Peter A. Boncz, Jan Flokstra, Torsten Grust, Maurice van Keulen, Stefan Manegold, K. Sjoerd Mullender, Jan Rittinger, Jens Teubner. MonetDB/XQuery-Consistent and Efficient Updates on the Pre/Post Plane. In Yannis E. Ioannidis, Marc H. Scholl, Joachim W. Schmidt, Florian Matthes, Michael Hatzopoulos, Klemens Böhm, Alfons Kemper, Torsten Grust, Christian Böhm, editors, Advances in Database Technology - EDBT 2006, 10th International Conference on Extending Database Technology, Munich, Germany, March 26-31, 2006, Proceedings. Volume 3896 of Lecture Notes in Computer Science, pages 1190-1193, Springer, 2006.
Relational XQuery processors aim at leveraging mature relational DBMS query processing technology to provide scalability and efficiency. To achieve this goal, various storage schemes have been proposed to encode the tree structure of XML documents in flat relational tables. Basically, two classes can be identified: (1) encodings using fixed-length surrogates, like the preorder ranks in the pre/post encoding  or the equivalent pre/size/level encoding , and (2) encodings using variable-length surrogates, like, e.g., ORDPATH  or P-PBiTree . Recent research  showed a clear advantage of the former for efficient evaluation of XPath location steps, exploiting techniques like cheap node order tests, positional lookup, and node skipping in staircase join . However, once updates are involved, variable-length surrogates are often considered the better choice, mainly as a straightforward implementation of structural XML updates using fixed-length surrogates faces two performance bottlenecks: (i) high physical cost (the preorder ranks of all nodes following the update position must be modified—on average 50% of the document), and (ii) low transaction concurrency (updating the size of all ancestor nodes causes lock contention on the document root).
In , we presented techniques that allow an efficient and ACID-compliant implementation of XML updates also on the pre/post (respectively pre/size/level encoding) without sacrificing its superior XPath (i.e., read-only) performance. This demonstration describes in detail, how we successfully implemented these techniques in MonetDB/XQuery [2, 1], an XML database system with full-fledged XQuery support. The system consists of the Pathfinder compiler that translates and optimizes XQuery into relational algebra , on top of the high-performance MonetDB relational database engine .