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2013 IEEE 29th International Conference on Data Engineering (ICDE) (2002)
San Jose, California
Feb. 26, 2002 to Mar. 1, 2002
ISBN: 0-7695-1531-2
pp: 0141
Yuqing Wu , Univ of Michigan
Shurug Al-Khalifa , Univ of Michigan
Divesh Srivastava , AT&T Labs-Research
Jignesh M. Patel , Univ of Michigan
Nick Koudas , AT&T Labs-Research
H. V. Jagadish , Univ of Michigan
XML queries typically specify patterns of selection predicates on multiple elements that have some specified tree structured relationships. The primitive tree structured relationships are parent-child and ancestor-descendant, and finding all occurrences of these relationships in an XML database is a core operation for XML query processing.In this paper, we develop two families of structural join algorithms for this task: tree-merge and stack-tree. The tree-merge algorithms are a natural extension of traditional merge joins and the recently proposed multi-predicate merge joins, while the stack-tree algorithms have no counterpart in traditional relational join processing. We present experimental results on a range of data and queries using the TIMBER native XML query engine built on top of SHORE. We show that while, in some cases, tree-merge algorithms can have performance comparable to stack-tree algorithms, in many cases they are considerably worse. This behavior is explained by analytical results that demonstrate that, on sorted inputs, the stack-tree algorithms have worst-case I/O and CPU complexities linear in the sum of the sizes of inputs and output, while the tree-merge algorithms do not have the same guarantee.
Yuqing Wu, Shurug Al-Khalifa, Divesh Srivastava, Jignesh M. Patel, Nick Koudas, H. V. Jagadish, "Structural Joins: A Primitive for Efficient XML Query Pattern Matching", 2013 IEEE 29th International Conference on Data Engineering (ICDE), vol. 00, no. , pp. 0141, 2002, doi:10.1109/ICDE.2002.994704
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