L-Tree: A Dynamic Labeling Structure for Ordered XML Data

With the ever growing use of XML as a data representation format, we see an increasing need for robust, high performance XML database systems. While most of the recent work focuses on efficient XML query processing, XML databases also need to support efficient updates. To speed up query processing, various labeling schemes have been proposed. However, the vast majority of these schemes have poor update performance. In this paper, we introduce a dynamic labeling structure for XML data: L-Tree and its orderpreserving labeling scheme with O(log n) amortized update cost and O(log n) bits per label. L-Tree has good performance on updates without compromising the performance of query processing. We present the update algorithm for L-Tree and analyze its complexity. Comments Postprint version. Published in Lecture Notes in Computer Science, Current Trends in Database Technology EDBT 2004 Workships, Volume 3268, 2004, pages 209-218. Publisher URL: http://dx.doi.org/10.1007/b101218 This conference paper is available at ScholarlyCommons: http://repository.upenn.edu/db_research/33 L-Tree: a Dynamic Labeling Structure for Ordered XML Data Yi Chen , George A. Mihaila , Rajesh Bordawekar , and Sriram Padmanabhan University of Pennsylvania, [email protected] IBM T.J. Watson Research Center, mihaila,srp,bordaw @us.ibm.com Abstract. With the ever growing use of XML as a data representation format, we see an increasing need for robust, high performance XML database systems. While most of the recent work focuses on efficient XML query processing, XML databases also need to support efficient updates. To speed up query processing, various labeling schemes have been proposed. However, the vast majority of these schemes have poor update performance. In this paper, we introduce a dynamic labeling structure for XML data: L-Tree and its order-preserving labeling scheme with O(log n) amortized update cost and O(log n) bits per label. L-Tree has good performance on updates without compromising the performance of query processing. We present the update algorithm for L-Tree and analyze its complexity. With the ever growing use of XML as a data representation format, we see an increasing need for robust, high performance XML database systems. While most of the recent work focuses on efficient XML query processing, XML databases also need to support efficient updates. To speed up query processing, various labeling schemes have been proposed. However, the vast majority of these schemes have poor update performance. In this paper, we introduce a dynamic labeling structure for XML data: L-Tree and its order-preserving labeling scheme with O(log n) amortized update cost and O(log n) bits per label. L-Tree has good performance on updates without compromising the performance of query processing. We present the update algorithm for L-Tree and analyze its complexity.