Selectively Storing XML Data in Relations

Abstract

Abstract. This paper presents a new framework for users to select relevant data from an XML document and store it in an existing relational database, as opposed to previous approaches that shred the entire XML document into a newly created database of a newly designed schema. The framework is based on a notion of XML2DB mappings. An XML2DB mapping extends a (possibly recursive) DTD by associating element types with semantic attributes and rules. It extracts either part or all of the data from an XML document, and generates SQL updates to increment an existing database using the XML data. We also provide an efficient technique to evaluate XML2DB mappings in parallel with SAX parsing. These yield a systematic method to store XML data selectively in an existing database.

A data-centric approach to manage business processes

“…There are many attempts to convert XML data into relational format [17,33] and vice versa [18,19,55]. These works have addressed complex conversion problems, namely the capacity of database storage, the performance of the parser, the definition of semantic constraints (primary keys, foreign keys, etc.…”

XML Publishing: Bridging Theory and Practice

“…In contrast to publishing transducers, an XML shredding automaton outputs a relation instead of an XML tree. Based on this an XML shredding language has been given in [14]. XML shredding automata can be used to characterize the expressive power and complexity of XML shredding languages found in practice.…”