damccorm opened a new pull request, #41127:
URL: https://github.com/apache/beam/pull/41127
### Description
Optimizes `_IntervalWindowBase.__eq__` and `__hash__` in
`sdks/python/apache_beam/utils/windowed_value.py` and `windowed_value.pxd`:
1. **Exact-type fast path in `_IntervalWindowBase.__eq__`:**
- Checks `type(self) is type(other)` first to compare `_start_micros ==
other._start_micros and _end_micros == other._end_micros` directly.
2. **Avoid tuple allocation in `_IntervalWindowBase.__hash__`:**
- Replaces `hash((self._start_micros, self._end_micros))` with direct
integer bit-mixing without allocating a 2-tuple per hash lookup.
### Benchmarks & Performance Impact
- **Microbenchmark:** [`bench_04_interval_window_eq_hash`
(`c2feb961eef`)](https://github.com/damccorm/beam/blob/c2feb961eef2e7d2410825aab9537c62a95e6790/sdks/python/apache_beam/testing/benchmarks/python_sdk_perf/microbenchmarks.py#L107-L117)
(on branch
[`perf/py-benchmarks-suite`](https://github.com/damccorm/beam/tree/perf/py-benchmarks-suite))
— 1,000,000 `IntervalWindow` equality and `hash()` calls improved by **6.27x
(`-84.1%`)** on `__eq__` and **3.04x (`-67.1%`)** on `__hash__`.
- **End-to-End Cloud Dataflow Benchmark (`core_window_row_combine`):**
Included in [`run_core_window_row_combine_pipeline`
(`c2feb961eef`)](https://github.com/damccorm/beam/blob/c2feb961eef2e7d2410825aab9537c62a95e6790/sdks/python/apache_beam/testing/benchmarks/python_sdk_perf/dataflow_e2e_benchmarks.py#L274-L302)
(3,000,000 generated events -> 9,000,000 sliding-windowed elements on a single
`n2-standard-4` worker), which improved end-to-end worker stage execution time
by **1.80x (`-44.5%`, `599.6s` -> `332.9s`)** and reduced total billable
Dataflow vCPU/Memory/PD usage by **`-26.1%` (`1,134` -> `838` vCPU-s)**.
### Testing
- Verified with `pytest sdks/python/apache_beam/transforms/window_test.py
sdks/python/apache_beam/utils/windowed_value_test.py`.
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