Unification in a parallel cluster is a difficult problem. Writing very large scale unification programs is an even harder problem.
What problem are you trying to solve? One option would be that you need to evaluate a conventionally-sized rulebase against many inputs. Map-reduce should be trivially capable of this. Another option would be that you want to evaluate a huge rulebase against a few inputs. It isn't clear that this would be useful given the problems of huge rulebases and the typically super-linear cost of resolution algorithms. Another option is that you want to evaluate many conventionally-sized rulebases against one or many inputs in order to implement a boosted rule engine. Map-reduce should be relatively trivial for this as well. What is it that you are trying to do? On Fri, Oct 19, 2012 at 12:25 PM, Luangsay Sourygna <luang...@gmail.com>wrote: > Hi, > > Does anyone know any (opensource) project that builds a rules engine > (based on RETE) on top Hadoop? > Searching a bit on the net, I have only seen a small reference to > Concord/IBM but there is barely any information available (and surely > it is not open source). > > Alpha and beta memories would be stored on HBase. Should be possible, no? > > Regards, > > Sourygna >
