On 2008-10-28 01:32, Carl Banks wrote:
> I was wondering if anyone had any advice on this.
>
> This is not to study graph theory; I'm using the graph to represent a
> problem domain. The graphs could be arbitrarily large, and could
> easily have millions of nodes, and most nodes have a substantial
> amount of data associated with them. Obviously I don't want a whole
> such graph in memory at once, so libraries the just deal with in-
> memory graphs are out.
>
> I know I could implement this with a relational DB, and I'd be fine
> with a library that was built on top of one. But I'm hoping for
> specialzed behavior useful for graphs.
>
> For example, suppose I have a set of nodes called A. It would be
> useful to know if any of these nodes are connected by paths that
> include no nodes in A. I could, of course, do that by reading from
> the database and following the paths, but I clearly don't want to do
> that. I would want instead to somehow cache the outside connectedness
> relationship between different nodes of A. But then what happens if
> something changes elsewhere. How is the cache for A notified, and can
> it be updated efficiently using graph theorems, rather than
> regenerated?
>
> It's very tricky; that's why I hope someone else has done it.
>
> I'm guessing no.
Aaron Watters is an expert on this and has implemented kjbuckets
for doing this in memory:
http://gadfly.sourceforge.net/kjbuckets.html
Gadfly uses the library to implement relational queries (and works
on disk):
http://gadfly.sourceforge.net/
The package is now maintained by Richard Jones.
You might be able to reuse some parts of Gadfly for your
purposes.
Also have a look at Pygr:
http://bioinfo.mbi.ucla.edu/pygr
which is a Python library to build a graph interface on top of
a relational database.
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