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Parallelization of XPath queries using multi-core processors

机译:使用多核处理器对XPath查询进行并行化

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In this study, we present experiences of parallelizing XPath queries using the Xalan XPath engine on shared-address space multi-core systems. For our evaluation, we consider a scenario where an XPath processor uses multiple threads to concurrently navigate and execute individual XPath queries on a shared XML document. Given the constraints of the XML execution and data models, we propose three strategies for parallelizing individual XPath queries: Data partitioning, Query partitioning, and Hybrid (query and data) partitioning. We experimentally evaluated these strategies on an x86 Linux multi-core system using a set of XPath queries, invoked on a variety of XML documents using the Xalan XPath APIs. Experimental results demonstrate that the proposed parallelization strategies work very effectively in practice; for a majority of XPath queries under evaluation, the execution performance scaled linearly as the number of threads was increased. Results also revealed the pros and cons of the differentparallelization strategies for different XPath query patterns.
机译:在本研究中,我们介绍了在共享地址空间多核系统上使用Xalan XPath引擎并行化XPath查询的经验。为了进行评估,我们考虑一个场景,其中XPath处理器使用多个线程在共享XML文档上同时导航和执行单个XPath查询。考虑到XML执行和数据模型的约束,我们提出了三种用于并行化各个XPath查询的策略:数据分区,查询分区和混合(查询和数据)分区。我们使用一组XPath查询在x86 Linux多核系统上实验性地评估了这些策略,这些查询使用Xalan XPath API在各种XML文档上调用。实验结果表明,所提出的并行化策略在实践中非常有效。对于评估中的大多数XPath查询,执行性能随着线程数量的增加而线性增加。结果还揭示了针对不同XPath查询模式的不同并行化策略的优缺点。

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