Query processing of streamed XML data
Proceedings of the eleventh international conference on Information and knowledge management
Efficient Filtering of XML Documents for Selective Dissemination of Information
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
XPath queries on streaming data
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Data stream management for historical XML data
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
On the memory requirements of XPath evaluation over XML streams
PODS '04 Proceedings of the twenty-third ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Buffering in query evaluation over XML streams
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Semantic query optimization for XQuery over XML streams
VLDB '05 Proceedings of the 31st international conference on Very large data bases
A transducer-based XML query processor
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Semantic query optimization in an automata-algebra combined XQuery engine over XML streams
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
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With respect to current methods for query evaluation over XML data streams, adoption of certain types of buffering techniques is unavoidable. Under lots of circumstances, the buffer scale may increase exponentially, which can cause memory bottleneck. Some optimization techniques have been proposed to solve the problem. However, the limit of these techniques has been defined by a concurrency lower bound and been theoretically proved. In this paper, we show through an empirical study that this lower bound can be broken by taking semantic information into account for buffer reduction. To demonstrate this, we build a SAX-based XML stream query evaluation system and design an algorithm that consumes buffers in line with the concurrency lower bound. After a further analysis of the lower bound, we design several semantic rules for the purpose of breaking the lower bound and incorporate these rules in the lower bound algorithm. Experiments are conducted to show that the algorithms deploying semantic rules individually and collectively all significantly outperform the lower bound algorithm that does not consider semantic information.