The Nimble XML Data Integration System
Proceedings of the 17th International Conference on Data Engineering
XQuery: a query language for XML
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Constraint-based XML query rewriting for data integration
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Native Xquery processing in oracle XMLDB
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
XML and relational database management systems: inside Microsoft® SQL Server™ 2005
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Native XML support in DB2 universal database
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Efficient Query Processing for Large XML Data in Distributed Environments
AINA '07 Proceedings of the 21st International Conference on Advanced Networking and Applications
A Parallel Approach to XML Parsing
GRID '06 Proceedings of the 7th IEEE/ACM International Conference on Grid Computing
Orchid: Integrating Schema Mapping and ETL
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Cost-based vectorization of instance-based integration processes
Information Systems
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Data Integration engines increasingly need to provide sophisticated processing options for XML data. In the past, it was adequate for these engines to support basic shredding and XML generation capabilities. However, with the steady growth of XML in applications and databases, integration platforms need to provide more direct operations on XML as well as improve the scalability and efficiency of these operations. In this paper, we describe a robust and comprehensive framework for performing Extract-Transform-Load (ETL) of XML. This includes (i) full computational model and engine capabilities to perform these operations in an ETL flow, (ii) an approach to pushing down XML operations into a database engine capable of supporting XML processing, and (iii) methods to apply partitioning techniques to provide scalable, parallel processing for large XML documents. We describe experimental results showing the effectiveness of these techniques.