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98 lines
2.3 KiB
Markdown
98 lines
2.3 KiB
Markdown
---
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layout: doc
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title: Profiling
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permalink: /en/doc/profiling/
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redirect_from:
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- /doc/Profiling/
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- /wiki/Profiling/
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---
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Profiling
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=========
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This is python profiling primer.
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For the purpose of this document, `qubes-dev` is name of the domain used for postprocessing profiling stats.
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Requirements
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------------
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~~~
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yum install gprof2dot graphviz
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git clone http://git.woju.eu/qubes/profiling.git
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~~~
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If you profile something on dom0, move `Upload.sh` from repository to dom0:
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~~~
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mkdir -p ~/profiling
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qvm-run -p qubes-dev 'cat ~/profiling/Upload.sh' > ~/profiling/Upload.sh
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~~~
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- WARNING: this will obviously be running third party code which is not signed by ITL nor Fedora. You have been warned.
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Workflow
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--------
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### Identify function responsible for some slow action
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You have to select area in which you suspect less than optimal performance. If you do not narrow the area, graphs may be unreadable.
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### Replace suspect function with probe
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Replace
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def foo(self, bar):
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# function content
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with
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def foo(self, *args, **kwargs):
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profile.runctx('self.real_foo(*args, **kwargs)', globals(), locals(),
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time.strftime('/home/user/profiling/foo-%Y%m%d-%H%M%S.pstats'))
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def real_foo(self, bar):
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# function content
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### Run application
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Beware that some functions may be called often. For example `qubesmanager/main.py:update_table` gets run once per second. This will produce one pstat file per second.
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Remember to revert your changes to application afterwards.
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### Upload statistics
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If you are in dom0:
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~~~
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cd ~/profiling
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./Upload.sh
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~~~
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### Analyse
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~~~
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make
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~~~
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For every `${basename}.pstats` this will produce `${basename}.txt` and `${basename}.svg`. SVG contains call graph. Text file contains list of all functions sorted by cumulative execution time. You may also try `make all-png`.
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~~~
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make index.html
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~~~
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This creates `index.html` with all SVG graphics linked to TXT files. Ready for upload.
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~~~
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make REMOTE=example.com:public_html/qubes/profiling/ upload
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~~~
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Example
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-------
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This example is from `qubes-manager` (`qubesmanager/main.py`).
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It is apparent than problem is around `get_disk_usage` which calls something via `subprocess.call`. It does it 15 times, probably once per VM.
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