I have to run the same R script in parallel (via batches) with different parameters. The R script builds and scores a H2O model. In this case should I, 

1. Set up an individual cluster for each batch run of the R script?

(OR)

2. Create a common cluster and set the scripts to use it?

I would prefer the latter solution, but I am not sure how to automate initialization and shutting down of the H2O cluster for so many batches. The first batch has to create the cluster (H2O.init() and the last batch has to shut it down)