See inline.
Jiri Kuthan wrote:
At 09:24 AM 5/30/2005, Greger V. Teigre wrote:
[...]
* 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.
I have to admit I am not sufficiently familiarized with BDB. If I
understand it right, they do confgurable in-memory caching and they
also support some kind of master-slave replication. I am not sure
though how this scales...(20 SERs with 20 BDBs, one of them master
and replicating UsrLoc changes to 19 slaves who are all able to
identify inconsistent cache?)
I mean the structural problem here is dealing with r-w intensive
Usrloc operations and still desiring to replicate for reliability.
There is a variety of algorithms to deal with it and I don't know
well what the respective DB systems actually do.
I'm not proposing to use BDB, it was just an example. Databases are very
good at replication, even two-way replication can be done quite efficiently
through locking etc. I just took Paul's setup with cluster back-end as
granted and wrote my comments based on that...
Thinking a bit wider and building on your comments, Jiri:
The challenge, I think, is to handle the following things in any likely
deployment scenario:
1. Usrloc writes to cache vs. DB
2. Replication of usrloc, multiple DBs vs. cluster, across LAN or WAN
3. Memory caching management (inconsistencies etc)
For the sake of the readers, here is how I understand SER's operations
today:
1. Usrloc is always written to cache, DB write is controlled through
write-through parameter
2. Replication is handled by t_replicate
3. Management of cache is not needed, the cache is always updated. However,
an updated DB (and thus dirty cache) will not be detected
Here is how I understand Paul's proposal (and with my annotated suggestions
from my last email :-):
1. Usrloc is always written to DB, cache is updated if it is already in the
cache
2. Replication is handled by underlying database across DBs or in a cluster
3. If usrloc is not found, DB is checked. If cache is full, some mechanism
for throwing out a usrloc is devised
I must admit I often fall for the argument: "let each system do what it is
best at."
Following that, replication should only be done at an application level if
the underlying database is not capable of doing it (if we agree that a DB is
good at replication). The only thing I see a DB is not capable of, is
handling the NAT issues. So, if a given usrloc has to be represented by
different location (ex. the registration server), then the DB cannot do
replication. However, if the NAT issue is handled through some other means,
ex. Call-Id aware LVS with one public IP, then the usrloc should be the same
across DBs and the DB should handle the replication.
You don't need many subscribers before you'll want redundancy and as
active-passive redundancy is a waste of resources, I believe an upgrade of
the replication mechanism should soon be imminent. ;-)
I think I have said this before, but this is my enterprise-level "dream"
scenario:
1. Two geographically distributed server centers
2. DNS SRV for load distribution (and possible using segmentation of clients
through their configurations if they don't support DNS SRV)
3. Each data center has Call-Id sensitive LVS in front, with one or more
servers at the back (a fair-sized LVS box can handle 8,000 UDP packets per
second)
4. Each data center either has a DB cluster or two-ways SER-based
replication
5. The data centers replicate between each other using either DB-based
replication or two-ways SER-based replication
6. The SER-based replication is an enhanced version of t_replicate() were
replication is to a set of servers and replication is ACKed and guaranteed
(queue). I would suggest using the XMLRPC interface Jan has introduced
7. I think Paul's cache-suggestions are good regardless of decisions on
replication
Entry level scenario where the same box is running LVS, SER, and DB (you can
quickly add new boxes) has a very low cost.
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).
You may also purchase more memory :)
Do you suggest that no mechanism should be devised when the cache limit is
hit? ;-) Then maybe I can suggest an email alert to the operator when a
certain amount of the cache is full... :-D I trust my people to act fast
and appropriate, but not that fast and appropriate!
g-)