Monitor Process Resources Usage
===============================
Bench aims to be a handy tool with these functions:
- Monitor CPU time (user time, sys time, real time)
- Monitor memory usage (vms usage, rss usage)
- Output to TSV(tab-delimited files)
- Output benchmarking metrics
- Visualize benchmarking over time
Examples
========
- Example 1: simple command
.. raw:: html
<!-- -->
::
> monitor.py sleep 2
pid ppid cwd cmd utime stime rtime maxRss maxVms avgRss avgVms
99627 99626 /home/zhanxw/mycode/bench sleep 2 0.0 0.0 1.8569419384 835584 6066176 835584 6066176
- Example 2: complex shell commands with samping interval equaing 0.5
second
.. raw:: html
<!-- -->
::
> monitor.py sh -c 'sleep 2 & sleep 4 & seq 1000000 >/dev/null & wait'
pid ppid cwd cmd utime stime rtime maxRss maxVms avgRss avgVms
100673 100672 /home/zhanxw/mycode/bench sh -c sleep 2 & sleep 4 & seq 1000000 >/dev/null & wait 0.0 0.0 3.6947889328 897024 4558848 897024 4558848
100674 100673 /home/zhanxw/mycode/bench sleep 2 0.0 0.0 1.68072605133 684032 6066176 684032 6066176
100675 100673 /home/zhanxw/mycode/bench sleep 4 0.0 0.0 3.86425089836 700416 6066176 700416 6066176
- Example 3: generate benmarking metrics to external file
The small program, burnCpu, will keep CPU running for several seconds.
Its source code is under src/.
::
> monitor.py -t -o burnCpu ./burnCpu
[1440476547.641628, 104060, 104059, '/home/zhanxw/mycode/bench/src', ['./burnCpu'], pcputimes(user=0.0, system=0.0), pmem(rss=1425408, vms=12984320)]
[1440476547.79734, 104060, 104059, '/home/zhanxw/mycode/bench/src', ['./burnCpu'], pcputimes(user=0.15, system=0.0), pmem(rss=1425408, vms=12984320)]
[1440476547.960703, 104060, 104059, '/home/zhanxw/mycode/bench/src', ['./burnCpu'], pcputimes(user=0.32, system=0.0), pmem(rss=1425408, vms=12984320)]
[1440476548.127665, 104060, 104059, '/home/zhanxw/mycode/bench/src', ['./burnCpu'], pcputimes(user=0.48, system=0.0), pmem(rss=1425408, vms=12984320)]
...
Additional result are stored in *burnCpu.csv*, *burnCpu.trace.csv* in
the Comma-separated format (CSV).
*burnCpu.csv* content
::
pid,ppid,cwd,cmd,utime,stime,rtime,maxRss,maxVms,avgRss,avgVms
104060,104059,/home/zhanxw/mycode/bench/src,./burnCpu,5.88,0.0,5.87858390808,1425408,12984320,1425408,12984320
*burnCpu.trace.csv* content
::
pid,ppid,cwd,cmd,utime,stime,rtime,rss,vms
104060,104059,/home/zhanxw/mycode/bench/src,./burnCpu,0.0,0.0,0.0,1425408,12984320
104060,104059,/home/zhanxw/mycode/bench/src,./burnCpu,0.15,0.0,0.155711889267,1425408,12984320
104060,104059,/home/zhanxw/mycode/bench/src,./burnCpu,0.32,0.0,0.319074869156,1425408,12984320
104060,104059,/home/zhanxw/mycode/bench/src,./burnCpu,0.48,0.0,0.486037015915,1425408,12984320
104060,104059,/home/zhanxw/mycode/bench/src,./burnCpu,0.65,0.0,0.653388023376,1425408,12984320
...
By using the trace output file, *burnCpu.trace.csv*, you can draw
benchmarking graphs, such as:
|image| NOTE ====
Shell (/bin/sh) can be used to execute commands. You can use "sh -c
'command arg1 arg2 ... '".
bench requires `psutil <https://pypi.python.org/pypi/psutil>`__ to
collect basic benchmarking metrics. We used psutil version 3.1.1 in
development.
Contact
=======
Xiaowei Zhan
.. |image| image:: http://zhanxw.com/bench/burnCpu.mon.png
