What is the easiest & most efficient way to count the number of nodes/edges in a large graph via Gremlin? The best I have found is using the V iterator:
gremlin> g.V.gather{it.size()}
However, this is not a viable option for large graphs, per the documentation for V:
The vertex iterator for the graph. Utilize this to iterate through all the vertices in the graph. Use with care on large graphs unless used in combination with a key index lookup.
I think the preferred way to do a count of all vertices would be:
gremlin> g = TinkerGraphFactory.createTinkerGraph()
==>tinkergraph[vertices:6 edges:6]
gremlin> g.V.count()
==>6
gremlin> g.E.count()
==>6
though, I think that on a very large graph g.V/E just breaks down no matter what you do. On a very large graph the best option for doing a count is to use a tool like Faunus(http://thinkaurelius.github.io/faunus/) so that you can leverage the power of Hadoop to do the counts in parallel.
UPDATE: The original answer above was for TinkerPop 2.x. For TinkerPop 3.x the answer is largely the same and implies use of Gremlin Spark or some provider specific tooling (like DSE GraphFrames for DataStax Graph) that is optimized to do those kinds of large scale traversals.