[Neo4j] Some questions about design when using neo4j

Marko Rodriguez okrammarko at gmail.com
Wed Sep 28 17:56:21 CEST 2011


If you want to play with JUNG over Neo4j, you can do it via TinkerPop.

Graph g = new Neo4jGraph("/tmp/neo4j");
GraphJung jung = new GraphJung(g);

That GraphJung object is a implementation of the JUNG Interfaces and can be processed by the JUNG algorithms package.




On Sep 28, 2011, at 1:06 AM, Peter Neubauer wrote:

> Gen,
> I guess there is nothing out of the box right now, but you could get
> inspiration from http://jung.sourceforge.net/doc/api/index.html,
> especially http://jung.sourceforge.net/doc/api/edu/uci/ics/jung/algorithms/flows/EdmondsKarpMaxFlow.html
> and implement one or just use it on a toy graph to test it out?
> Cheers,
> /peter neubauer
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> On Sat, Sep 3, 2011 at 12:33 AM, Benjamin Gustafsson
> <benjamingustafsson at gmail.com> wrote:
>> Just in case there are any graph experts out there that want to exercise
>> their brains. (Its quite a while since I studied algorithms and optimization
>> regarding graphs. :-)
>> I'm able to implement a algorithm described in pseudocode (if anyone knows a
>> good algorithm for my special case below).
>> I have the transportation problem and need to find a preferably small (not
>> necessarily smallest) set of nodes that transports a certain amount of
>> credit/commodity from source node S to sink node T. All edges have a
>> capacity stated as a attribute for the edge, this can be read while
>> traversing the graph. Transportation cost for commodity/credit in the graph
>> is zero. The only cost in this graph problem is computation time to *find a
>> set of paths delivering all the commodity*(in my case credit). The path
>> lengths chosen are not important.
>> (This is the standard ripplepay problem, but I didn't like the algorithms
>> used by the original ripplepay implementation. It does not scale up to
>> millions of users. It is not fast enough.)
>> http://en.wikipedia.org/wiki/Transportation_network_%28graph_theory%29
>> And I also need a quick way of analysing if it is possible to send all
>> commodity across the network. If the amount commodity to be sent is lower
>> than max flow. (lower than min cut). There will initially be clusters with
>> very few edges connecting the clusters. If the nodes are in different
>> clusters the min cut can be really easy/*quick* to find (if we do it the
>> right way).
>> http://en.wikipedia.org/wiki/Max-flow_min-cut_theorem
>> Any implementations for neo4j already available regarding my special case?
>> --
>> //Benjamin Gustafsson
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