Storing semistructured data with STORED
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Equivalences Among Relational Expressions with the Union and Difference Operators
Journal of the ACM (JACM)
The importance of being biased
STOC '02 Proceedings of the thiry-fourth annual ACM symposium on Theory of computing
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Relational Databases for Querying XML Documents: Limitations and Opportunities
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Efficient Relational Storage and Retrieval of XML Documents
Selected papers from the Third International Workshop WebDB 2000 on The World Wide Web and Databases
Hardness of Approximating Problems on Cubic Graphs
CIAC '97 Proceedings of the Third Italian Conference on Algorithms and Complexity
The XML benchmark project
Storing XML (with XSD) in SQL Databases: Interplay of Logical and Physical Designs
IEEE Transactions on Knowledge and Data Engineering
UserMap: an adaptive enhancing of user-driven XML-to-relational mapping strategies
ADC '08 Proceedings of the nineteenth conference on Australasian database - Volume 75
Holistic schema mappings for XML-on-RDBMS
DASFAA'06 Proceedings of the 11th international conference on Database Systems for Advanced Applications
Efficient fragmentation of large XML documents
DEXA'07 Proceedings of the 18th international conference on Database and Expert Systems Applications
Hi-index | 0.00 |
A key problem that arises in the context of storing XML documents in relational databases is that of finding an optimal relational decomposition for a given set of XML documents and a given set of XML queries over those documents. While there have been a number of ad hoc solutions proposed for this problem, to our knowledge this paper represents a first step toward formalizing the problem and studying its complexity. It turns out that to even define what one means by an optimal decomposition, one first needs to specify an algorithm to translate XML queries to relational queries, and a cost model to evaluate the quality of the resulting relational queries. By examining an interesting problem embedded in choosing a relational decomposition, we show that choices of different translation algorithms and cost models result in very different complexities for the resulting optimization problems. Our results suggest that, contrary to the trend in previous work, the eventual development of practical algorithms for finding relational decompositions for XML workloads will require judicious choices of cost models and translation algorithms, rather than an exclusive focus on the decomposition problem in isolation.