feat: Add size op support in local engine (#1865)

Author: TrevorBergeron

bigframes/session/polars_executor.py

@@ -20,6 +20,7 @@
 
 from bigframes.core import array_value, bigframe_node, expression, local_data, nodes
 import bigframes.operations
+from bigframes.operations import aggregations as agg_ops
 from bigframes.session import executor, semi_executor
 
 if TYPE_CHECKING:
@@ -32,9 +33,11 @@
     nodes.ReversedNode,
     nodes.SelectionNode,
     nodes.SliceNode,
+    nodes.AggregateNode,
 )
 
 _COMPATIBLE_SCALAR_OPS = ()
+_COMPATIBLE_AGG_OPS = (agg_ops.SizeOp, agg_ops.SizeUnaryOp)
 
 
 def _get_expr_ops(expr: expression.Expression) -> set[bigframes.operations.ScalarOp]:
@@ -48,7 +51,8 @@ def _is_node_polars_executable(node: nodes.BigFrameNode):
         return False
     for expr in node._node_expressions:
         if isinstance(expr, expression.Aggregation):
-            return False
+            if not type(expr.op) in _COMPATIBLE_AGG_OPS:
+                return False
         if isinstance(expr, expression.Expression):
             if not _get_expr_ops(expr).issubset(_COMPATIBLE_SCALAR_OPS):
                 return False

tests/system/small/engines/test_aggregation.py

@@ -0,0 +1,82 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import pytest
+
+from bigframes.core import array_value, expression, identifiers, nodes
+import bigframes.operations.aggregations as agg_ops
+from bigframes.session import polars_executor
+from bigframes.testing.engine_utils import assert_equivalence_execution
+
+pytest.importorskip("polars")
+
+# Polars used as reference as its fast and local. Generally though, prefer gbq engine where they disagree.
+REFERENCE_ENGINE = polars_executor.PolarsExecutor()
+
+
+@pytest.mark.parametrize("engine", ["polars", "bq"], indirect=True)
+def test_engines_aggregate_size(
+    scalars_array_value: array_value.ArrayValue,
+    engine,
+):
+    node = nodes.AggregateNode(
+        scalars_array_value.node,
+        aggregations=(
+            (
+                expression.NullaryAggregation(agg_ops.SizeOp()),
+                identifiers.ColumnId("size_op"),
+            ),
+            (
+                expression.UnaryAggregation(
+                    agg_ops.SizeUnaryOp(), expression.deref("string_col")
+                ),
+                identifiers.ColumnId("unary_size_op"),
+            ),
+        ),
+    )
+    assert_equivalence_execution(node, REFERENCE_ENGINE, engine)
+
+
+@pytest.mark.parametrize("engine", ["polars", "bq"], indirect=True)
+@pytest.mark.parametrize(
+    "grouping_cols",
+    [
+        ["bool_col"],
+        ["string_col", "int64_col"],
+        ["date_col"],
+        ["datetime_col"],
+        ["timestamp_col"],
+        ["bytes_col"],
+    ],
+)
+def test_engines_grouped_aggregate(
+    scalars_array_value: array_value.ArrayValue, engine, grouping_cols
+):
+    node = nodes.AggregateNode(
+        scalars_array_value.node,
+        aggregations=(
+            (
+                expression.NullaryAggregation(agg_ops.SizeOp()),
+                identifiers.ColumnId("size_op"),
+            ),
+            (
+                expression.UnaryAggregation(
+                    agg_ops.SizeUnaryOp(), expression.deref("string_col")
+                ),
+                identifiers.ColumnId("unary_size_op"),
+            ),
+        ),
+        by_column_ids=tuple(expression.deref(id) for id in grouping_cols),
+    )
+    assert_equivalence_execution(node, REFERENCE_ENGINE, engine)