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Does anyone have any favorite tools for visualizing very large graphs? I'm thinking 200k nodes and 2 million edges? Graphviz segfaults graphs a fraction of the

Does anyone have any favorite tools for visualizing very large graphs? I'm thinking 200k nodes and 2 million edges? Graphviz segfaults graphs a fraction of the size and even at that scale a node by node representation isn't super helpful without being able to zoom out and look for patterns.

hit8run 9y ago
Out of curiosity: is IBM Rational Rose doing the job? Haven't used it for years.
deleted 9y ago
[deleted]
bitexploder 9y ago
Gephi might work.
dredmorbius 9y ago
I've occasionally looked into larger projects, though not that large. There are some tools in R and python that seem to turn up. I'm sorry I don't have anything more specific than that to suggest, though it might be a fruitful direction.
jamessb 9y ago
What layout algorithm are you using for graphviz? sfdp is less computationally intensive than dot/neato/circo, and I would have thought it would be able to cope (assuming you have enough RAM/swap) - this gallery [1] uses graphviz to visualize networks from the University of Florida Sparse Matrix collection, the largest of which "have tens of millions of nodes and over a billion of edges". Gephi and Cytoscape are the main free graphical applications for analyzing networks; they might work for you. Tulip [2] might also be worth a try. [1]: https://web.archive.org/web/20111102185002/http://www2.research.att.com:80/~yifanhu/GALLERY/GRAPHS/indexAll.html https://web.archive.org/web/20111102185002/http://www2.resea... [2]: http://tulip.labri.fr/TulipDrupal/ http://tulip.labri.fr/TulipDrupal/
lmeyerov 9y ago
We made http://github.com/graphistry/pygraphistry http://github.com/graphistry/pygraphistry for that sort of thing, feel free to ping for an API key! The idea is by connecting GPUs in your browser to GPUs in the cloud, we can do bigger and bigger datasets over time. We're currently 1M nodes & edges in interactive-time (so no leaving your computer for 1hr+ or crashing), and actively working on the V2 engine to get us to 100X more. And yep, generally we don't want to stay long in large views, so we see it more about being scalable / smart / usable enough to let you go in-and-out.

hit8run 9y ago

Out of curiosity: is IBM Rational Rose doing the job? Haven't used it for years.

deleted 9y ago

[deleted]

bitexploder 9y ago

Gephi might work.

dredmorbius 9y ago

I've occasionally looked into larger projects, though not that large. There are some tools in R and python that seem to turn up. I'm sorry I don't have anything more specific than that to suggest, though it might be a fruitful direction.

jamessb 9y ago

What layout algorithm are you using for graphviz? sfdp is less computationally intensive than dot/neato/circo, and I would have thought it would be able to cope (assuming you have enough RAM/swap) - this gallery [1] uses graphviz to visualize networks from the University of Florida Sparse Matrix collection, the largest of which "have tens of millions of nodes and over a billion of edges". Gephi and Cytoscape are the main free graphical applications for analyzing networks; they might work for you. Tulip [2] might also be worth a try. [1]: https://web.archive.org/web/20111102185002/http://www2.research.att.com:80/~yifanhu/GALLERY/GRAPHS/indexAll.html https://web.archive.org/web/20111102185002/http://www2.resea... [2]: http://tulip.labri.fr/TulipDrupal/ http://tulip.labri.fr/TulipDrupal/

lmeyerov 9y ago

We made http://github.com/graphistry/pygraphistry http://github.com/graphistry/pygraphistry for that sort of thing, feel free to ping for an API key! The idea is by connecting GPUs in your browser to GPUs in the cloud, we can do bigger and bigger datasets over time. We're currently 1M nodes & edges in interactive-time (so no leaving your computer for 1hr+ or crashing), and actively working on the V2 engine to get us to 100X more. And yep, generally we don't want to stay long in large views, so we see it more about being scalable / smart / usable enough to let you go in-and-out.