The International Journal of Innovative Research in Computer and Communication Engineering
Map-Reduce is software framework that allows certain type of parallelizable or distributable problems involving bulky data sets to be solve using computing clusters. This paper presents a hybrid Map-Reduce framework that gathers computations resources from different clusters and runs Map-Reduce jobs across them. The mechanism is realized using DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering algorithms among Map-Reduce, parallel processing framework over clusters. However, the instant accomplishment of algorithms undergoes from efficiency problem for higher execution time as well as inadequate memory.