Research of kNN algorithm based on MapReduce and double levels of inverted grid index

• Published in: Zhejiang da xue xue bao. Journal of Zhejiang University. Sciences edition. Li xue ban Vol. 41; no. 6; pp. 703 - 708
• Main Authors: Zhao, Minchao, Du, Zhenhong, Zhang, Feng, Liu, Renyi, Li, Rongya
• Format: Journal Article
• Language: Chinese
• Published: Zhejiang University Press 01.11.2014
• Subjects: Algorithms; Blocking; circulartrip; Computational efficiency; Computing time; Indexing; Internet; k最邻近结点算法; mapreduce; Mathematical analysis; Query processing; 云计算; 双层倒排网格索引
• ISSN: 1008-9497
• DOI: 10.3785/j.issn.1008-9497.2014.06.016

With the development of satellite positioning and mobile internet technology, the geospatial data become more multi-source and heterogeneous, which consequently makes the obtainment of the interesting points around a target remarkably important. Considering that the key to the efficiency of the kNN algorithm lies in the design of data index and the storage structure of data block, we propose a MapReduce-oriented double inverted grid index for geospatial data. The target's neighbor query calculation is implemented based on the CircularTrip algorithm, and finally the nearest point sets are achieved according to the requirements. The results of the following experiments show that the indexing method not only provides a significant improvement in kNN query efficiency, but also has a good performance under a great amount of data, which consequently fits large-scale parallel computing better.