Michael, sorry to answer so late. After following your instructions I got that performance was acceptable.
Thank you very much for your help. Regards, Alberto. On Monday, March 30, 2015 at 8:13:36 AM UTC+2, Michael Hunger wrote: > > That's what I said. > > Use an effective cache (i.e. one of the primitive collection libraries > with a map from long -> long) > > Most memory efficient and performant way: > > Alternatively, what you do is to do a dual-pass. > > Create an Array of the expected sizes, add the key entries to the array. > Sort the array > The keys are entries of the array and the array-index is the node-id. > you can scan the array for duplicates and null them out. > And then you can use Arrays.binarySearch() to find your entries. > > This is quite efficient and similar to what Neo4j uses internally for > neo4j-import. > > Michael > > Am 29.03.2015 um 18:50 schrieb Alberto Jesús Rubio Sánchez < > [email protected] <javascript:>>: > > Hi Michael, > > I've been testing and my problem is that the file is very large and the > memory becomes full. > > For this reason I thought to use a cache to store the ids. If a node id > isn't in the cache, the node is inserted even if the node is in the > database. Finally look for duplicate nodes remaining to merge them. > > I think it may be a good solution. What do you think? > > Thanks, > Alberto. > > -- > 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] <javascript:>. > For more options, visit https://groups.google.com/d/optout. > > > -- 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.
