30 May
2005
30 May
'05
4:35 p.m.
Greger,
We would let SER use the save() function which would update the local
machine's cache and eventually persist the record to MySQL. Once persisted
the other MySQL servers would then see the updated usrloc record, thus
letting other ser routers "see" then if needed.
The only real difference here is that t_replicate() would not ever be
called.
P
On 5/30/05, Greger V. Teigre <greger(a)teigre.com> wrote:
Actually, a minute delay would be a bad thing
because replicated
usrloc records, using t_replicate() would not make it in to peer SER
server caches when the server is starting up.
Yeah, I forgot about that
scheme...
Given this fact, and given the fact that most SER
modules do not hash
data upon server startup [like group.so, etc, etc] we are starting to
see little value in caching usrloc. Our MySQL server is hit 12 times
for an INVITE message and so complete caching of usrloc is of minimal
performace gain.
Anyhow, we're not in process of modifying SER so that:
* when ser starts up usrloc is "lazy-loaded"
* if a usrloc record is looked up in cache and is __NOT__ found, then
MySQL will be queried. If found in MySQL then the usrloc record will
be put in to cache for future lookups
By doing these two things we should not have a problem we excessively
large subscriber bases.
Thoughts?
Makes sense. This is how Berkeley DB and many other DBs work. In fact,
the best would be to build an abstraction cache layer around all the query
functions that have data in the DB. This way you would get the optimum
performance/scalability.
However, there is one more thing: You need to decide on an algorithm for
selecting a usrloc record to replace when the cache is full. Do you store
extra info in memory for each usrloc to make the right decision (ex. based
on the number of lookups).
Also, what to do when you are storing a new location with save: Do you put
it in the cache as well? Today this happens automatically. As you have
continous registrations, you will fill up the cache with registered clients
(and push out the ones having been called). What you really want is to keep
the user locations you need (those required by lookup) in the cache. So I
would suggest that in save(), you only write to the DB (and of course update
the record if its in the cache) and that lookup() is the function that will
control the activation and replacement of the records in the cache.
I think this approach to caching is of interest also to those who do not
have a mysql cluster, but do regular replication, for example to reduce
start-up time. I believe an implementation may get pretty involved (in terms
of important functions you need to touch). However, I cannot see that you
will need to touch the core.
g-)
Paul
On 5/29/05, Greger V. Teigre <greger(a)teigre.com> wrote:
Interesting discussion. I believe most large-scale deployments (there
aren't really that many...) divide the user base across several
servers. I
believe they use 20K users is a "good number" per server. So, one ser
having to load that many records, is only if you have a cluster with
no
server divide. Loading all the contacts into memory is impossible to
scale,
at one point it will take too long time and take too much memory.
So, a
better architecture *for such a deployment scenario* would be a cache
of
some size and then a lookup of records in DB if not present in cache.
Loading 330 records per second, you can load about 20,000 contacts in
a
minute, which probably is ok.
g-)
Zeus Ng wrote:
> See inline comment.
>
>> Thanks for the info. I did change that config.h define and
>> now it works well.
>
> Great to hear that the little change solve your problem.
>
>>
>> My newest problem is the ser start time. In my very
>> non-scientific test it took ser about 25 minutes before it
>> began serving requests because it was loading usrloc information.
>>
>> That was using 500000 records in the location table. The
>> MySQL server was running on the same box as SER, which is
>> also my workstation, so stuff like Firefox, X, etc, were in use.
>>
>> But this does bring up an interesting problem namely - how
>> can ser service SIP clients while loading large number of
>> usrloc records? I'm kind of thinking that this could be a big
>
> No, you can't. In fact, you will experience a temporary slow down
> when a hugh number of UA is un-registering because the table was
> locked during that period of time. I once use sipsak to register 5000
> users in 15s. When they all expired about the same time, SER hang for
> a while for locking the table to release the record from memory.
>
>
>> problem. When dealing with massive user bases there is no
>> such thing as a "quick restart".
>
> Well, that's the trade-off of memory base db. You need to balance the
> startup time verse runtime performance.
>
>>
>> We do have LVS fully "sip-aware" so we are doing true UDP
>> load balancing based on the Call-ID header, but this is still
>> a problem [potentially] with replication ucontact records
>> while the server is starting up.
>>
>> I wonder if it is possible to modify the behaviour of usrloc
>> so that it loads in the background while ser is processing
>> SIP messages. And when lookup("location") is executed, usrloc
>> searching the the ser cache and then MySQL if no hit is found
>> in cache -- or something like that.
>
> This triggers me to bring up the common question asked on this list
> before. Can SER use just MySQL for usrloc? A similar concept has been
> done on the speeddial module. It would help load distribution, faster
> startup time and better redundancy. Of course, slower lookup as
> tradeoff.
>
> I once consider replacing the build-in memory base DB with MySQL
> memory db. However, that idea was dropped due to time constrain and
> compatability (postgresql) issue.
>
>>
>> Can anyone on serusers give some tips as to how to get ser to
>> load usrloc entries optimized? I know the usual stuff like
>> faster MySQL disks, faster network connection, dedicated app
>> servers, etc, etc. But I'm looking for ser and/or MySQL
>> tweaking hacks.
>
> Good luck on your search.
>
>
>>
>> Regards,
>> Paul
>>
>>
>
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