Hello,
On 11/12/11 1:28 PM, Javier Gallart wrote:
Thanks Daniel
yes, I thought about that too, I like redis a lot, and the redis
module addition to kamailio is excellent news. However in this context
it's not trivial to write a function that looks for the best match in
a redis tree structure as mt_match does...
ok, in the same idea of a remote caching system, we have memcache
connector module, but probably it is the same situation as with redis.
Back to initial topic, I am not a user of db_berkeley, but afaik, the
module loads the content in memory of kamailio, so if you use mtree,
then it is practically a duplicate of content. Besides, I guess
db_berkeley will have some internal structure overhead that will use a
bit more memory.
What I can think of at this moment for a solution will be
adding/removing prefixes from mtree using mi/rpc command, so in case of
change of records, instead of loading the database table, the updates
can be done from command line or so.
Another option might be using database directly. With mysql, a good
solution is to define database table in memory, then add/updates records
there as needed. From config file, use sqlops with sql_query, matching
using 'IN' operator, against matching number exapnded with s.prefixes
transformation:
http://www.kamailio.org/wiki/cookbooks/3.2.x/transformations#sprefixes_len
Also, afaik, if you want postgres, it has some sort of index plugin that
can be used to match on longest prefix.
Cheers,
Daniel
Regards
Javi
On Sat, Nov 12, 2011 at 9:28 AM, Daniel-Constantin Mierla
<mico...@gmail.com <mailto:mico...@gmail.com>> wrote:
Hello,
just mentioning ndb_redis module (in 3.2) - you may want to look
at, it is key based access memory system. Otherwise, I haven't
used personally berkeley db to comment on this particular subject.
Cheers,
Daniel
On 11/11/11 7:50 PM, Javier Gallart wrote:
Hi list
we've been happily using the mtree module for months now. Lately
the size of the tree has grown a lot. The mtree table needs to be
fully repopulated and reloaded several times a day, and we are
looking for a fastest mechanism (for populating the table, I
guess the reload time does not depend much on the db backend...).
Does anyone tried with Berkeley DB? Is this combination
mtree-berkeley actually feasible...?
Thanks
Javi
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