For frequent disk I/O and big data transmissions among different racks and physical nodes, the intermediate data communication has become the biggest performance bottle-neck in most running Hadoop systems. This paper proposes a reduce placement algorithm called CORP to schedule related map and reduce tasks on the near nodes or clusters or racks for the data locality. Since the number of keys cannot be counted until the input data are processed by map tasks, this paper firstly provides a sampling algorithm based on reservoir sampling to achieve the distribution of the keys in intermediate data....
