Queries on XML documents typically combine selections on element contents, and, via path expressions, the structural relationships between tagged elements. Structural joins are used to find all pairs of elements satisfying the primitive structural relationships specified in the query, namely, parent child and ancestor descendant relationships. Efficient support for structural joins is thus the key to efficient implementations of XML queries. Recently proposed node numbering schemes enable the capturing of the XML document structure us- ing traditional indices (such as B+-trees or R-trees). This paper proposes efficient struc- tural join algorithms in the presence of tag indices. We first concentrate on using B+- trees and show how to expedite a structural join by avoiding collections of elements that do not participate in the join. We then intro- duce an enhancement (based on sibling pointers) that further improves performance. Such sibling pointers are easily implemented and dynamically maintainable. We also present a structural join algorithm that utilizes R-trees.

XML documents are typically queried with a combination of value search and structure search. While querying by values can leverage traditional database technologies, evaluating structural relationship, specifically parent-child or ancestor-descendant relationship, between XML element sets has imposed a great challenge on efficient XML query processing. This paper proposes XR-tree, namely, XML Region Tree, which is a dynamic external memory index structure specially designed for strictly nested XML data. The unique feature of XR-tree is that, for a given element, all its ancestors (or descendants) in an element set indexed by an XRtree can be identified with optimal worst case I/O cost. We then propose a new structural join algorithm that can evaluate the structural relationship between two XR-tree indexed element sets by effectively skipping ancestors and descendants that do not participate in the join. Our extensive performance study shows that the XR-tree based join algorithm significantly outperforms previous algorithms. 1.

Abstract. With the advent of native and XML enabled database systems, techniques for efficiently storing, indexing and querying large collections of XML documents have become an important research topic. This paper presents the storage, indexing and query processing architecture of eXist, an Open Source native XML database system. eXist is tightly integrated with existing tools and covers most of the native XML database features. An enhanced indexing scheme at the architecture’s core supports quick identification of structural node relationships. Based on this scheme, we extend the application of path join algorithms to implement most parts of the XPath query language specification and add support for keyword search on element and attribute contents. 1. Overview eXist

As with relational data, XML data changes over time with the creation, modification, and deletion of XML documents. Expressing queries on timevarying (relational or XML) data is more difficult than writing queries on nontemporal data. In this paper, we present a temporal XML query language, XQuery, in which we add valid time support to XQuery by minimally extending the syntax and semantics of XQuery. We adopt a stratum approach which maps a XQuery query to a conventional XQuery. The paper focuses on how to perform this mapping, in particular, on mapping sequenced queries, which are by far the most challenging. The critical issue of supporting sequenced queries (in any query language) is time-slicing the input data while retaining period timestamping. Timestamps are distributed throughout an XML document, rather than uniformly in tuples, complicating the temporal slicing while also providing opportunities for optimization.

Abstract. In this paper, we present a method for representing the history of XML documents using Multidimensional XML (MXML). We demonstrate how a set of basic change operations on XML documents can be represented in MXML, and show that temporal XML snapshots can be obtained from MXML representations of XML histories. We also argue that our model is capable to represent changes not only in an XML document but to the corresponding XML Schema document aswell. 1

By storing the successive versions of a document in an incremental fashion, XML repositories and data warehouses achieve (i) the efficient preservation of critical information, and (ii) the ability of supporting historical queries on the evolution of documents and their contents. In this paper, we present efficient techniques for managing multiversion document histories and supporting powerful temporal queries on such documents. Our approach consists in (i) concisely representing the successive versions of a document as an XML document that implements a temporally grouped data model, and (ii) using XML query languages, such as XQuery, to express complex queries on the content of a particular version, and on the temporal evolution of the document elements and their contents. We show that the data definition & manipulation framework of XML & XQuery can support temporal models and historical queries significantly better than the traditional framework of Relational Tables & SQL. To demonstrate this point, we investigate how to express complex queries on the history of relational tables published as XML data.

There is much current interest in publishing and viewing database-resident data as XML documents. In fact, such XML views of the database can be easily visualized on web browsers and processed by web languages, including powerful query languages such as XQuery. As the database is updated, its external XML view also evolves. In this paper, we investigate the problem of representing the evolution history of such a view as yet another XML document, whereby the complete history of the database can also be visualized on web browsers, processed by web languages, and queried using powerful query languages such as XQuery. We investigate various approaches used for publishing relational data, and identify and select those which are best for representing and querying database histories. We show that the selected representations make it easy to formulate in XQuery temporal queries that are difficult to express using SQL on database relations. Finally, we discuss briefly the storage organization that can be used to support these queries efficiently.

Different models have been proposed recently for representing temporal data, tracking historical information, and recovering the state of the document as of any given time, in XML documents. We address the problem of indexing temporal XML documents. In particular we show that by indexing continuous paths, i.e. paths that are valid continuously during a certain interval in a temporal XML graph, we can dramatically increase query performance. We describe

Abstract. XML indices are essential for efficiently processing XML queries which typically have predicates on both structures and values. Since the number of all possible structural and value indices is large even for a small XML document with a simple structure, XML DBMSs must carefully choose which indices to build. In this paper, we propose a tool, called XIST, that can be used by an XML DBMS as an index selection tool. XIST exploits XML structural information, data statistics, and query workload to select the most beneficial indices. XIST employs a technique that organizes paths that are evaluated to the same result into equivalence classes and uses this concept to reduce the number of paths considered as candidates for indexing. XIST selects a set of candidate paths and evaluates the benefit of an index on each candidate path on the basis of performance gains for non-update queries and penalty for update queries. XIST also recognizes that an index on a path can influence the benefit of an index on another path and accounts for such index interactions. We present an experimental evaluation of XIST and current XML index selection techniques, and show that the indices selected by XIST result in greater overall improvements in query response times and often require less disk space. 1

In this paper we address the problem of evaluating path expression queries on multiversion XML documents. Such queries are typically implemented on static (i.e., non-versioned) documents as path joins, using numbering schemes that maintain the structural relationships among the document elements. We extend previously proposed pattern matching techniques so as to support versions. We first present an easily updatable numbering scheme that efficiently captures structural relationships among the elements of the dynamically evolving document. We then propose a variation of Pathstack, an optimal pattern matching algorithm, that addresses the characteristics of our environment. Finally, through a thorough experimental evaluation we investigate two storage techniques in terms of space utilization and query efficiency.