Well, what Jeff wrote is also true.
I do hot-copy of databases because we have a set of products that have
full automated builds and, to increase performance, I made the build
generate the SQLite database on memory and then dump it to the filesystem.
Cheers,
Richard.
Hi,
I'm currently running several python applications (each app using
sqlalchemy) accessing (read/write) a single SQLite database stored on
disk.
For performance reasons, I would like to store this db file in RAM
memory (ie, in my /dev/shm)
The applications would then access a shared in-memory db through
SQLAlchemy and a backup application would periodically make a hot copy
of the in-memory db to disk. Then, on a [power off, power on]
sequence, this backup app would copy the backed up db file from disk
to RAM before launching the other apps.
Before starting, I would like to know if you think it is feaseable. My
questions are:
1- Has SQLALchemy an API to do a hot copy? (based on
http://sqlite.org/backup.htmlfor this particular db type)
2- If so, is this an actual hot copy, ie: the other apps will still
run without waiting for the backup app to finish he backup?
3- Is there a particular configuration in SQLAlchemy that enables
sharing an in-momory db from different apps (python processes)?
Thanks a lot for your feedback,
Pierre
--
Pierre,
While I do think this is feasible, I would discourage going down this
path unless you have a really good reason. It sounds like you need a
real database engine like postgres here. It basically does everything
you describe out of the box, is easy to set up, and will likely be
more reliable than anything you could come up with on your own. It
will also perform better when dealing with many simultaneous
transactions.
If you still run into performance problems you could look into
introducing a caching layer such as memcached, but I wouldn't cross
that bridge until I had thoroughly tweaked my db settings and
identified real bottlenecks in my application(s).
Jeff Peck
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