VanL wrote:
> I am working on a project that will require building and querying large
> graph objects (initially 8M nodes, 30-40M edges; eventually 40M nodes,
> 100M edges). NetworkX seems to be the most popular, but I am concerned
> that a dict representation for nodes would use too much memory -
On Aug 24, 5:37 pm, VanL wrote:
>
> Can anybody who has worked with large graphs before give a recommendation?
>
when using large graphs another limitation may come from the various
graph algorithm run times. Most likely you will need to squeeze out as
much as possible and a python implementation
You may try the Python bindings for the Boost Graph Library, the graph
you talk about may fit in 2GB of a 32 bit OS too (this is the first
link I have found, it's a lot of time I don't use those graph
bindings):
http://banyan.usc.edu/log/c_cpp/boost-graph-library-python-bindings
Bye,
bearophile
--
VanL schrieb:
I am working on a project that will require building and querying large
graph objects (initially 8M nodes, 30-40M edges; eventually 40M nodes,
100M edges). NetworkX seems to be the most popular, but I am concerned
that a dict representation for nodes would use too much memory -- m
I am working on a project that will require building and querying large
graph objects (initially 8M nodes, 30-40M edges; eventually 40M nodes,
100M edges). NetworkX seems to be the most popular, but I am concerned
that a dict representation for nodes would use too much memory -- my
initial test
