Good morning Hannu,
Hannu Krosing wrote:
> People do that in cases where there is high write loads ("high" as in
> "not 10+ times less than reads") and just replicating the RO copies
> would be prohibitively expensive in either network, cpu or memory terms.
Okay. It that case it's even less like any type of replication.
IMO, Data Partitioning is the most simple method of Load Balancing. It's
like saying: hey, if your database server is overloaded, simply split
your data over multiple servers.
Which is not always possible and can lead to other problems. Some of
which can solved by replication solutions.
> In what way is pgpool multimaster ? last time I looked it did nothing
> but applying DML to several databses. i.e. it is not replication at all,
Please give your definition of replication.
Wikipedia gives us [1]: "Replication refers to the use of redundant
resources, such as software or hardware components, to improve
reliability, fault-tolerance, or performance."
Pgpool does that by Query Broadcasting, no?
> or at least it is masterless, unless we think of the pgpool process
> itself as the _single_ master :)
Hm. That's a good point. Pgpool allows to write to only one master (the
pgpool process) but read from multiple, synchronous masters. I admit
that makes it a little hard to split into Single- or Multi-Master.
Doesn't Sequoia support multiple Query Broadcasting processes? Would it
qualify as Multi-Master *Replication*, then?
In an ideal implementation, every Master could broadcast queries to all
other masters. Thus giving a *real* Multi-Master solution. Postgres-R
(6.4) did fall back into that mode for transactions which change a lot
of tuples, so that the writeset didn't exceed a certain size limit.
> I think this gives completely wrong picture of what pgpool does.
As I see it, that's because pgpool is a very limited implementation of
Query Broadcasting. But pgpool is not the only solution implementing
that algorithm. Do we want to describe the general algorithm or pgpool here?
Regards
Markus
[1]: Wikipedia about Replication (Computer Science):
http://en.wikipedia.org/wiki/Replication_%28computer_science%29