ComMapReduce: An Improvement of MapReduce with Lightweight Communication Mechanisms

ScaDiPaSi: An Effective Scalable and Distributable MapReduce-Based Method to Find Patient Similarity on Huge Healthcare Networks

“…According to [27], a decomposable algorithm, partitionable data, and sufficient small data partition are the main characteristics required for effective use of MapReduce. In [23], classic MapReduce was optimized to decrease the data transformation load. In the method described in [23], a shared area for information was considered.…”

“…In [23], classic MapReduce was optimized to decrease the data transformation load. In the method described in [23], a shared area for information was considered. This type of design is suitable for solving problems, such as k-nn and top k queries.…”

Parallel Dynamic Skyline Query Using MapReduce

“…[4] has proposed parallel algorithms which can compute the skylines and reverse skylines using MapReduce. The dynamic skyline operator was not addressed in [4,5].…”

“…The authors have studied skyline query in the MapReduce platform [3,4,5]. Skyline computation was primarily adapted to the MapReduce Framework by Zhang bo liang et al [3], elaborated on in later works [4,5]. [4] has proposed parallel algorithms which can compute the skylines and reverse skylines using MapReduce.…”

“…As a parallel programming framework, MapReduce [17] is utilized to process big data on large clusters of commodity machines. The authors have studied skyline query in the MapReduce platform [3,4,5]. Skyline computation was primarily adapted to the MapReduce Framework by Zhang bo liang et al [3], elaborated on in later works [4,5].…”