Abstract:The Map Reduce paradigm is now considered a standard platform that is used for large-scale data processing and management. A major operation that the Map Reduce platform relies on greatly is tasks scheduling. Although many schedulers have been presented, task scheduling is still one of the major problems that face Map Reduce frameworks. Schedulers need to maintain data locality to achieve an acceptable performance by avoiding several data transmissions. Hence, in this paper, we propose a new scheduling algorit… Show more
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