Hi Marc - yes, it takes minutes to do queries on nodes with lots of edges.  Like:

:> g.V().has("somevar","someVal").outE().has("indexedField","value")

I believe this is because of the large partition size.  I would love to use vertex cutting; but there seems to be a problem with it:

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Every-time, I built a small graph and exported to graphML for viewing in Gephi I would have node IDs that only existed in the edges list.
I printed the nodeID in my code everywhere it was used, and I would never see it in the output, but the graphML had it in the edges list and those 'zombie nodes' did exist in the graph as confirmed by gremlin queries. This was happening because I was using:
VertexLabel sourceLabel = mgmt.makeVertexLabel("source").partition().make(); Once I removed partition, the "zombie" node IDs disappeared.  I wanted to use partition for that since those particular vertexes can have a lot of edges; potentially billions. 

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Is there a bug with vertex cutting?  Thank you!

-Joe

Hi Joe,

You do not describe whether breaking this rule of thumb causes real performance issues in your case. Anyway, JanusGraph allows you to partition the stored edges of a node, see:
https://docs.janusgraph.org/advanced-topics/partitioning/#vertex-cut

Marc

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