  Hadoop MapReduce is now a popular choice for performing large-scale data
analytics. This technical report describes a detailed set of mathematical
performance models for describing the execution of a MapReduce job on Hadoop.
The models describe dataflow and cost information at the fine granularity of
phases within the map and reduce tasks of a job execution. The models can be
used to estimate the performance of MapReduce jobs as well as to find the
optimal configuration settings to use when running the jobs.
