Xandy: A scalable change detection technique for ordered XML documents using relational databases

摘要

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.