googleapis · TrevorBergeron · Jul 1, 2025 · Jun 28, 2025 · Jun 30, 2025 · Jun 30, 2025
@@ -35,6 +35,7 @@
     nodes.ProjectionNode,
     nodes.SliceNode,
     nodes.AggregateNode,
+    nodes.FilterNode,
 )
 
 _COMPATIBLE_SCALAR_OPS = (

@@ -0,0 +1,67 @@
+# 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, nodes
+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()
+
+
+@pytest.mark.parametrize("engine", ["polars", "bq"], indirect=True)
+def test_engines_filter_bool_col(
+    scalars_array_value: array_value.ArrayValue,
+    engine,
+):
+    node = nodes.FilterNode(
+        scalars_array_value.node, predicate=expression.deref("bool_col")
+    )
+    assert_equivalence_execution(node, REFERENCE_ENGINE, engine)
+
+
+@pytest.mark.parametrize("engine", ["polars", "bq"], indirect=True)
+def test_engines_filter_expr_cond(
+    scalars_array_value: array_value.ArrayValue,
+    engine,
+):
+    predicate = ops.gt_op.as_expr(
+        expression.deref("float64_col"), expression.deref("int64_col")
+    )
+    node = nodes.FilterNode(scalars_array_value.node, predicate=predicate)
+    assert_equivalence_execution(node, REFERENCE_ENGINE, engine)
+
+
+@pytest.mark.parametrize("engine", ["polars", "bq"], indirect=True)
+def test_engines_filter_true(
+    scalars_array_value: array_value.ArrayValue,
+    engine,
+):
+    predicate = expression.const(True)
+    node = nodes.FilterNode(scalars_array_value.node, predicate=predicate)
+    assert_equivalence_execution(node, REFERENCE_ENGINE, engine)
+
+
+@pytest.mark.parametrize("engine", ["polars", "bq"], indirect=True)
+def test_engines_filter_false(
+    scalars_array_value: array_value.ArrayValue,
+    engine,
+):
+    predicate = expression.const(False)
+    node = nodes.FilterNode(scalars_array_value.node, predicate=predicate)
+    assert_equivalence_execution(node, REFERENCE_ENGINE, engine)
@@ -53,8 +53,7 @@ def test_polar_execution_sorted_filtered(session_w_polars, scalars_pandas_df_ind
         .to_pandas()
     )
 
-    # Filter and isnull not supported by polar engine yet, so falls back to bq execution
-    assert session_w_polars._metrics.execution_count == (execution_count_before + 1)
+    assert session_w_polars._metrics.execution_count == execution_count_before
     assert_pandas_df_equal(bf_result, pd_result)