SQL-to-MapReduce Translation for Efficient OLAP Query Processing with MapReduce

Hyeon Gyu Kim
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引用次数: 2

Abstract

Substantial research has addressed that frequent I/O required for scalability and faulttolerance sacrifices efficiency of MapReduce. Regarding this, our previous work discussed a method to reduce I/O cost when processing OLAP queries with MapReduce. The method can be implemented simply by providing an SQL-to-MapReduce translator on top of the MapReduce framework and needs not modify the underlying framework. In this paper, we present techniques to translate SQL queries into corresponding MapReduce programs which support the method discussed in our previous work for I/O cost reduction.
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使用MapReduce进行高效OLAP查询处理的sql到MapReduce转换
大量的研究表明,可伸缩性和容错所需的频繁I/O会牺牲MapReduce的效率。关于这一点,我们之前的工作讨论了使用MapReduce处理OLAP查询时减少I/O成本的方法。该方法可以简单地通过在MapReduce框架之上提供SQL-to-MapReduce转换器来实现,而不需要修改底层框架。在本文中,我们介绍了将SQL查询转换为相应MapReduce程序的技术,这些程序支持我们之前的工作中讨论的降低I/O成本的方法。
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