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PyGraphistry – A library to extract, transform, and visually explore big graphs

github.com

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Re: PyGraphistry – A library to extract, transform, and visually explore big graphs

#2

Post by lmeyerov »

Fun to see a link here!

Always happy to describe what's happening underneath w/ connecting GPUs in the browser to GPUs in the datacenter. Likewise, the connection between event data & graph analytics is powerful as data scales, so happy to dig into that too.

Not shown there, we're piloting a 'visual playbook' investigation layer to help teams who investigate through a lot of event data. This has been especially relevant for security (SOC/IR/hunt) and anti-fraud as a team grows and needs to cover more ground. Playbooks let you finally record common multi-step multi-datasource workflows and get real visibility out of them. When your alerting flags something, running the playbook will gather & correlate that data for you, and unique to Graphistry, present it in a full visual (graph) analytics session. Think visually automating multi-step queries across Splunk + Spark + various APIs. And of course, for the advanced analysts, giant GPU-accelerated visualizations. We're actively piloting with interesting teams, so please ping info@graph....com if it may be your team's kind of thing.

Re: PyGraphistry – A library to extract, transform, and visually explore big graphs

#4

Post by lqdc13 »

lmeyerov wrote: post #2

Fun to see a link here! Always happy to describe what's happening underneath w/ connecting GPUs in the browser to GPUs in the datacenter. Likewise, the connection between event data & graph analytics is powerful as data scales, so happy to dig into that too. Not shown there, we're piloting a 'visual playbook' investigation layer to help teams who investigate through a lot of event data. This has been especially relev…

Is it possible to use a local GPU from the machine that has the data? Kind of like Gephi?

Re: PyGraphistry – A library to extract, transform, and visually explore big graphs

#5

Post by ThePhysicist »

lmeyerov wrote: post #2

Fun to see a link here! Always happy to describe what's happening underneath w/ connecting GPUs in the browser to GPUs in the datacenter. Likewise, the connection between event data & graph analytics is powerful as data scales, so happy to dig into that too. Not shown there, we're piloting a 'visual playbook' investigation layer to help teams who investigate through a lot of event data. This has been especially relev…

Is it possible to visualize graphs entirely on the client side (without sending any data to your backend)? We have some very large graphs that we'd like to explore, but unfortunately it's not possible to send the data to the cloud, hence a local solution would be great. I have investigated Gephi but unfortunately the performance is quite disappointing for very large graphs.

Re: PyGraphistry – A library to extract, transform, and visually explore big graphs

#8

Post by bearjaws »

m3nu wrote: post #7

Another plot.ly pushing their freemium product via Github? No pricing on the homepage yet. Will come later, after enough people integrated it in their projects.

Anyone looking for an opensource version of plot.ly, take a look at http://www.metabase.com/

Re: PyGraphistry – A library to extract, transform, and visually explore big graphs

#9

Post by MurrayHill1980 »

ThePhysicist wrote: post #5
lmeyerov wrote: post #2

Fun to see a link here! Always happy to describe what's happening underneath w/ connecting GPUs in the browser to GPUs in the datacenter. Likewise, the connection between event data & graph analytics is powerful as data scales, so happy to dig into that too. Not shown there, we're piloting a 'visual playbook' investigation layer to help teams who investigate through a lot of event data. This has been especially relev…

Is it possible to visualize graphs entirely on the client side (without sending any data to your backend)? We have some very large graphs that we'd like to explore, but unfortunately it's not possible to send the data to the cloud, hence a local solution would be great. I have investigated Gephi but unfortunately the performance is quite disappointing for very large graphs.

Graphistry is impressive, but not free, and needs their server and an API key. You probably already know about graphviz sfdp (not interactive). There's been interesting recent work on distributed maxent optimization https://arxiv.org/pdf/1506.04383.pdf and sparse stress models https://arxiv.org/abs/1608.08909 (see its references as well, for example, Khoury's MARS is still available at https://github.com/marckhoury/mars). This problem requires a ton of algorithm engineering, a lot of messy user interface engineering, and integration into an HPC environment is a big issue, so progress in open source has not been that rapid.
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