Efficient evaluation of multiple queries on streaming XML data
Proceedings of the eleventh international conference on Information and knowledge management
Processing XML Streams with Deterministic Automata
ICDT '03 Proceedings of the 9th International Conference on Database Theory
Efficient Filtering of XML Documents for Selective Dissemination of Information
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Stream processing of XPath queries with predicates
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
XPath queries on streaming data
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Efficient Filtering of XML Documents with XPath Expressions
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Light-weight xPath processing of XML stream with deterministic automata
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
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
The VLDB Journal — The International Journal on Very Large Data Bases
A transducer-based XML query processor
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
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The rapid growth in the amount of XML data and the development of publish-subscribe systems have led to great interest in processing streaming XML data. We propose the QstreamX system for querying streaming XML data using a novel structure, called Hash-Lookup Query Trees, which consists of a Filtering HashTable (FHT), a Static Query Tree (SQT) and a Dynamic Query Tree (DQT). The FHT is used to filter out irrelevant elements and provide direct access to relevant nodes in the SQT. The SQT is a tree model of the input query. Based on the SQT, the DQT is built dynamically at runtime to evaluate queries. We show, with experimental evidence, that QstreamX achieves throughput five times higher than the two most recently proposed stream querying systems, XSQ and XAOS, at much lower memory consumption.