Query Technology Over XML Streams Based On Macro Forest Transducers

Extensible Markup Language(XML) is a semi-structured data description language. XML is widely used in the Internet field because it has a highly readable, cross-platform and scalability and other features. XML is not only an excellent data storage format, but also a standard of Internet data sharing and interaction. The research of query algorithm over XML data has been hotspot in database field.In recent years, with the rapid popularization of the network in the industry and people’s daily lives, the number of network applications increase speedily. Many Web-based applications will continue to produce large amounts of detailed data automatically, such as meteorological real-time analysis, financial transaction log, and Internet security monitoring systems. As the amount of data exchange in network surges, "XML stream data" get widespread attention of the researchers. The processing of stream data has some characteristics like access once, sustained processing, limited storage and rapid response. So finding a small amount of valuable data out from the huge amounts of continuous arrival data, not only needs rich query capabilities and powerful query capabilities, and should avoid consuming too much system resources. However, most of the conventional mechanism over XML, can not apply to XML streams. Researchers must face new demands and challenges. Therefore, the study of query processing algorithms for XML streams becomes particularly important.XML streams query algorithm based on macro forest transducers is considered to be one of the best query algorithms. This paper presents a construction method of macro forest transducers according to XPath expression. The expression covers the core part of the XPath query, such as PC axis, AD axis, arbitrary multiple predicates and any level of nested predicate. Experiments show that the proposed approach supports a larger range of queries, as well as the number of transducers’ state is linearly related to the complexity of the query. The algorithm can also check out target results correctly with high efficiency.