python / python/pyperformance

asyncio_websockets tests the implementation of `zlib`, not of Python

Aperta
#460 2 commenti 1 reazione 0 assegnatari Vedi su GitHub

Nessuno ha ancora preso questa issue.

Lingua principale
Python
Stelle
1k
Fork
203
Merge medio
1h 20m
PR unite (30g)
2

Descrizione

I found out that the asyncio_websockets benchmark spends ~87% of runtime in zlib (i.e. in the shared library libz.so), or whatever compression library is the default on the system-under-test.

In other words, asyncio_websockets tests the implementation of compression/decompression algorithms rather than anything to do with the Python interpreter or the websockets Python module. Websockets indeed enables compression by default: https://websockets.readthedocs.io/en/stable/topics/compression.html, excerpt from that official documentation:

connect() and serve() enable compression by default because the reduction in network bandwidth is usually worth the additional memory and CPU cost.

Problem

I believe this benchmark may not be measuring what's intended in its current form. For example, a replacement of zlib with zlib-ng or zlib-rs (which are newer drop-in replacement of zlib) may significantly affect the performance score of this benchmark, even though nothing changed in Python and/or websockets implementations. It is hard to root cause such performance modification, without knowing this detail about the asyncio_websockets benchmark.

It is also used in e.g. Phoronix testing, which may lead to unexpected conclusions for readers who aren't aware of this detail. Example: https://www.phoronix.com/review/cachyos-ubuntu-2510-f43/5.

Solutions

I see the following solutions:

  1. Clearly document this behavior in https://pyperformance.readthedocs.io/benchmarks.html (in fact, there is no mention of websockets benchmark at all).
  2. Remove this benchmark, since the workload is dominated by native zlib rather than Python or websockets logic.
  3. Modify this benchmark to disable compression, as described here: https://websockets.readthedocs.io/en/stable/topics/compression.html#configuring-compression

I'd lean towards option 3 (disabling compression) as it preserves the benchmark's intent while removing the zlib dependency from results. I'm happy to submit a PR if the maintainers agree.

Reproducing

I ran it with a Amazon Linux 2023 docker container (OS distro similar to Fedora):

docker run --rm -it amazonlinux:2023 /bin/bash # -->

dnf install -y pip perf dnf-utils
dnf debuginfo-install zlib python3.9
python3 -m pip install pyperformance
python3 -m pip install websockets==11.0.3 pyperf==2.6.3

perf record -g --call-graph dwarf -- \
  python3 -u /usr/local/lib/python3.9/site-packages/pyperformance/data-files/benchmarks/bm_asyncio_websockets/run_benchmark.py

After running the benchmark, we can examine the resulting perf.data file:

$ perf report --hierarchy
...
-   99.93%        python3
   -   87.22%        libz.so.1.2.11
      +   40.11%        [.] inflate_fast
      +   36.28%        [.] deflate_slow
      ...
   +    5.20%        libpython3.9.so.1.0
   +    1.60%        libc.so.6
   ...

P.S. Thank you for maintaining the pyperformance project!

Guida per i contributori

Nessuna guida per i contributori indicizzata per questo repository

Come iniziare

  1. Leggi tutta la issue e poi la guida ai contributi del progetto.
  2. Commenta sulla issue per dire che te ne occupi tu — evita che due persone facciano lo stesso lavoro.
  3. Fai un fork del repository e lavora su un branch.
  4. Apri una pull request che faccia riferimento al numero della issue.

Direzione di ricerca

Inizia da pyperformance/data-files/benchmarks/bm_asyncio_websockets/run_benchmark.py e riproduci il profilo con perf per confermare la quota di zlib. Esamina le indicazioni collegate sulla compressione di websockets e il punto di ingresso della documentazione del benchmark. Il lavoro è completo quando la soluzione scelta dai maintainers è implementata e il comportamento di compressione del benchmark è chiaramente documentato o escluso dal carico di lavoro misurato.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Valutazione

Stack tecnologico
python
Ambito
performance, testing-qa
Tipo di issue
Bug
Difficoltà
4/5
Tempo stimato
3-5 giorni
Stato di attività
Attiva
Chiarezza
Abbastanza chiara
Idoneità per principianti
48/100

Ricevi le nuove issue nella tua casella

Un breve riepilogo di issue GitHub adatte ai principianti.