bench

Monitor Process Resources Usage

| Bench aims to be a handy tool with these functions: | - Monitor CPU time (user time, system time, real time) | - Monitor memory usage (virtual memory usage, resident memory usage) | - Output to TSV(tab-delimited files) | - Output benchmark metrics | - Visualize performance metrics (memory consumptions) over time

Examples

We showed several examples below. Please note that all output are tabularized for demonstration purpose.

• Example 1: simple command.

| This will start the process sleep for 2 seconds. The tabular output below was from the actual command: monitor.py sleep 2 2>&1 |column -t -s $'\t'. | If you simply run monitor.py sleep 2, you will get tab-deliminated outputs in standard error (stderr).

::

    $> monitor.py sleep 2
    pid     ppid    utime  stime  rtime         rss     vms      maxRss  maxVms   avgRss    avgVms     cwd                                cmd
    133692  133675  0.0    0.0    1.9368159771  774144  6066176  774144  6066176  774144.0  6066176.0  /home/zhanxw/mycode/bench/scripts  sleep 2

• Example 2: complex shell commands with sampling interval equaling to 0.1 second

This example will use shell to start 3 processes: sleep 2, sleep 4 and seq 1000000. You can see bench can monitor all 4 processes all together.

::

    $> monitor.py sh -c 'sleep 2 & sleep 4 & seq 1000000 >/dev/null & wait'
    pid     ppid    utime  stime  rtime            rss     vms      maxRss  maxVms   avgRss    avgVms     cwd                                cmd
    135004  134985  0.0    0.0    3.9532430172     798720  4558848  798720  4558848  798720.0  4558848.0  /home/zhanxw/mycode/bench/scripts  sh -c sleep 2 & sleep 4 & seq 10000000 >/dev/null & wait
    135006  135004  0.0    0.0    3.95348381996    655360  6066176  655360  6066176  655360.0  6066176.0  /home/zhanxw/mycode/bench/scripts  sleep 4
    135005  135004  0.0    0.0    1.83160495758    774144  6066176  774144  6066176  774144.0  6066176.0  /home/zhanxw/mycode/bench/scripts  sleep 2
    135007  135004  0.05   0.0    0.0599648952484  720896  6090752  720896  6090752  720896.0  6090752.0  /home/zhanxw/mycode/bench/scripts  seq 10000000

• Example 3: generate performance metrics to external file

Here we used a small program, burnCpu. It will keep CPU running for several seconds. Its source code is under src/.

The option -t will enable outputting traces. That means at several time stops, performance metrics of each processes will be outputted to the standard error as well as a separate comma-separated file, $prefix.trace.csv.

The option -g will generate a graph which contains several sub-figures, including timings for each processes, memory consumption for each processes, and memory consumption over the processing running time.

The option -o will specify the output prefix. The default value will be bench, meaning, you will get bench.csv. You can overwrite this value by using -o option.

::

    $> monitor.py -t -g -o burnCpu ./burnCpu
    pid     ppid    utime  stime  rtime            rss      vms       cwd                                cmd
    135471  135454  0.04   0.0    0.0441780090332  1449984  12984320  /home/zhanxw/mycode/bench/scripts  ../src/burnCpu
    135471  135454  0.2    0.0    0.205282926559   1449984  12984320  /home/zhanxw/mycode/bench/scripts  ../src/burnCpu
    135471  135454  0.38   0.0    0.381079912186   1449984  12984320  /home/zhanxw/mycode/bench/scripts  ../src/burnCpu
    ...

Additional result are stored in burnCpu.csv, burnCpu.trace.csv in the Comma-separated format (CSV).

burnCpu.csv file content

::

pid,ppid,utime,stime,rtime,rss,vms,maxRss,maxVms,avgRss,avgVms,cwd,cmd
144433,144416,5.4,0.0,5.40555810928,1404928,12984320,1404928,12984320,1404928.0,12984320.0,/home/zhanxw/mycode/bench/scripts,../src/burnCpu

burnCpu.trace.csv file content

::

pid,ppid,utime,stime,rtime,rss,vms,cwd,cmd
144433,144416,0.03,0.0,0.0423669815063,1404928,12984320,/home/zhanxw/mycode/bench/scripts,../src/burnCpu
144433,144416,0.19,0.0,0.20046210289,1404928,12984320,/home/zhanxw/mycode/bench/scripts,../src/burnCpu
144433,144416,0.36,0.0,0.373480081558,1404928,12984320,/home/zhanxw/mycode/bench/scripts,../src/burnCpu
...

When -g optioned is specified, bench will generate several performance metrics in the file burnCpu.trace.csv:

|image|

Notes

| To benchmark a complex command or combinations of commands, you can use shell (sh or bash) . For example, you can use "sh -c 'command arg1 arg2 ... '" (see Example 2). | Bench requires psutil <https://pypi.python.org/pypi/psutil>__ to collect basic performance metrics, and | requires numpy <http://www.numpy.org/>__ and pandas <http://pandas.pydata.org/>__ for statistical calculations. | In this release, we used psutil 3.1.1, numpy 1.8.2, pandas 0.16.2 and matplotlib 1.4.3.

Contact

| For questions or commend, please visit bench github repo: | repo <https://github.com/zhanxw/bench>__

| or email to: | Xiaowei Zhan

.. |image| image:: http://zhanxw.com/bench/burnCpu.png