Bitmap indexes for relational XML twig query processing

Kyong-Ha Lee, Bongki Moon
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引用次数: 3

Abstract

Due to an increasing volume of XML data, it is considered prudent to store XML data on an industry-strength database system instead of relying on a domain specific application or a file system. For shredded XML data stored in the relational tables, however, it may not be straightforward to apply existing algorithms for twig query processing, because most of the algorithms require XML data to be accessed in a form of streams of elements grouped by their tags and sorted in a particular order. In order to support XML query processing within the common framework of relational database systems, we first propose several bitmap indexes for supporting holistic twig joins on XML data stored in the relational tables. Since bitmap indexes are well supported in most of the commercial and open-source database systems, the proposed bitmap indexes and twig query processing algorithms can be incorporated into the relational query processing framework with more ease. The proposed query processing algorithms are efficient in terms of both time and space, since the compressed bitmap indexes stay compressed during query processing. In addition, we propose a hybrid index which computes twig query solutions with only bit-vectors, without accessing labeled XML elements stored in the relational tables.
用于关系XML枝查询处理的位图索引
由于XML数据量的增加,将XML数据存储在行业强度的数据库系统上而不是依赖于特定于领域的应用程序或文件系统是明智的做法。然而,对于存储在关系表中的分解XML数据,应用现有算法进行分支查询处理可能并不简单,因为大多数算法要求以元素流的形式访问XML数据,这些元素流按标记分组,并按特定顺序排序。为了在关系数据库系统的通用框架内支持XML查询处理,我们首先提出了几个位图索引,用于支持存储在关系表中的XML数据的整体分支连接。由于位图索引在大多数商业和开源数据库系统中都得到了很好的支持,因此所提出的位图索引和小枝查询处理算法可以更容易地合并到关系查询处理框架中。所提出的查询处理算法在时间和空间上都是有效的,因为在查询处理过程中压缩的位图索引保持压缩。此外,我们提出了一种混合索引,它只使用位向量计算分支查询解决方案,而不访问存储在关系表中的标记XML元素。
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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