damccorm commented on code in PR #37532:
URL: https://github.com/apache/beam/pull/37532#discussion_r3010122264
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sdks/python/apache_beam/transforms/util.py:
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@@ -1319,6 +1320,274 @@ def expand(self, pcoll):
self._batch_size_estimator, self._element_size_fn))
+def _default_element_size_fn(element: Any) -> int:
+ """Default element size function that tries len(), falls back to 1.
+
+ This function attempts to compute the size of an element using len().
+ If the element does not support len() (e.g., integers), it falls back to 1.
+
+ Args:
+ element: The element to compute the size of.
+
+ Returns:
+ The size of the element, or 1 if len() is not supported.
+ """
+ try:
+ return len(element)
+ except TypeError:
+ return 1
Review Comment:
We should probably warn in this case since this is almost certainly not what
the user desired. To avoid warning on every element, we can make this function
a member of the `_SortAndBatchElementsDoFn` and use a member variable to track
if we've already warned. That way we only warn once per DoFn instance
##########
sdks/python/apache_beam/testing/benchmarks/sort_and_batch_benchmark.py:
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@@ -0,0 +1,650 @@
+#
+# 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.
+#
+
+"""Benchmark: BatchElements vs SortAndBatchElements (weight-based splitting).
+
+Compares two batching strategies for variable-length inference workloads:
+
+- Baseline (BatchElements): fixed-count chunking, ignores element sizes.
+- Stateless (SortAndBatchElements): within each bundle, sorts elements
+ by size, then splits batches using max_batch_weight so that each batch
+ has a bounded total weight. The improvement comes from *changing batch
+ boundaries* (weight-based splitting), NOT from sorting alone -- sorting
+ within fixed boundaries yields 0% gain (verified by strict-control).
Review Comment:
> The improvement comes from *changing batch
> boundaries* (weight-based splitting), NOT from sorting alone
This is surprising to me - doesn't sorting the batch functionally change the
batch boundaries as well?
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