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 different parallelization strategies for different XPath query patterns.
The concept of a trigger is centrrd to any active database. Upon the occurrence of a trigger even~the trigger is "fired", i.e, the trigger action is executed. We describe a model and a language for specifying basic and composite trigger events in the context of an object-oriented database. The specified events can be detected efficiently using finite automata. We integrate our model with O++, the database programming language for the Ode object database being developed at AT&T Bell Labs. We propose a new Event-Action model, which folds into the event specification the condition part of the well-known Event-Condition-Action model and avoids the multiple coupling modes between the event, condition, and action trigger components,
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