A Methodology for Coupling Fragments of XPath with Structural Indexes for XML Documents

Supporting efficient access to XML data using XPath [3] continues to be an important research problem [6, 12]. XPath queries are used to specify nodelabeled trees which match portions of the hierarchical XML data. In XPath query evaluation, indices similar to those used in relational database systems – namely, value indices on tags and text values – are first used, together with structural join algorithms [1, 2, 19]. This approach turns out to be simple and efficient. However, the structural containment relationships native to XML data are not directly captured by value indices. To directly capture the structural information of XML data, a family of structural indices has been introduced. DataGuide [5] was the first to be proposed, followed by the 1-index [13], which is based on the notion of bi-simulation among nodes in an XML document. These indices can be used to evaluate some path expressions accurately without accessing the original data graph. Milo and Suciu [13] also introduced the 2-index and T-index, based on similarity of pairs (vectors) of nodes. Unfortunately, these and other early structural indices tend to be too large for practical use because they typically maintain too fine-grained structural information about the document [9, 16]. To remedy this, Kaushik et al. introduced the A(k)-index which uses a notion of bi-similarity on nodes relativized to paths of length k [10]. This captures localized structural information of a document, and can support path expressions of length up to k. Focusing just on local similarity, the A(k)-index can be substantially smaller than the 1-index and others. Several works have investigated maintenance and tuning of the A(k) indices. The D(k)-index [15] and M(k)-index [8] extend the A(k)-index to adapt to query workload. Yi et al. [18] developed update techniques for the A(k)-index and 1-index. Finally, the integrated use of structural and value indices has been