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Erschienen in:
2015 | OriginalPaper | Buchkapitel
Efficient Processing of Multi-way Joins Using MapReduce
verfasst von : Linlin Ding, Siping Liu, Yu Liu, Aili Liu, Baoyan Song
Erschienen in: Intelligent Computation in Big Data Era
Verlag: Springer Berlin Heidelberg
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Multi-way join is critical for many big data applications such as data mining and knowledge discovery. Even though lots of research have been devoted to processing multi-way joins using MapReduce, there are still several problems in general to be further improved, such as transferring numerous unpromising intermediate data and lacking of better coordination mechanisms. This work proposes an efficient multi-way joins processing model using MapReduce, named Sharing-Coordination-MapReduce (SC-MapReduce), which has the functions of sharing and coordination. Our SC-MapReduce model can filter the unpromising intermediate data largely by using the sharing mechanism and optimize the multiple tasks coordination of multi-way joins. Extensive experiments show that the proposed model is efficient, robust and scalable.