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MapReduce is an effective programming model for large-scale data-intensive computing applications. Hadoop, an open-source implementation of MapReduce, has been widely used. The communication overhead from the big data sets’ transmission affects the performance of Hadoop greatly. In consideration of data locality, Hadoop schedules tasks to the nodes near the(More)
MapReduce is a programming model for data-intensive applications. The performance of MapReduce is greatly affected by the scheduling efficiency, which needs to consider both the parallelism of processing and overhead of data transmission. Lots of researches only focus on optimizing scheduling mechanisms or data storage strategies to reduce the overhead of(More)
Clustering coefficient is an important measure in social network analysis, community detection and many other applications. However, it is expensive to compute clustering coefficient for the real-world networks, because many networks, such as Facebook and Twitter, are usually large and evolving continuously. Aiming to improve the performance of clustering(More)
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