, True], ids=["unsorted", "sorted"])
 def is_sorted(request):
     return request.param