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摘要:A Map Reduce cloud is the key to the success of cloud computing nowadays by the capability of processing large datasets simultaneously on nodes in a cloud. However, a Map Reduce cloud may waste many CPU resources to frequently process similar intermediate data in its Reduce tasks because specific intermediate data is always moved to specific Slave nodes. A MapR educe cloud can utilize the proposed idea of supporting the cache mechanism for Reduce tasks to avoid unnecessary computation. In experiments, a Map Reduce cloud is proved to get great performance improvement from the help of the cache mechanism when running CPU-intensive applications. Accordingly, a Map Reduce cloud can be justified to have the extension of the cache mechanism proposed in this paper.
会议名称:

2016 IEEE International Conference on Big Data Analysis

会议时间:

2016-03-12

会议地点:

中国浙江杭州

  • 专辑:

    信息科技

  • 专题:

    计算机硬件技术

  • 分类号:

    TP3

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