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arXiv 1104.2079cs.DB
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使用基于类型的文档投影优化XML查询

Optimizing XML querying using type-based document projection

Véronique Benzaken, Giuseppe Castagna, Dario Colazzo, Kim Nguyen

摘要:

XML数据投影(或修剪)是主存查询引擎的自然优化:给定文档D上的查询Q,D的不需要评估Q的子树被修剪,从而产生更小的文档D ';然后在D'上执行查询Q,从而避免分配和处理Q永远不会到达的节点。在本文中,我们提出了一种基于类型的新方法,它大大改进了当前的解决方案。除了提供可比或更高的精度和更少的修剪开销,我们的解决方案-不像目前的方法-考虑到后向轴,谓词,可以应用于多个查询,而不仅仅是单个查询。边贡献是一种新型的可编程处理后向轴的系统。我们的方法的合理性被正式证明。此外,我们证明该方法也是完备的(即,产生最好的类型驱动修剪)。我们进一步验证我们的方法,使用XMark和XPathMark基准测试,并表明修剪不仅提高了主内存查询引擎的性能(如预期的那样),但也是最先进的原生XML数据库的状态。

英文摘要:

XML data projection (or pruning) is a natural optimization for main memory query engines: given a query Q over a document D, the subtrees of D that are not necessary to evaluate Q are pruned, thus producing a smaller document D'; the query Q is then executed on D', hence avoiding to allocate and process nodes that will never be reached by Q. In this article, we propose a new approach, based on types, that greatly improves current solutions. Besides providing comparable or greater precision and far lesser pruning overhead, our solution ---unlike current approaches--- takes into account backward axes, predicates, and can be applied to multiple queries rather than just to single ones. A side contribution is a new type system for XPath able to handle backward axes. The soundness of our approach is formally proved. Furthermore, we prove that the approach is also complete (i.e., yields the best possible type-driven pruning) for a relevant class of queries and Schemas. We further validate our approach using the XMark and XPathMark benchmarks and show that pruning not only improves the main memory query engine's performances (as expected) but also those of state of the art native XML databases.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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