Expunge as_frame conversions in Column algorithms

python/cudf/cudf/core/column/column.py

@@ -943,14 +943,14 @@ def is_unique(self) -> bool:
 
     @property
     def is_monotonic_increasing(self) -> bool:
-        return not self.has_nulls() and self.as_frame()._is_sorted(
-            ascending=None, null_position=None
+        return not self.has_nulls() and libcudf.sort.is_sorted(
+            [self], [True], None
         )
 
     @property
     def is_monotonic_decreasing(self) -> bool:
-        return not self.has_nulls() and self.as_frame()._is_sorted(
-            ascending=[False], null_position=None
+        return not self.has_nulls() and libcudf.sort.is_sorted(
+            [self], [False], None
         )
 
     def sort_values(
@@ -1134,8 +1134,8 @@ def apply_boolean_mask(self, mask) -> ColumnBase:
     def argsort(
         self, ascending: bool = True, na_position: str = "last"
     ) -> "cudf.core.column.NumericalColumn":
-        return self.as_frame()._get_sorted_inds(
-            ascending=ascending, na_position=na_position
+        return libcudf.sort.order_by(
+            [self], [ascending], na_position, stable=True
         )
 
     def __arrow_array__(self, type=None):
@@ -1161,10 +1161,17 @@ def searchsorted(
         side: str = "left",
         ascending: bool = True,
         na_position: str = "last",
-    ):
-        values = as_column(value).as_frame()
-        return self.as_frame().searchsorted(
-            values, side, ascending=ascending, na_position=na_position
+    ) -> Self:
+        if not isinstance(value, ColumnBase) or value.dtype != self.dtype:
+            raise ValueError(
+                "Column searchsorted expects values to be column of same dtype"
+            )
+        return libcudf.search.search_sorted(
+            [self],
+            [value],
+            side=side,
+            ascending=ascending,
+            na_position=na_position,
         )
 
     def unique(self) -> ColumnBase:

python/cudf/cudf/core/column/decimal.py

@@ -10,7 +10,6 @@
 
 import cudf
 from cudf import _lib as libcudf
-from cudf._lib.quantiles import quantile as cpp_quantile
 from cudf._lib.strings.convert.convert_fixed_point import (
     from_decimal as cpp_from_decimal,
 )
@@ -192,15 +191,12 @@ def _decimal_quantile(
     ) -> ColumnBase:
         quant = [float(q)] if not isinstance(q, (Sequence, np.ndarray)) else q
         # get sorted indices and exclude nulls
-        sorted_indices = self.as_frame()._get_sorted_inds(
-            ascending=True, na_position="first"
+        indices = libcudf.sort.order_by(
+            [self], [True], "first", stable=True
+        ).slice(self.null_count, len(self))
+        result = libcudf.quantiles.quantile(
+            self, quant, interpolation, indices, exact
         )
-        sorted_indices = sorted_indices[self.null_count :]
-
-        result = cpp_quantile(
-            self, quant, interpolation, sorted_indices, exact
-        )
-
         return result._with_type_metadata(self.dtype)
 
     def as_numerical_column(

python/cudf/cudf/core/column/numerical_base.py

@@ -182,15 +182,12 @@ def _numeric_quantile(
         self, q: np.ndarray, interpolation: str, exact: bool
     ) -> NumericalBaseColumn:
         # get sorted indices and exclude nulls
-        sorted_indices = self.as_frame()._get_sorted_inds(
-            ascending=True, na_position="first"
-        )
-        sorted_indices = sorted_indices.slice(
-            self.null_count, len(sorted_indices)
-        )
+        indices = libcudf.sort.order_by(
+            [self], [True], "first", stable=True
+        ).slice(self.null_count, len(self))
 
         return libcudf.quantiles.quantile(
-            self, q, interpolation, sorted_indices, exact
+            self, q, interpolation, indices, exact
         )
 
     def cov(self, other: NumericalBaseColumn) -> float:

python/cudf/cudf/core/indexed_frame.py

@@ -3260,8 +3260,11 @@ def _first_or_last(
             # is on the end of the offset. See pandas gh29623 for detail.
             to_search = to_search - pd_offset.base
             return self.loc[:to_search]
+        needle = as_column(to_search, dtype=self._index.dtype)
         end_point = int(
-            self._index._column.searchsorted(to_search, side=side)[0]
+            self._index._column.searchsorted(
+                needle, side=side
+            ).element_indexing(0)
         )
         return slice_func(end_point)
 

python/cudf/cudf/tests/test_search.py

@@ -38,7 +38,10 @@ def test_searchsorted(side, obj_class, vals_class):
     pvals = vals.to_pandas()
 
     expect = psr.searchsorted(pvals, side)
-    got = sr.searchsorted(vals, side)
+    if obj_class == "column":
+        got = sr.searchsorted(vals._column, side)
+    else:
+        got = sr.searchsorted(vals, side)
 
     assert_eq(expect, cupy.asnumpy(got))