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Skipnet-Octree Based Indexing Technique for Cloud Database Management System

机译:基于Skipnet-Octree的云数据库管理系统索引技术

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This article describes how data indexing plays a very crucial role in query processing. Systems based on traditional indexes like B-tree, R-tree, Bitmap, inverted indexing techniques are not suitable for efficient query evaluation as these systems are based on simple key-value pair and used only for point queries. In cloud data repositories, point queries are not sufficient for query as a cloud consists of multidimensional data. For multidimensional query processing, many techniques have been developed. In this article, a dynamic double layer indexing structure with the help of a Skipnet overlay for global indexing and an Octree index technique for local indexing has been proposed. It has been concluded from the experiments that Skipnet-Octree performs better than the previous double-layer indexing technique for complex queries.
机译:本文介绍了数据索引如何在查询处理中发挥至关重要的作用。基于传统索引(如B树,R树,位图,反向索引技术)的系统不适合进行有效的查询评估,因为这些系统基于简单的键值对,并且仅用于点查询。在云数据存储库中,点查询不足以进行查询,因为云由多维数据组成。对于多维查询处理,已经开发了许多技术。在本文中,提出了一种借助Skipnet覆盖进行全局索引和使用Octree索引技术进行局部索引的动态双层索引结构。从实验得出的结论是,对于复杂查询,Skipnet-Octree的性能优于以前的双层索引技术。

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