Valentyn Tymofieiev created BEAM-4858:
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Summary: Clean up _BatchSizeEstimator in element-batching
transform.
Key: BEAM-4858
URL: https://issues.apache.org/jira/browse/BEAM-4858
Project: Beam
Issue Type: Bug
Components: sdk-py-core
Reporter: Valentyn Tymofieiev
Assignee: Robert Bradshaw
Beam Python 3 conversion [exposed|https://github.com/apache/beam/pull/3971]
non-trivial performance-sensitive logic in element-batching transform. Let's
take a look at
[util.py#L271|https://github.com/apache/beam/blob/e98ff7c96afa2f72b3a98426dc1e9a47224da5c8/sdks/python/apache_beam/transforms/util.py#L271].
Due to Python 2 language semantics, the result of {{x2 / x1}} will depend on
the type of the keys - whether they are integers or floats.
The keys of key-value pairs contained in {{self._data}} are added as integers
[here|https://github.com/apache/beam/blob/d2ac08da2dccce8930432fae1ec7c30953880b69/sdks/python/apache_beam/transforms/util.py#L260],
however, when we 'thin' the collected entries
[here|https://github.com/apache/beam/blob/d2ac08da2dccce8930432fae1ec7c30953880b69/sdks/python/apache_beam/transforms/util.py#L279],
the keys will become floats. Surprisingly, using either integer or float
division [in the
comparator|https://github.com/apache/beam/blob/e98ff7c96afa2f72b3a98426dc1e9a47224da5c8/sdks/python/apache_beam/transforms/util.py#L271]
consistently negatively affects the performance of a custom pipeline I was
using to benchmark these changes.
In terms of Python 3 conversion the best course of action seems to be to
preserve the existing Python 2 behavior using old_div from `past.division`, in
long term we may want to add microbenchmark that we can use to target this code
and evaluate it's performance, clean up the logic, and maybe cythonize since
this code seems to be performance-critical.
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