I would like to extract graph projections from a graph so that I can build smaller graphs from large ones for specific use cases (in most of the cases I can think of these graph projections will have a smaller size than source graph). Consider the following simple example in my original graph (all nodes have different types aka labels):
A -> B -> C -> D
Since the path from A to D exists, in my new graph I would create the nodes A and D and the edge between them. These paths could be easily discovered with a traversal (or even with the subgraph step I think):
g.V().as('a').out('aTob').out('bToC').out('cToD').as('d').select('a', 'd');
The thing is that these kind of traversals where one does not start from a specific set of nodes (where an index would be used) are not very efficient since they require a full graph scan.
16:46:27 WARN com.thinkaurelius.titan.graphdb.transaction.StandardTitanTx - Query requires iterating over all vertices. For better performance, use indexes
What kind of actions can be done here so that graph projections can be accomplished in an efficient way?
