Lerong Cheng, Jinjun Xiong, et al.
ASP-DAC 2008
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. © 2009 VLDB Endowment.
Lerong Cheng, Jinjun Xiong, et al.
ASP-DAC 2008
Rafae Bhatti, Elisa Bertino, et al.
Communications of the ACM
Xiaozhu Kang, Hui Zhang, et al.
ICWS 2008
Elliot Linzer, M. Vetterli
Computing