Structural Join and Staircase Join Algorithms of Sibling Relationship

The processing of XML queries can result in evaluation of various structural relationships. Efficient algorithms for evaluating ancestor-descendant and parent-child relationships have been proposed. Whereas the problems of evaluating preceding-sibling-following-sibling and preceding-following relationships are still open. In this paper, we studied the structural join and staircase join for sibling relationship. First, the idea of how to filter out and minimize unnecessary reads of elements using parent＇s structural information is introduced, which can be used to accelerate structural joins of parent-child and preceding-sibling-following-sibling relationships. Second, two efficient structural join algorithms of sibling relationship are proposed. These algorithms lead to optimal join performance： nodes that do not participate in the join can be judged beforehand and then skipped using B^＋-tree index. Besides, each element list joined is scanned sequentially once at most. Furthermore, output of join results is sorted in document order. We also discussed the staircase join algorithm for sibling axes. Studies show that, staircase join for sibling axes is close to the structural join for sibling axes and shares the same characteristic of high efficiency. Our experimental results not only demonstrate the effectiveness of our optimizing techniques for sibling axes, but also validate the efficiency of our algorithms. As far as we know, this is the first work addressing this problem specially.

An Effective Semantic Cache for Exploiting XPath Query/View Answerability

Maintaining a semantic cache of materialized XPath views inside or outside the database is a novel, feasible and efficient approach to facilitating XML query processing. However, most of the existing approaches incur the following disadvantages： 1） they cannot discover enough potential cached views sufficiently to effectively answer subsequent queries; or 2） they are inefficient for view selection due to the complexity of XPath expressions. In this paper, we propose SCEND, an effective Semantic Cache based on dEcompositioN and Divisibility, to exploit the XPath query/view answerability. The contributions of this paper include： 1） a novel technique of decomposing complex XPath queries into some much simpler ones, which can facilitate discovering more potential views to answer a new query than the existing methods and thus can adequately exploit the query/view answerability; 2） an efficient view-section method by checking the divisibility between two positive numbers assigned to queries and views; 3） a cache-replacement approach to further enhancing the query/view answerability; 4） an extensive experimental study which demonstrates that our approach achieves higher performance and outperforms the existing state-of-the-art alternative methods significantly.