I can understand this use case. e.g. you have some 100 parameter financial instrument that can only be valued with monte-carlo methods. You could have 1 GB of

I can understand this use case. e.g. you have some 100 parameter financial instrument that can only be valued with monte-carlo methods. You could have 1 GB of data, but many core years of computation. In this case, is Hadoop actually a good tool? When you have such a small amount of data, it is unlikely you will ever be faced with a "reduce" challenge, and thus the problem is better solved with a simple queue rather than a hadoop cluster.