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
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 <[EMAIL PROTECTED]>wrote:
> 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?