I need some modelling advice. We want to store and analyse movement patterns. Think of trucks moving through a logistic's networks. We want to ask which truck has ever moved from location A to location B and what was the sequence of intermediate stops they made to get there.
In a later stage we also want to be able to ask this question if there is no truck that has stopped at location A and B. Which trucks and which sequence of stops would we have needed to get from A to B. Right now we modeled all locations as nodes and every trip a truck has ever made as a separate edge. The edges are attributed with a truck ID and a sequence number. We wrote our custom expander class to be used with the traversal framework and to take care of the sequence numbers and truck IDs to only get complete sequences for individual trucks. However, this performs very badly. Right now we have 300 locations/nodes and 300.000 trips/edges. Some stops have 20.000 outgoing trips that we are checking for truck ID and sequence number (for every outgoing relationship, get attributes and check) . This performs too badly. 13 seconds for 900 sequences. Finally, we want to try to scale it to 3000 locations and 20.000.000 trips. Do you have any alternative modelling ideas? Thanks a lot already. ps: I was thinking of storing every trucks list as a long linear sequence of stops/nodes. The nodes are additionally linked to some identifier Node through a type of is relation: "stop x is location A". -- You received this message because you are subscribed to the Google Groups "Neo4j" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
