Change detection in hierarchically structured information
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Meaningful change detection in structured data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
XRel: a path-based approach to storage and retrieval of XML documents using relational databases
ACM Transactions on Internet Technology (TOIT)
Path materialization revisited: an efficient storage model for XML data
ADC '02 Proceedings of the 13th Australasian database conference - Volume 5
Relational Databases for Querying XML Documents: Limitations and Opportunities
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Detecting Changes in XML Documents
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
XML parsing: a threat to database performance
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
XBench Benchmark and Performance Testing of XML DBMSs
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
XANADUE: a system for detecting changes to XML data in tree-unaware relational databases
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
An XQuery-based version extension of an XML native database
Proceedings of the 2009 EDBT/ICDT Workshops
Automation everywhere: autonomics and data management
BNCOD'07 Proceedings of the 24th British national conference on Databases
OXONE: a scalable solution for detecting superior quality deltas on ordered large xml documents
ER'06 Proceedings of the 25th international conference on Conceptual Modeling
| Hi-index | 0.00 |
Previous work in change detection to XML documents is not suitable for detecting the changes to large XML documents as it requires a lot of memory to keep the two versions of XML documents in the memory. In this article, we take a more conservative yet novel approach of using traditional relational database engines for detecting the changes to large ordered XML documents. To this end, we have implemented a prototype system called XANDY that converts XML documents into relational tuples and detects the changes from these tuples by using SQL queries. Our experimental results show that the relational-based approach has better scalability compared to published algorithm like X-Diff. It has comparable efficiency and result quality compared to X-Diff in some cases. Our experimental results also show that, generally, XANDY has better result quality than XyDiff.