A k-nearest neighbor (k-NN) query, which retrieves nearest k points from a database is one of the fundamental query types in spatial databases. An all k-nearest neighbor query (AkNN query), a variation of a k-NN query, determines the k-nearest neighbors for each point in the dataset in a query process. In this paper, we propose a method for processing AkNN queries in Hadoop. We decompose the given space into cells and execute a query using the MapReduce framework in a distributed and parallel manner. Using the distribution statistics of the target data points, our method can process given queries efficiently. © 2012 Springer-Verlag.
CITATION STYLE
Yokoyama, T., Ishikawa, Y., & Suzuki, Y. (2012). Processing all k-nearest neighbor queries in Hadoop. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7418 LNCS, pp. 346–351). https://doi.org/10.1007/978-3-642-32281-5_34
Mendeley helps you to discover research relevant for your work.