From XML schema to relations: a cost-based approach to XML storage

Abstract

XML has become an important medium for data representation, particularly when that data is exchanged over or browsed on the Internet. As the volume of XML data increases, there is a growing interest in storing XML in relational databases so that the well-developed features of these systems (e.g., concurrency control, crash recovery, query processors) can be re-used. However, given the wide variety of XML applications and the mismatch between XML's nested-tree structure and the flat tuples of the relational model, storing XML documents in relational databases presents interesting challenges.LegoDB is a cost-based XML-to-relational mapping engine that addresses this problem. It explores a space of possible mappings and selects the best mapping for a given application (defined by an XML Schema, XML data statistics, and an XML query workload). LegoDB leverages existing XML and relational technologies: it represents the target application using XML standards and constructs the space of configurations using XML-specific operations, and it uses a traditional relational optimizer to obtain accurate cost estimates of the derived configurations. In this paper, we describe the LegoDB mapping engine and provide experimental results that demonstrate the effectiveness of this approach.

Storing and Querying XML Data in Object-Relational DBMSs

“…They proposed three strategies to map DTDs into relational schemas and identified the Hybrid inlining algorithm as being superior to the other ones (in most cases). Most recently, Bohannon et al [2] introduced a cost-based framework for XML-to-relational storage mapping that automatically finds the best mapping for a given configuration of an XML Schema, XML data statistics, and an XML query workload. Like [25,2], we also use the schema of XML documents to derive a relational schema.…”

“…Most recently, Bohannon et al [2] introduced a cost-based framework for XML-to-relational storage mapping that automatically finds the best mapping for a given configuration of an XML Schema, XML data statistics, and an XML query workload. Like [25,2], we also use the schema of XML documents to derive a relational schema. However, unlike these previously discussed algorithms, we leverage the data type extensibility feature of ORDBMSs to provide a more efficient mapping.…”

Adaptive XML Shredding: Architecture, Implementation, and Challenges

“…In the examples that follow, for simplicity, we use the type notation from the XQuery type system, described in [8]. A formal definition of p-schemas and the corresponding grammar appear in [5].…”

“…LegoDB [5] generates a space of possible schema mappings by repeatedly transforming the original XML Schema, and for each transformed schema, applying a fixed mapping from XML Schema into relations. In this section, we describe how the fixed mapping is implemented.…”

XViz: A Tool for Visualizing XPath Expressions

“…In some cases there exist techniques that automatize some of these tasks: for example an approach for index selection is discussed in [1], and efficient mappings to relational storage are described in [3]. However, these techniques are quite complex, and by no means universally available.…”