
Hi,
I am developing one windows application to display the graph using Node XL.. The graph is rendered in 40 seconds with the no of vertices of range (4,0005,000)...
I have a requirement where I will have vertices in the range of 120,000150,000 and the current grpah is unable to load..
Can anybody help me out to load large no. of graphs with above range.
Statistics
No of Vertices  Time(Seconds)
4300  40
12000  150
21000  480
40000  830
79000  Does Not load even after 1 hour
I have 4 GB RAM with 32 bit OS...Any help is appreciated



NodeXL isn't designed to work with graphs that large. It's best suited for graphs with a few thousand edges and vertices. People have used it with tens of thousands of edges and vertices, but that takes a lot of patience, a lot of computer horsepower,
or both.
This is from the release notes for the NodeXL Class Libraries:
"Important Note: NodeXL works well with graphs that have up to a few thousand vertices and edges. It might work satisfactorily with larger graphs if you have a fast computer and some patience, but if you have very large graphs, you might
want to look at SNAP, the Stanford Network Analysis Platform. SNAP can handle graphs with millions of vertices and edges."
 Tony


Coordinator
Dec 17, 2013 at 1:42 AM

I should extend on Tony's point that hardware resources play a big role in expanding the data volume capacity of NodeXL. For a graph of the size you want to analyze you might consider a 64 bit operating system and 8 or even 16GB of RAM.
 Marc



Since NodeXL is mainly for social networking data analysis, and social networking always deals with large data(vertices,edges)...So how is the NodeXL Deals with the scenario? Any other way/Suggestion is always welcome...
Thanks,
Suryansu


Dec 17, 2013 at 4:12 PM
Edited Dec 20, 2013 at 6:10 PM

Hello, Suryansu:
Social network data analysis does sometimes deal with smalltomedium size datasets, and that is the target that NodeXL is aimed at. We would like very much to have NodeXL handle hundreds of thousands of edges and vertices with aplomb, but that is an engineering
challenge and there are always tradeoffs involved in such things. We decided early on to devote our limited resources to providing ease of use in a familiar environment (Excel), and to leave the larger datasets to packages that are explicitly designed to handle
them. SNAP is one such package. From the
SNAP website:
"It is written in C++ and easily scales to massive networks with hundreds of millions of nodes, and billions of edges."
 Tony

