Attribute-based Approach for Multiple Continuous Queries over Data Streams 


Vol. 14,  No. 5, pp. 459-470, Aug.  2007
10.3745/KIPSTD.2007.14.5.459


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  Abstract

A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Query processing for such a data stream should also be continuous and rapid, which requires strict time and space constraints. In most DSMS (Data Stream Management System), the selection predicates of continuous queries are grouped or indexed to guarantee these constraints. This paper proposes a new scheme called an ASC (Attribute Selection Construct) that collectively evaluates selection predicates containing the same attribute in multiple continuous queries. An ASC contains valuable information, such as attribute usage status, partially pre-calculated matching results and selectivity statistics for its multiple selection predicates. The processing order of those ASC’s that are corresponding to the attributes of a base data stream can significantly influence the overall performance of multiple query evaluation. Consequently, a method of establishing an efficient evaluation order of multiple ASC’s is also proposed. Finally, the performance of the proposed method is analyzed by a series of experiments to identify its various characteristics.

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[IEEE Style]

H. H. Lee and W. S. Lee, "Attribute-based Approach for Multiple Continuous Queries over Data Streams," The KIPS Transactions:PartD, vol. 14, no. 5, pp. 459-470, 2007. DOI: 10.3745/KIPSTD.2007.14.5.459.

[ACM Style]

Hyun Ho Lee and Won Suk Lee. 2007. Attribute-based Approach for Multiple Continuous Queries over Data Streams. The KIPS Transactions:PartD, 14, 5, (2007), 459-470. DOI: 10.3745/KIPSTD.2007.14.5.459.

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