We explain how the popular, highly abstract MapReduce model of parallel computation (MRC) can be rooted in reality by explaining how it can be simulated on realistic distributed-memory parallel machine models like BSP. We first refine the model (MRC$^+$) to include parameters for total work $w$, bottleneck work $\hat{w}$, data volume $m$, and maximum object sizes $\hat{m}$. We then show matching upper and lower bounds for executing a MapReduce calculation on the distributed-memory machine -- $Θ(w/p+\hat{w}+\log p)$ work and $Θ(m/p+\hat{m}+\log p)$ bottleneck communication volume using $p$ processors.