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[期刊]Exploiting Bloom Filters for Efficient Joins in MapReduce

[日期:2013-10-07] 来源:  作者: [字体: ]

Exploiting Bloom Filters for Efficient Joins in MapReduce

Taewhi Lee, Kisung Kim, and Hyoung-Joo Kim

MapReduce is a programming model that is extensively used for large-scale data analysis. However, it is inefficient to perform join operations us-ing MapReduce, because large intermediate results are produced, even in cases where only a small fraction of input data participate in the join. We alleviate this problem by exploiting Bloom filters within a single MapRe-duce job. We create Bloom filters for an input dataset, and filter out the redundant records in the other input dataset in the map phase.


Bloom Filters for Efficient Joins in MapReduce

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