feat: Support local execution of comparison ops

bigframes/core/compile/polars/lowering.py

@@ -12,15 +12,31 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import dataclasses
+
 from bigframes import dtypes
 from bigframes.core import bigframe_node, expression
 from bigframes.core.rewrite import op_lowering
-from bigframes.operations import numeric_ops
+from bigframes.operations import comparison_ops, numeric_ops
 import bigframes.operations as ops
 
 # TODO: Would be more precise to actually have separate op set for polars ops (where they diverge from the original ops)
 
 
+@dataclasses.dataclass
+class CoerceArgsRule(op_lowering.OpLoweringRule):
+    op_type: type[ops.BinaryOp]
+
+    @property
+    def op(self) -> type[ops.ScalarOp]:
+        return self.op_type
+
+    def lower(self, expr: expression.OpExpression) -> expression.Expression:
+        assert isinstance(expr.op, self.op_type)
+        larg, rarg = _coerce_comparables(expr.children[0], expr.children[1])
+        return expr.op.as_expr(larg, rarg)
+
+
 class LowerFloorDivRule(op_lowering.OpLoweringRule):
     @property
     def op(self) -> type[ops.ScalarOp]:
@@ -40,7 +56,42 @@ def lower(self, expr: expression.OpExpression) -> expression.Expression:
         return ops.where_op.as_expr(zero_result, divisor_is_zero, expr)
 
 
-POLARS_LOWERING_RULES = (LowerFloorDivRule(),)
+def _coerce_comparables(expr1: expression.Expression, expr2: expression.Expression):
+
+    target_type = dtypes.coerce_to_common(expr1.output_type, expr2.output_type)
+    if expr1.output_type != target_type:
+        expr1 = _lower_cast(ops.AsTypeOp(target_type), expr1)
+    if expr2.output_type != target_type:
+        expr2 = _lower_cast(ops.AsTypeOp(target_type), expr2)
+    return expr1, expr2
+
+
+# TODO: Need to handle bool->string cast to get capitalization correct
+def _lower_cast(cast_op: ops.AsTypeOp, arg: expression.Expression):
+    if arg.output_type == dtypes.BOOL_DTYPE and dtypes.is_numeric(cast_op.to_type):
+        # bool -> decimal needs two-step cast
+        new_arg = ops.AsTypeOp(to_type=dtypes.INT_DTYPE).as_expr(arg)
+        return cast_op.as_expr(new_arg)
+    return cast_op.as_expr(arg)
+
+
+LOWER_COMPARISONS = tuple(
+    CoerceArgsRule(op)
+    for op in (
+        comparison_ops.EqOp,
+        comparison_ops.EqNullsMatchOp,
+        comparison_ops.NeOp,
+        comparison_ops.LtOp,
+        comparison_ops.GtOp,
+        comparison_ops.LeOp,
+        comparison_ops.GeOp,
+    )
+)
+
+POLARS_LOWERING_RULES = (
+    *LOWER_COMPARISONS,
+    LowerFloorDivRule(),
+)
 
 
 def lower_ops_to_polars(root: bigframe_node.BigFrameNode) -> bigframe_node.BigFrameNode:

bigframes/core/compile/scalar_op_compiler.py

@@ -1498,6 +1498,7 @@ def eq_op(
     x: ibis_types.Value,
     y: ibis_types.Value,
 ):
+    x, y = _coerce_comparables(x, y)
     return x == y
 
 
@@ -1507,6 +1508,7 @@ def eq_nulls_match_op(
     y: ibis_types.Value,
 ):
     """Variant of eq_op where nulls match each other. Only use where dtypes are known to be same."""
+    x, y = _coerce_comparables(x, y)
     literal = ibis_types.literal("$NULL_SENTINEL$")
     if hasattr(x, "fill_null"):
         left = x.cast(ibis_dtypes.str).fill_null(literal)
@@ -1523,6 +1525,7 @@ def ne_op(
     x: ibis_types.Value,
     y: ibis_types.Value,
 ):
+    x, y = _coerce_comparables(x, y)
     return x != y
 
 
@@ -1534,6 +1537,17 @@ def _null_or_value(value: ibis_types.Value, where_value: ibis_types.BooleanValue
     )
 
 
+def _coerce_comparables(
+    x: ibis_types.Value,
+    y: ibis_types.Value,
+):
+    if x.type().is_boolean() and not y.type().is_boolean():
+        x = x.cast(ibis_dtypes.int64)
+    elif y.type().is_boolean() and not x.type().is_boolean():
+        y = y.cast(ibis_dtypes.int64)
+    return x, y
+
+
 @scalar_op_compiler.register_binary_op(ops.and_op)
 def and_op(
     x: ibis_types.Value,
@@ -1735,6 +1749,7 @@ def lt_op(
     x: ibis_types.Value,
     y: ibis_types.Value,
 ):
+    x, y = _coerce_comparables(x, y)
     return x < y
 
 
@@ -1744,6 +1759,7 @@ def le_op(
     x: ibis_types.Value,
     y: ibis_types.Value,
 ):
+    x, y = _coerce_comparables(x, y)
     return x <= y
 
 
@@ -1753,6 +1769,7 @@ def gt_op(
     x: ibis_types.Value,
     y: ibis_types.Value,
 ):
+    x, y = _coerce_comparables(x, y)
     return x > y
 
 
@@ -1762,6 +1779,7 @@ def ge_op(
     x: ibis_types.Value,
     y: ibis_types.Value,
 ):
+    x, y = _coerce_comparables(x, y)
     return x >= y
 
 

bigframes/session/polars_executor.py

@@ -32,11 +32,20 @@
     nodes.OrderByNode,
     nodes.ReversedNode,
     nodes.SelectionNode,
+    nodes.ProjectionNode,
     nodes.SliceNode,
     nodes.AggregateNode,
 )
 
-_COMPATIBLE_SCALAR_OPS = ()
+_COMPATIBLE_SCALAR_OPS = (
+    bigframes.operations.eq_op,
+    bigframes.operations.eq_null_match_op,
+    bigframes.operations.ne_op,
+    bigframes.operations.gt_op,
+    bigframes.operations.lt_op,
+    bigframes.operations.ge_op,
+    bigframes.operations.le_op,
+)
 _COMPATIBLE_AGG_OPS = (agg_ops.SizeOp, agg_ops.SizeUnaryOp)
 
 

tests/system/small/engines/test_comparison_ops.py

@@ -0,0 +1,70 @@
+# 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 itertools
+
+import pytest
+
+from bigframes.core import array_value
+import bigframes.operations as 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()
+
+# numeric domain
+
+
+def apply_op_pairwise(
+    array: array_value.ArrayValue, op: ops.BinaryOp, excluded_cols=[]
+) -> array_value.ArrayValue:
+    exprs = []
+    for l_arg, r_arg in itertools.permutations(array.column_ids, 2):
+        if (l_arg in excluded_cols) or (r_arg in excluded_cols):
+            continue
+        try:
+            _ = op.output_type(
+                array.get_column_type(l_arg), array.get_column_type(r_arg)
+            )
+            exprs.append(op.as_expr(l_arg, r_arg))
+        except TypeError:
+            continue
+    assert len(exprs) > 0
+    new_arr, _ = array.compute_values(exprs)
+    return new_arr
+
+
+@pytest.mark.parametrize("engine", ["polars", "bq"], indirect=True)
+@pytest.mark.parametrize(
+    "op",
+    [
+        ops.eq_op,
+        ops.eq_null_match_op,
+        ops.ne_op,
+        ops.gt_op,
+        ops.lt_op,
+        ops.le_op,
+        ops.ge_op,
+    ],
+)
+def test_engines_project_comparison_op(
+    scalars_array_value: array_value.ArrayValue, engine, op
+):
+    # exclude string cols as does not contain dates
+    # bool col actually doesn't work properly for bq engine
+    arr = apply_op_pairwise(scalars_array_value, op, excluded_cols=["string_col"])
+    assert_equivalence_execution(arr.node, REFERENCE_ENGINE, engine)