一种基于多核机群架构的混合索引结构

摘要

We present a hybrid-index structure for high-dimensional data which named HKD-tree(Hybrid K-Dimensional Tree)．To make use of two-level parallelization 0f multi-core clusters we combined with KD-tree and LSH，which uses LSH in the leaf nodes of KD-tree．Compared with the traditional index structure the hybrid index structure has effective parallel processing ability and good scalability which is suitable for the multi-core cluster platform and high-dimensional data indexing.The experiment resuits show that the performance of the hybrid index structure is superior to the traditional index structure on the multi-cure cluster systems．%本文提出了一种HKD-tree(Hybrid K-Dimensional tree)混合索引结构.该结构将KD-tree(K-Dimensional tree)和LSH(Locality Sensitive Hashing)两种索引结构进行组合,利用KD-tree作为上层结构的主干而LSH充当叶子节点,从而可以利用多核机群系统的层次并行结构特性.与传统的索引结构相比,该混合索引结构具有高效并行处理、可扩展性好等特点,适于多核机群系统平台及高维数据索引.实验结果表明,该混合索引结构在多核机群系统上的性能优于传统的索引结构.