Two algorithms for maintaining order in a list
STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
The design and analysis of spatial data structures
The design and analysis of spatial data structures
On supporting containment queries in relational database management systems
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Holistic twig joins: optimal XML pattern matching
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Indexing and Querying XML Data for Regular Path Expressions
Proceedings of the 27th International Conference on Very Large Data Bases
Structural Joins: A Primitive for Efficient XML Query Pattern Matching
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Efficient Processing of XML Containment Queries Using Partition-Based Schemes
IDEAS '04 Proceedings of the International Database Engineering and Applications Symposium
Query indexing with containment-encoded intervals for efficient stream processing
Knowledge and Information Systems
Efficient structural joins on indexed XML documents
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Holistic twig joins on indexed XML documents
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Staircase join: teach a relational DBMS to watch its (axis) steps
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
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A structural join finds all occurrences of structural, or containment, relationship between two sets of XML node elements: ancestor and descendant. Prior approaches to structural joins mostly focus on maintaining offline indexes on disks or requiring the elements in both sets to be sorted. However, either one can be expensive. More important, not all node elements are beforehand indexed or sorted. We present an on-demand, in-memory indexing approach to performing structural joins. There is no need to sort the elements. We discover that there are similarities between the problems of structural joins and stabbing queries. However, previous work on stabbing queries, although efficient in search time, is not directly applicable to structural joins because of high storage costs. We develop two storage reduction techniques to alleviate the problem of high storage costs. Simulations show that our new method outperforms prior approaches.