googleapis · TrevorBergeron · Jan 23, 2025 · Jan 16, 2025 · Jan 17, 2025 · Jan 23, 2025
@@ -405,8 +405,7 @@ def project_window_op(
             ArrayValue(
                 nodes.WindowOpNode(
                     child=self.node,
-                    column_name=ex.deref(column_name),
-                    op=op,
+                    expression=ex.UnaryAggregation(op, ex.deref(column_name)),
                     window_spec=window_spec,
                     output_name=ids.ColumnId(output_name),
                     never_skip_nulls=never_skip_nulls,

@@ -479,10 +479,9 @@ def _(
     return _apply_window_if_present(column.dense_rank(), window) + 1
 
 
-@compile_unary_agg.register
+@compile_nullary_agg.register
 def _(
     op: agg_ops.RowNumberOp,
-    column: ibis_types.Column,
     window=None,
 ) -> ibis_types.IntegerValue:
     return _apply_window_if_present(ibis_api.row_number(), window)

@@ -861,8 +861,7 @@ def promote_offsets(self, col_id: str) -> OrderedIR:
     ## Methods that only work with ordering
     def project_window_op(
         self,
-        column_name: ex.DerefOp,
-        op: agg_ops.UnaryWindowOp,
+        expression: ex.Aggregation,
         window_spec: WindowSpec,
         output_name: str,
         *,
@@ -881,53 +880,66 @@ def project_window_op(
         # See: https://github.com/ibis-project/ibis/issues/9773
         used_exprs = map(
                self._compile_expression,
-            itertools.chain(
-                (column_name,), map(ex.DerefOp, window_spec.all_referenced_columns)
+            map(
+                ex.DerefOp,
+                itertools.chain(
+                    expression.column_references, window_spec.all_referenced_columns
+                ),
             ),
         )
         can_directly_window = not any(
             map(lambda x: is_literal(x) or is_window(x), used_exprs)
         )
         if not can_directly_window:
             return self._reproject_to_table().project_window_op(
-                column_name,
-                op,
+                expression,
                 window_spec,
                 output_name,
                 never_skip_nulls=never_skip_nulls,
             )
 
-        column = typing.cast(ibis_types.Column, self._compile_expression(column_name))
         window = self._ibis_window_from_spec(
-            window_spec, require_total_order=op.uses_total_row_ordering
+            window_spec, require_total_order=expression.op.uses_total_row_ordering
         )
         bindings = {col: self._get_ibis_column(col) for col in self.column_ids}
 
         window_op = agg_compiler.compile_analytic(
-            ex.UnaryAggregation(op, column_name),
+            expression,
             window,
             bindings=bindings,
         )
 
+        inputs = tuple(
+            typing.cast(ibis_types.Column, self._compile_expression(ex.DerefOp(column)))
+            for column in expression.column_references
+        )
         clauses = []
-        if op.skips_nulls and not never_skip_nulls:
-            clauses.append((column.isnull(), ibis_types.null()))
-        if window_spec.min_periods:
-            if op.skips_nulls:
+        if expression.op.skips_nulls and not never_skip_nulls:
+            for column in inputs:
+                clauses.append((column.isnull(), ibis_types.null()))
+        if window_spec.min_periods and len(inputs) > 0:
+            if expression.op.skips_nulls:
                 # Most operations do not count NULL values towards min_periods
+                per_col_does_count = (column.notnull() for column in inputs)
+                # All inputs must be non-null for observation to count
+                is_observation = functools.reduce(
+                    lambda x, y: x & y, per_col_does_count
+                ).cast(int)
                 observation_count = agg_compiler.compile_analytic(
-                    ex.UnaryAggregation(agg_ops.count_op, column_name),
+                    ex.UnaryAggregation(agg_ops.sum_op, ex.deref("_observation_count")),
                     window,
-                    bindings=bindings,
+                    bindings={"_observation_count": is_observation},
                 )
             else:
                 # Operations like count treat even NULLs as valid observations for the sake of min_periods
                 # notnull is just used to convert null values to non-null (FALSE) values to be counted
-                denulled_value = typing.cast(ibis_types.BooleanColumn, column.notnull())
+                is_observation = inputs[0].notnull()
                 observation_count = agg_compiler.compile_analytic(
-                    ex.UnaryAggregation(agg_ops.count_op, ex.deref("_denulled")),
+                    ex.UnaryAggregation(
+                        agg_ops.count_op, ex.deref("_observation_count")
+                    ),
                     window,
-                    bindings={**bindings, "_denulled": denulled_value},
+                    bindings={"_observation_count": is_observation},
                 )
             clauses.append(
                 (

@@ -364,8 +364,7 @@ def compile_aggregate(self, node: nodes.AggregateNode, ordered: bool = True):
     @_compile_node.register
     def compile_window(self, node: nodes.WindowOpNode, ordered: bool = True):
         result = self.compile_ordered_ir(node.child).project_window_op(
-            node.column_name,
-            node.op,
+            node.expression,
             node.window_spec,
             node.output_name.sql,
             never_skip_nulls=node.never_skip_nulls,

@@ -16,7 +16,7 @@
 import dataclasses
 import functools
 import itertools
-from typing import cast, Sequence, TYPE_CHECKING
+from typing import cast, Sequence, Tuple, TYPE_CHECKING
 
 import bigframes.core
 import bigframes.core.expression as ex
@@ -125,6 +125,24 @@ def get_args(
                 f"Aggregation {agg} not yet supported in polars engine."
             )
 
+        def compile_agg_expr(self, expr: ex.Aggregation):
+            if isinstance(expr, ex.NullaryAggregation):
+                inputs: Tuple = ()
+            elif isinstance(expr, ex.UnaryAggregation):
+                assert isinstance(expr.arg, ex.DerefOp)
+                inputs = (expr.arg.id.sql,)
+            elif isinstance(expr, ex.BinaryAggregation):
+                assert isinstance(expr.left, ex.DerefOp)
+                assert isinstance(expr.right, ex.DerefOp)
+                inputs = (
+                    expr.left.id.sql,
+                    expr.right.id.sql,
+                )
+            else:
+                raise ValueError(f"Unexpected aggregation: {expr.op}")
+
+            return self.compile_agg_op(expr.op, inputs)
+
         def compile_agg_op(self, op: agg_ops.WindowOp, inputs: Sequence[str] = []):
             if isinstance(op, agg_ops.ProductOp):
                 # TODO: Need schema to cast back to original type if posisble (eg float back to int)
@@ -320,9 +338,9 @@ def compile_sample(self, node: nodes.RandomSampleNode):
     @compile_node.register
     def compile_window(self, node: nodes.WindowOpNode):
         df = self.compile_node(node.child)
-        agg_expr = self.agg_compiler.compile_agg_op(
-            node.op, [node.column_name.id.sql]
-        ).alias(node.output_name.sql)
+        agg_expr = self.agg_compiler.compile_agg_expr(node.expression).alias(
+            node.output_name.sql
+        )
         # Three window types: completely unbound, grouped and row bounded
 
         window = node.window_spec

@@ -33,7 +33,6 @@
 import bigframes.core.slices as slices
 import bigframes.core.window_spec as window
 import bigframes.dtypes
-import bigframes.operations.aggregations as agg_ops
 
 if typing.TYPE_CHECKING:
     import bigframes.core.ordering as orderings
@@ -1325,16 +1324,15 @@ def remap_refs(self, mappings: Mapping[bfet_ids.ColumnId, bfet_ids.ColumnId]):
 
 @dataclasses.dataclass(frozen=True, eq=False)
 class WindowOpNode(UnaryNode):
-    column_name: ex.DerefOp
-    op: agg_ops.UnaryWindowOp
+    expression: ex.Aggregation
     window_spec: window.WindowSpec
     output_name: bigframes.core.identifiers.ColumnId
     never_skip_nulls: bool = False
     skip_reproject_unsafe: bool = False
 
     def _validate(self):
         """Validate the local data in the node."""
-        assert self.column_name.id in self.child.ids
+        assert all(ref in self.child.ids for ref in self.expression.column_references)
 
     @property
     def non_local(self) -> bool:
@@ -1363,9 +1361,11 @@ def row_count(self) -> Optional[int]:
 
     @functools.cached_property
     def added_field(self) -> Field:
-        input_type = self.child.get_type(self.column_name.id)
-        new_item_dtype = self.op.output_type(input_type)
-        return Field(self.output_name, new_item_dtype)
+        input_types = self.child._dtype_lookup
+        return Field(
+            self.output_name,
+            bigframes.dtypes.dtype_for_etype(self.expression.output_type(input_types)),
+        )
 
     @property
     def node_defined_ids(self) -> Tuple[bfet_ids.ColumnId, ...]:
@@ -1376,7 +1376,7 @@ def prune(self, used_cols: COLUMN_SET) -> BigFrameNode:
             return self.child.prune(used_cols)
         consumed_ids = (
             used_cols.difference([self.output_name])
-            .union([self.column_name.id])
+            .union(self.expression.column_references)
             .union(self.window_spec.all_referenced_columns)
         )
         return self.transform_children(lambda x: x.prune(consumed_ids))
@@ -1391,7 +1391,7 @@ def remap_vars(
     def remap_refs(self, mappings: Mapping[bfet_ids.ColumnId, bfet_ids.ColumnId]):
         return dataclasses.replace(
             self,
-            column_name=self.column_name.remap_column_refs(
+            expression=self.expression.remap_column_refs(
                 mappings, allow_partial_bindings=True
             ),
             window_spec=self.window_spec.remap_column_refs(

@@ -381,7 +381,7 @@ def skips_nulls(self):
 
 # This should really by a NullaryWindowOp, but APIs don't support that yet.
 @dataclasses.dataclass(frozen=True)
-class RowNumberOp(UnaryWindowOp):
+class RowNumberOp(NullaryWindowOp):
     name: ClassVar[str] = "rownumber"
 
     @property