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ICDE
2012
IEEE

Fuzzy Joins Using MapReduce

11 years 6 months ago
Fuzzy Joins Using MapReduce
—Fuzzy/similarity joins have been widely studied in the research community and extensively used in real-world applications. This paper proposes and evaluates several algorithms for finding all pairs of elements from an input set that meet a similarity threshold. The computation model is a single MapReduce job. Because we allow only one MapReduce round, the Reduce function must be designed so a given output pair is produced by only one task; for many algorithms, satisfying this condition is one of the biggest challenges. We break the cost of an algorithm into three components: the execution cost of the mappers, the execution cost of the reducers, and the communication cost from the mappers to reducers. The algorithms are presented first in terms of Hamming distance, but extensions to edit distance and Jaccard distance are shown as well. We find that there are many different approaches to the similarity-join problem using MapReduce, and none dominates the others when both communicat...
Foto N. Afrati, Anish Das Sarma, David Menestrina,
Added 28 Sep 2012
Updated 28 Sep 2012
Type Journal
Year 2012
Where ICDE
Authors Foto N. Afrati, Anish Das Sarma, David Menestrina, Aditya G. Parameswaran, Jeffrey D. Ullman
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