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MapReduce has shown vigorous vitality and penetrated both academia and industry in recent years. MapReduce not only can be used as an ETL tool, it can do even much more. The technique has been applied to SQL summation, OLAP, data mining, machine learning, information retrieval, multimedia data processing, science data processing etc. Basically MapReduce is(More)
MapReduce is a popular framework for large-scale data analysis. As data access is critical for MapReduce’s performance, some recent work has applied different storage models, such as column-store or PAX-store, to MapReduce platforms. However, the data access patterns of different queries are very different. No storage model is able to achieve the optimal(More)
Big data analysis is a main challenge we meet recently. Cloud computing is attracting more and more big data analysis applications, due to its well scalability and fault-tolerance. Some aggregation functions, like SUM, can be computed in parallel, because they satisfy distributive law of addition. Unfortunately, some of statistical functions are not(More)
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