[mod_python] IPC, db conn sharing, and other fine things

Mike Looijmans mike.looijmans at asml.com
Wed Aug 27 07:38:01 EST 2003

>- nsv buckets --- nsv == NaviServer (AOLServer's original name) shared
>variables... they were effectively arrays that stored information
>accessible and modifiable by any running thread... perfect for caching
>database information for faster generation of dynamic pages...

In mod_python, just use global variables in modules. Use dictionary objects
as fast storage mechanism.

>- database connection pooling --- provided easy, standardized, and
>scalable access to existing database connections

Same as above: Use global variables.

>... obviously I could write some sort of
>caching daemon in Python that used UNIX sockets and some simple
>key/value pair protocol to do db data caching... or I could write some
>sort of db-pooling daemon...

Why not integrate it into one of your modules?
Once loaded, the module remains in memory. So you can have it start a daemon
thread and use that as your IPC server. I always design the pages such that
no IPC is needed, each page gets its data exclusively from the request and
the database. The database is a great way to exchange data anyway, performs
excellent and survives even a power-down.

>So I suppose what I'm asking is that is there any way natively in
>mod_python to support these enterprise critical features? And if not,
>how the hell do you guys who use mod_python manage to have massive
>hit-per-second sites without data caching?

Python is so powerful a language, that creating these "enterprise critical
features" in raw code is just something you do on the side. I don't put
these in a library because there's more work in maintaining that library
than just entering the code. A threadsafe DB pooling system takes about 5
lines of Python code to program, and you need only one for the whole

I do a little caching for 'static' tables, something like:

cache = {}
    data = cache[key]
except KeyError:
    c = db.cursor()
    c.execute(somequery % key)
    data = c.fetchall()[0][0]
    cache[key] = data
return data

Also, I did some experiments with our  MySQL database, and found that the
overhead in a DB connection creation is very, very low when the DBMS is on
the same host. I was unable to measure any difference in performance,
compared to running an SQL statement, connecting to the socket just didn't
take any time. I implemented DB connection pooling anyway.

When tuning performance, I tend to optimize the design, SQL and index trees,
that helps performance a lot more than fiddling with fancy features.
Database pooling helped about 1%, changing a primary key from a,b to b,a
increased performance by 300%.


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