geruh commented on code in PR #3046:
URL: https://github.com/apache/iceberg-python/pull/3046#discussion_r2881748803
##########
pyiceberg/table/__init__.py:
##########
@@ -1960,13 +2049,11 @@ def _build_residual_evaluator(self, spec_id: int) ->
Callable[[DataFile], Residu
# The lambda created here is run in multiple threads.
# So we avoid creating _EvaluatorExpression methods bound to a single
# shared instance across multiple threads.
- return lambda datafile: (
- residual_evaluator_of(
- spec=spec,
- expr=self.row_filter,
- case_sensitive=self.case_sensitive,
- schema=self.table_metadata.schema(),
- )
+ return lambda datafile: residual_evaluator_of(
Review Comment:
nit: this is a cosmetic change
##########
tests/benchmark/test_read_benchmark.py:
##########
@@ -0,0 +1,165 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you 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.
+"""Read throughput micro-benchmark for ArrowScan configurations.
+
+Measures records/sec and peak Arrow memory across ScanOrder, concurrent_files,
+and batch_size configurations introduced for issue #3036.
+
+Memory is measured using pa.total_allocated_bytes() which tracks PyArrow's C++
+memory pool (Arrow buffers, Parquet decompression), not Python heap
allocations.
+
+Run with: uv run pytest tests/benchmark/test_read_benchmark.py -v -s
+"""
+
Review Comment:
Can you mark with `@pytest.mark.benchmark`
##########
tests/catalog/test_hive.py:
##########
Review Comment:
I think you could just rebase to reduce the noise here
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