Parallel R-tree search algorithm on DSVM

Botao Wang, Hiroyuki Horinokuchi, K. Kaneko, A. Makinouchi
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引用次数: 24

Abstract

Though parallel database systems have been extensively studied, as far as we know, the parallel algorithms of R-tree proposed so far are limited to one workstation with multiprocessors or multi disks, where a parallel sorting algorithm or concurrent I/O is used to improve the performance. For the searching of R-trees, multiple search paths from the root to leaves are traversed sequentially. This sequential traverse can be transformed into multiple parallel traverses based on multiple search paths, where the query is divided into subqueries which can be executed concurrently. Aiming at parallel I/O and CPU operations, we introduce a parallel R-tree search algorithm running on distributed shared virtual memory (DSVM), especially on Shusseuo which is an ODBMS providing global persistent object management on persistent DSVM. The related problems are discussed and the evaluations are made based on Shusseuo. Experimental results show that optimal performance can be reached in dealing with large volumes of data.
基于DSVM的并行r树搜索算法
虽然并行数据库系统已经得到了广泛的研究,但据我们所知,目前提出的R-tree并行算法仅限于一个多处理器或多磁盘的工作站,其中使用并行排序算法或并发I/O来提高性能。对于r树的搜索,顺序遍历从根到叶的多条搜索路径。这种顺序遍历可以转换为基于多个搜索路径的多个并行遍历,其中查询被划分为可以并发执行的子查询。针对并行I/O和CPU操作,介绍了一种运行在分布式共享虚拟内存(DSVM)上的并行r树搜索算法,特别是在分布式共享虚拟内存(DSVM)上提供全局持久对象管理的ODBMS Shusseuo上。对相关问题进行了探讨,并以蜀黍为例进行了评价。实验结果表明,在处理大量数据时,可以达到最佳性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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