Regarding extended scalability over larger platforms than the ones considered in this paper, it should be highlighted that two authors of this paper have proposed a formal scalability analysis of MapReduce applications . In this analysis the authors prove that the most scalable MapReduce applications are reduceless applications, which is exactly the case of SparkBLAST. Indeed, Theorem 5.2 of  states that the increase of amount of computation necessary for a reduceless Scalable MapReduce Computation (SMC) application to maintain a given isoefficiency level is proportional to the number of processors (nodes). This is the most scalable configuration over all scenarios analyzed in . Simulation results that goes up to 10000 nodes corroborate the limits stated in this and other theorems of .