chore: Add a function to traverse BFET and encode type usage (#2390)

Next step is to add the encoded usage to the job_config.label before SQL
dispatch.

Related bug: b/406578908

Author: sycai

bigframes/core/logging/data_types.py

@@ -12,15 +12,115 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+from __future__ import annotations
+
+import functools
 
 from bigframes import dtypes
+from bigframes.core import agg_expressions, bigframe_node, expression, nodes
+from bigframes.core.rewrite import schema_binding
+
+IGNORED_NODES = (
+    nodes.SelectionNode,
+    nodes.ReadLocalNode,
+    nodes.ReadTableNode,
+    nodes.ConcatNode,
+    nodes.RandomSampleNode,
+    nodes.FromRangeNode,
+    nodes.PromoteOffsetsNode,
+    nodes.ReversedNode,
+    nodes.SliceNode,
+    nodes.ResultNode,
+)
+
+
+def encode_type_refs(root: bigframe_node.BigFrameNode) -> str:
+    return f"{root.reduce_up(_encode_type_refs_from_node):x}"
+
+
+def _encode_type_refs_from_node(
+    node: bigframe_node.BigFrameNode, child_results: tuple[int, ...]
+) -> int:
+    child_result = functools.reduce(lambda x, y: x | y, child_results, 0)
+
+    curr_result = 0
+    if isinstance(node, nodes.FilterNode):
+        curr_result = _encode_type_refs_from_expr(node.predicate, node.child)
+    elif isinstance(node, nodes.ProjectionNode):
+        for assignment in node.assignments:
+            expr = assignment[0]
+            if isinstance(expr, (expression.DerefOp)):
+                # Ignore direct assignments in projection nodes.
+                continue
+            curr_result = curr_result | _encode_type_refs_from_expr(
+                assignment[0], node.child
+            )
+    elif isinstance(node, nodes.OrderByNode):
+        for by in node.by:
+            curr_result = curr_result | _encode_type_refs_from_expr(
+                by.scalar_expression, node.child
+            )
+    elif isinstance(node, nodes.JoinNode):
+        for left, right in node.conditions:
+            curr_result = (
+                curr_result
+                | _encode_type_refs_from_expr(left, node.left_child)
+                | _encode_type_refs_from_expr(right, node.right_child)
+            )
+    elif isinstance(node, nodes.InNode):
+        curr_result = _encode_type_refs_from_expr(node.left_col, node.left_child)
+    elif isinstance(node, nodes.AggregateNode):
+        for agg, _ in node.aggregations:
+            curr_result = curr_result | _encode_type_refs_from_expr(agg, node.child)
+    elif isinstance(node, nodes.WindowOpNode):
+        for grouping_key in node.window_spec.grouping_keys:
+            curr_result = curr_result | _encode_type_refs_from_expr(
+                grouping_key, node.child
+            )
+        for ordering_expr in node.window_spec.ordering:
+            curr_result = curr_result | _encode_type_refs_from_expr(
+                ordering_expr.scalar_expression, node.child
+            )
+        for col_def in node.agg_exprs:
+            curr_result = curr_result | _encode_type_refs_from_expr(
+                col_def.expression, node.child
+            )
+    elif isinstance(node, nodes.ExplodeNode):
+        for col_id in node.column_ids:
+            curr_result = curr_result | _encode_type_refs_from_expr(col_id, node.child)
+    elif isinstance(node, IGNORED_NODES):
+        # Do nothing
+        pass
+    else:
+        # For unseen nodes, do not raise errors as this is the logging path, but
+        # we should cover those nodes either in the branches above, or place them
+        # in the IGNORED_NODES collection.
+        pass
+
+    return child_result | curr_result
+
+
+def _encode_type_refs_from_expr(
+    expr: expression.Expression, child_node: bigframe_node.BigFrameNode
+) -> int:
+    # TODO(b/409387790): Remove this branch once SQLGlot compiler fully replaces Ibis compiler
+    if not expr.is_resolved:
+        if isinstance(expr, agg_expressions.Aggregation):
+            expr = schema_binding._bind_schema_to_aggregation_expr(expr, child_node)
+        else:
+            expr = expression.bind_schema_fields(expr, child_node.field_by_id)
 
+    result = _get_dtype_mask(expr.output_type)
+    for child_expr in expr.children:
+        result = result | _encode_type_refs_from_expr(child_expr, child_node)
 
-def _add_data_type(existing_types: int, curr_type: dtypes.Dtype) -> int:
-    return existing_types | _get_dtype_mask(curr_type)
+    return result
 
 
-def _get_dtype_mask(dtype: dtypes.Dtype) -> int:
+def _get_dtype_mask(dtype: dtypes.Dtype | None) -> int:
+    if dtype is None:
+        # If the dtype is not given, ignore
+        return 0
     if dtype == dtypes.INT_DTYPE:
         return 1 << 1
     if dtype == dtypes.FLOAT_DTYPE:

tests/system/small/core/logging/__init__.py

@@ -0,0 +1,13 @@
+# Copyright 2026 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.

tests/system/small/core/logging/test_data_types.py

@@ -0,0 +1,113 @@
+# Copyright 2026 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.
+
+from typing import Sequence
+
+import pandas as pd
+import pyarrow as pa
+
+from bigframes import dtypes
+from bigframes.core.logging import data_types
+import bigframes.pandas as bpd
+
+
+def encode_types(inputs: Sequence[dtypes.Dtype]) -> str:
+    encoded_val = 0
+    for t in inputs:
+        encoded_val = encoded_val | data_types._get_dtype_mask(t)
+
+    return f"{encoded_val:x}"
+
+
+def test_get_type_refs_no_op(scalars_df_index):
+    node = scalars_df_index._block._expr.node
+    expected_types: list[dtypes.Dtype] = []
+
+    assert data_types.encode_type_refs(node) == encode_types(expected_types)
+
+
+def test_get_type_refs_projection(scalars_df_index):
+    node = (
+        scalars_df_index["datetime_col"] - scalars_df_index["datetime_col"]
+    )._block._expr.node
+    expected_types = [dtypes.DATETIME_DTYPE, dtypes.TIMEDELTA_DTYPE]
+
+    assert data_types.encode_type_refs(node) == encode_types(expected_types)
+
+
+def test_get_type_refs_filter(scalars_df_index):
+    node = scalars_df_index[scalars_df_index["int64_col"] > 0]._block._expr.node
+    expected_types = [dtypes.INT_DTYPE, dtypes.BOOL_DTYPE]
+
+    assert data_types.encode_type_refs(node) == encode_types(expected_types)
+
+
+def test_get_type_refs_order_by(scalars_df_index):
+    node = scalars_df_index.sort_index()._block._expr.node
+    expected_types = [dtypes.INT_DTYPE]
+
+    assert data_types.encode_type_refs(node) == encode_types(expected_types)
+
+
+def test_get_type_refs_join(scalars_df_index):
+    node = (
+        scalars_df_index[["int64_col"]].merge(
+            scalars_df_index[["float64_col"]],
+            left_on="int64_col",
+            right_on="float64_col",
+        )
+    )._block._expr.node
+    expected_types = [dtypes.INT_DTYPE, dtypes.FLOAT_DTYPE]
+
+    assert data_types.encode_type_refs(node) == encode_types(expected_types)
+
+
+def test_get_type_refs_isin(scalars_df_index):
+    node = scalars_df_index["string_col"].isin(["a"])._block._expr.node
+    expected_types = [dtypes.STRING_DTYPE, dtypes.BOOL_DTYPE]
+
+    assert data_types.encode_type_refs(node) == encode_types(expected_types)
+
+
+def test_get_type_refs_agg(scalars_df_index):
+    node = scalars_df_index[["bool_col", "string_col"]].count()._block._expr.node
+    expected_types = [
+        dtypes.INT_DTYPE,
+        dtypes.BOOL_DTYPE,
+        dtypes.STRING_DTYPE,
+        dtypes.FLOAT_DTYPE,
+    ]
+
+    assert data_types.encode_type_refs(node) == encode_types(expected_types)
+
+
+def test_get_type_refs_window(scalars_df_index):
+    node = (
+        scalars_df_index[["string_col", "bool_col"]]
+        .groupby("string_col")
+        .rolling(window=3)
+        .count()
+        ._block._expr.node
+    )
+    expected_types = [dtypes.STRING_DTYPE, dtypes.BOOL_DTYPE, dtypes.INT_DTYPE]
+
+    assert data_types.encode_type_refs(node) == encode_types(expected_types)
+
+
+def test_get_type_refs_explode():
+    df = bpd.DataFrame({"A": ["a", "b"], "B": [[1, 2], [3, 4, 5]]})
+    node = df.explode("B")._block._expr.node
+    expected_types = [pd.ArrowDtype(pa.list_(pa.int64()))]
+
+    assert data_types.encode_type_refs(node) == encode_types(expected_types)

tests/unit/core/logging/test_data_types.py

@@ -29,6 +29,7 @@
 @pytest.mark.parametrize(
     ("dtype", "expected_mask"),
     [
+        (None, 0),
         (UNKNOWN_TYPE, 1 << 0),
         (dtypes.INT_DTYPE, 1 << 1),
         (dtypes.FLOAT_DTYPE, 1 << 2),
@@ -51,19 +52,3 @@
 )
 def test_get_dtype_mask(dtype, expected_mask):
     assert data_types._get_dtype_mask(dtype) == expected_mask
-
-
-def test_add_data_type__type_overlap_no_op():
-    curr_type = dtypes.STRING_DTYPE
-    existing_types = data_types._get_dtype_mask(curr_type)
-
-    assert data_types._add_data_type(existing_types, curr_type) == existing_types
-
-
-def test_add_data_type__new_type_updated():
-    curr_type = dtypes.STRING_DTYPE
-    existing_types = data_types._get_dtype_mask(dtypes.INT_DTYPE)
-
-    assert data_types._add_data_type(
-        existing_types, curr_type
-    ) == existing_types | data_types._get_dtype_mask(curr_type)