Hi, I am interested in providing network metrics such as centrality, eigenvector centrality, degree, etc to graphs that I must assume will contain lots (millions+) of nodes. I am interested in any suggestions regarding the best way to approach this:
- Is it reasonable to add these metrics as properties of the nodes? My thought here is that this would work nicely when exporting the graph as GraphML. - Can these metrics be maintained in the database over time, or should they be calculated as needed? - Does the calculation of a metric for a single node require traversing the entire graph (or at least the sub-graph it is connected to)? Does it depend on the metric being calculated? - If the answer is, yes - it take a long time to update a set of metrics, what are the typical solutions? Do we go down a path like we do with data warehousing where the graph is loaded from the operational store periodically in batches, and then becomes stale over time? What might be some solutions for graphs that are constantly updated - or is the tradeoff simply that to have metrics your entire graph must be updated after any update for the metrics to be valid? (For example - can a node be time stamped or something, or is it the case that any change to the graph can change the metrics for every other node?) Thanks in advance. -Paul _______________________________________________ Neo4j mailing list User@lists.neo4j.org https://lists.neo4j.org/mailman/listinfo/user
