The issue being that relationships on disk are not ordered, so that, even when just accessing the few relationships of the one type you still have to scan all rels.
For supporting different approaches you either have to change the store-format to handle the storage and loading of relationships of supernodes differently. Or: - if you'd rather want to avoid supernodes you can have an Expander in your traversers that delays the traversals of supernodes (perhaps the other nodes give you already enough results for the domain to consume). (You could also limit/timebox that). - You can also have Expanders that use an B-Tree or Relationship index internally (for the "few"-rels). With autoindexing you could actually put a property on those few "rels" that makes them automatically indexed. And then in the Expander use relIndex.get(startNode,null,null) to get all of them for expansion. It can be useful to get something like this implemented once and then offered to all users either as part of the product or perhaps in a component like neo4j-collections ? (these are just ideas) Cheers Michael Am 30.06.2011 um 13:57 schrieb Craig Taverner: > This topics has come up before, and the domain level solutions are usually > very similar, like Norbert's category/proxy nodes (to group by > type/direction) and Niels' TimeLineIndex (BTree). I wonder whether we can > build a generic user-level solution that can also be wrapped to appear as an > internal database solution? > > For example, consider Niels's solution of the TimeLine index. In this case > we group all the nodes based on a consistent hash. Usually the timeline > would use a timestamp, but really any reasonably variable property can do, > even the node-id itself. Then we have a BTree between the dense nodes and > the root node (node with too many relationships). How about this crazy idea, > create an API that mimics the normal node.getRelationship*() API, but > internally traverses the entire tree? And also for creating the > relationships? So for most cod we just do the usual > node.createRelationshipTo(node,type,direction) and node.traverse(...), but > internally we actually traverse the b-tree. > > This would solve the performance bottleneck being observed while keeping the > 'illusion' of directly connected relationships. The solution would be > implemented mostly in the application space, so will not need any changes to > the core database. I see this as being of the same kind of solution as the > auto-indexing. We setup some initial configuration that results in certain > structures being created on demand. With auto-indexing we are talking about > mostly automatically adding lucene indexes. With this idea we are talking > about automatically replacing direct relationships with b-trees to resolve a > specific performance issue. > > And when the relationship density is very low, if the b-tree is > auto-balancing, it could just be a direct relationship anyway. > > On Wed, Jun 29, 2011 at 6:56 PM, Agelos Pikoulas > <agelos.pikou...@gmail.com>wrote: > >> My problem pattern is exactly the same as Niels's : >> >> A dense-node has millions of relations of a certain direction & type, >> and only a few (sparse) relations of a different direction and type. >> The traversing is usually following only those sparse relationships on >> those >> dense-nodes. >> >> Now, even when traversing on these sparse relations, neo4j becomes >> extremely >> slow >> on a certainly non linear Order (the big cs O). >> >> Some tests I run (email me if u want the code) reveal that even the number >> of those dense-nodes in the database greatly influences the results. >> >> I just reported to Michael the runs with the latest M05 snapshot, which are >> not very positive... >> I have suggested an (auto) indexing of relationship types / direction that >> is used by traversing frameworks, >> but I ain't no graphdb-engine expert :-( >> >> A' >> >> >> Message: 5 >>> Date: Wed, 29 Jun 2011 18:19:10 +0200 >>> From: Niels Hoogeveen <pd_aficion...@hotmail.com> >>> Subject: Re: [Neo4j] traversing densely populated nodes >>> To: <user@lists.neo4j.org> >>> Message-ID: <col110-w326b152552b8f7fbe1312d8b...@phx.gbl> >>> Content-Type: text/plain; charset="iso-8859-1" >>> >>> >>> Michael, >>> >>> >>> >>> The issue I am refering to does not pertain to traversing many relations >> at >>> once >>> >>> but the impact many relationship of one type have on relationships >>> >>> of another type on the same node. >>> >>> >>> >>> Example: >>> >>> >>> >>> A topic class has 2 million outgoing relationships of type "HAS_INSTANCE" >>> and >>> >>> has 3 outgoing relationships of type "SUB_CLASS_OF". >>> >>> >>> >>> Fetching the 3 relations of type "SUB_CLASS_OF" takes very long, >>> >>> I presume due to the presence of the 2 million other relationships. >>> >>> >>> >>> I have no need to ever fetch the "HAS_INSTANCE" relationships from >>> >>> the topic node. That relation is always traversed from the other >> direction. >>> >>> >>> >>> I do want to know the class of a topic instance, leading to he topic >> class, >>> >>> but have no real interest ever to traverse all topic instance from the >>> topic >>> >>> class (at least not directly.. i do want to know the most recent >> addition, >>> >>> and that's what I use the timeline index for). >>> >>> >>> >>> Niels >>> >>> >>>> From: michael.hun...@neotechnology.com >>>> Date: Wed, 29 Jun 2011 17:50:08 +0200 >>>> To: user@lists.neo4j.org >>>> Subject: Re: [Neo4j] traversing densely populated nodes >>>> >>>> I think this is the same problem that Angelos is facing, we are >> currently >>> evaluating options to improve the performance on those highly connected >>> supernodes. >>>> >>>> A traditional option is really to split them into group or even kind of >>> shard their relationships to a second layer. >>>> >>>> We're looking into storage improvement options as well as modifications >>> to retrieval of that many relationships at once. >>>> >>>> Cheers >>>> >>>> Michael >>> >> _______________________________________________ >> Neo4j mailing list >> User@lists.neo4j.org >> https://lists.neo4j.org/mailman/listinfo/user >> > _______________________________________________ > Neo4j mailing list > User@lists.neo4j.org > https://lists.neo4j.org/mailman/listinfo/user _______________________________________________ Neo4j mailing list User@lists.neo4j.org https://lists.neo4j.org/mailman/listinfo/user
