Hi Nate,
I was wondering if I could take a look at the schema you used for your
database so I don't have to work backwards to figure out what to create,
as I am guessing the types of fields you used at this point.
Thanks in advance,
-Rick
nathan binkert wrote:
>> Is there any pointers out there about how to use the mysql + M5 integration?
>>
> Unfortunately, I'm pretty sure that there's nothing much. Basically,
> the output side is easy, you just have to call m5.stats.initMySQL()
> and then when stats are dumped, they get dumped to the mysql database.
> There are two other issues. Database setup is done with
> "util/stats/stats.py database init". The main issue is with
> extraction.
>
> Look at the stats.py script for example code. There are a few things
> that I support:
>
> First, once you've connected to the database, the code queries the
> database for all stat names and sucks them out of the database. You
> can then use the update_dict call to put all of the stats into a dict
> of your choice (you can even pass globals() or locals() as the dict).
>
> In that dict, you will get a whole bunch of proxy objects, for each
> stat. So if you have an object foo.bar and a stat called blah, you'd
> end up with foo.bar.blah in that dict. The proxies understand all of
> the fomula stuff, so you can say
> x = foo.bar.blah / foo.bar.baz and you'll get a new proxy object x
> that is a division of the two stats.
>
> You can call db.get("my.job.name", x) to query the database for the result.
>
> There are a few more sophisticated things you can do. If you dump
> stats more than once in a single run, you can use: db.sum(), db.avg(),
> db.stdev(). Those stats give you the sum, mean, and standard
> deviation of all of the dumps done in that single run.
>
> All in all, it's really pretty powerful, but it does take some getting
> used to. There are some outstanding changes that you'd probably find
> useful in our shared patch queue (see stats.diff). That patch also
> has lots of examples of how I integrated the database stuff with
> matplotlib.
>
> I have grand plans to go a lot further with this stuff. Essentially,
> I plan to create a database file (probably a python shelf, though
> maybe sqlite db) that contains all of the stat data and make all of
> this python code both able to query the mysql database and the
> database file. I will move all of the stats output code that is
> currently in C++ over to python (I've made stats accessible to the
> python side of M5). Then I can use the same basic query code to dump
> the text file from either the mysqldb, database file, or the python
> interface to stats. Finally, I will probably also move from MySQLdb
> to sqlalchemy.
>
>
> Ok, long e-mail. I hope you find this stuff useful. If you want to
> learn a thing or two about python, databases, swig, and the C/Python
> API, consider helping me out! This sounds like a whole lot of stuff,
> but in all honestly, a significant fraction of the code is written.
> It's mostly a matter of putting the pieces together and cleaning it
> all up.
>
> Nate
>
>
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