The mongodb document says that
To compact this space, run db.repairDatabase() from the mongo shell (note this operation will block and is slow).
in http://www.mongodb.org/display/DOCS/Excessive+Disk+Space
I wonder how to make the mongodb free deleted disk space automatically ?
p.s. We stored many downloading task in mongodb, up to 20GB, and finished these in half an hour.
In general if you don’t need to shrink your datafiles you shouldn’t shrink them at all. This is because “growing” your datafiles on disk is a fairly expensive operation and the more space that MongoDB can allocate in datafiles the less fragmentation you will have.
So, you should try to provide as much disk-space as possible for the database.
However if you must shrink the database you should keep two things in mind.
MongoDB grows it’s data files by
doubling so the datafiles may be
64MB, then 128MB, etc up to 2GB (at
which point it stops doubling to
keep files until 2GB.)
As with most any database … to
do operations like shrinking you’ll
need to schedule a separate job to
do so, there is no “autoshrink” in
MongoDB. In fact of the major noSQL databases
(hate that name) only Riak
will autoshrink. So, you’ll need to
create a job using your OS’s
scheduler to run a shrink. You could use an bash script, or have a job run a php script, etc.
Serverside Javascript
You can use server side Javascript to do the shrink and run that JS via mongo’s shell on a regular bases via a job (like cron or the windows scheduling service) …
Assuming a collection called foo you would save the javascript below into a file called bar.js and run …
The javascript file would look something like …
This will run and return something like …
Run this on a schedule (during none peak hours) and you are good to go.
Capped Collections
However there is one other option, capped collections.
Basically you can limit the size of (or number of documents in ) a collection to say .. 20GB and once that limit is reached MongoDB will start to throw out the oldest records and replace them with newer entries as they come in.
This is a great way to keep a large amount of data, discarding the older data as time goes by and keeping the same amount of disk-space used.