Hi, here my new answer, I got into this issue:
I have a large weighted graph with only one schema index on nodes (Topic): 4M topics and 100M rels. I wanted to find paths between two given nodes. I tried out with queries like this one: since it is a weighted graph, I compute the weighted path between nodes as the sum of its weight (I called weight 'proximity' here). Problem is, a query of this type, on such a large graph, tooks ages: Note that using an index, either directly the internal id, give same responsive results *Is there any way to speed up performance to reasonable production time?* (lower than 1s ... it means 3 orders of magnitude ... ) MATCH (n) , (m), p = (n)-[*0..2]-(m) where id(n) = 103105 and id(m) = 1386672 with p, n, m return p, reduce(totProximity = 0, n IN relationships(p)| totProximity + n.proximity) AS pathProximity order by pathProximity DESC; *~1M ms !!! * same as MATCH (n:Topic) , (m:Topic), p = (n)-[*0..2]-(m) where n.name = 'title-1' and id(m) = 'title-2' with p, n, m return p, reduce(totProximity = 0, n IN relationships(p)| totProximity + n.proximity) AS pathProximity order by pathProximity DESC; *~2M ms !!! * -- 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.
