Hey Sean, we haven't added support for the batch inserter in the python bindings yet, I can think of two things you can do:
a) Use the batch inserter in java land like you say to create your db, and then just set embedded python to use that db location. b) Just use the normal API, depending on how interconnected your data is, if you do transactions of say 100 000 inserts per TX, it shouldn't take that long to insert 70M nodes. Pure insert of 1 node with one property clocks in on my machine at about 30 000 inserts per second. It might be interesting to add support for the GEOFF ( http://py2neo.org/geoff/) import/export format that the cool kids behind py2neo has developed.. Add a ticket to the github page for neo4j-embedded if you'd like to see any of that happen :) /jake On Wed, Oct 5, 2011 at 4:03 PM, Sean Davis <sdav...@mail.nih.gov> wrote: > I have a few datasets that contain about 70M nodes. Relationships > between these sets will be sparse and will be added over time. What > is the fastest way to load these nodes into neo4j? I can work with > java (http://wiki.neo4j.org/content/Batch_Insert) if necessary, but > I'd be interested to hear if there is a way to use this API in the new > embedded python mode. > > Thanks, > Sean > _______________________________________________ > Neo4j mailing list > User@lists.neo4j.org > https://lists.neo4j.org/mailman/listinfo/user > -- Jacob Hansson Phone: +46 (0) 763503395 Twitter: @jakewins _______________________________________________ Neo4j mailing list User@lists.neo4j.org https://lists.neo4j.org/mailman/listinfo/user
