On-demand index for efficient structural joins

Abstract

A structural join finds all occurrences of structural, or containment, relationship between two sets of XML node elements: ancestor and descendant. Prior approaches to structural joins mostly focus on maintaining offline indexes on disks or requiring the elements in both sets to be sorted. However, either one can be expensive. More important, not all node elements are beforehand indexed or sorted. We present an on-demand, in-memory indexing approach to performing structural joins. There is no need to sort the elements. We discover that there are similarities between the problems of structural joins and stabbing queries. However, previous work on stabbing queries, although efficient in search time, is not directly applicable to structural joins because of high storage costs. We develop two storage reduction techniques to alleviate the problem of high storage costs. Simulations show that our new method outperforms prior approaches. © Springer-Verlag Berlin Heidelberg 2006.