1. A method, executed by one or more processors, for providing an entirely hosted MapReduce data analytic infrastructure for executing a distributed large-scale compute job, the method comprising: providing complete portability with respect to a programmer's local machine, operating system, and browser; continuously metering consumed compute, storage, and network resources on a hosting system; continuously reporting cost metering to a user; for each compute instance of the distributed large-scale compute job, monitoring input data and output data for the compute instance, and logging the input data and output data for the compute instance; generating input data from a kernel program, wherein the kernel program is smaller than the generated input data; and data-sorting at least a portion of the output data of the distributed large-scale compute job during a Map phase, wherein the data-sorting comprises, indexed writing of data sorting keys to shared storage by independently-executed Map jobs, wherein the hosted infrastructure does not require an installed client software or software development kit and wherein the hosted infrastructure does not require the compilation of computer code.