Xandy: Detecting Changes on Large Unordered XML Documents Using Relational Databases

E Leonardi, SS Bhowmick, S Madria - … 2005, Beijing, China, April 17-20 …, 2005 - Springer
Database Systems for Advanced Applications: 10th International Conference …, 2005Springer
Previous works in change detection on XML documents are 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 paper, we take a more conservative yet novel
approach of using traditional relational database engines for detecting the changes to large
unordered XML documents. We elaborate how we detect the changes on unordered XML
documents by using relational database. To this end, we have implemented a prototype …
Abstract
Previous works in change detection on XML documents are 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 paper, we take a more conservative yet novel approach of using traditional relational database engines for detecting the changes to large unordered XML documents. We elaborate how we detect the changes on unordered XML documents by using relational database. 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 approach has better scalability compared to published algorithms like X-Diff. The result quality of our approach is comparable to the one of X-Diff.
Springer
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