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Keyword search on relational data streams

Authors Markowetz, A. HKUST affiliated (currently or previously)
Yang, Y. HKUST affiliated (currently or previously)
Papadias, D. View this author's profile
Issue Date 2007
Source Proceedings of the ACM SIGMOD International Conference on Management of Data , 2007, p. 605-616
Summary Increasing monitoring of transactions, environmental parameters, homeland security, RFID chips and interactions of online users rapidly establishes new data sources and application scenarios. In this paper, we propose keyword search on relational data streams (S-KWS) as an effective way for querying in such intricate and dynamic environments. Compared to conventional query methods, S-KWS has several benefits. First, it allows search for combinations of interesting terms without a-priori knowledge of the data streams in which they appear. Second, it hides the schema from the user and allows it to change, without the need for query re-writing. Finally, keyword queries are easy to express. Our contributions are summarized as follows. (i) We provide formal semantics for S-KWS, addressing the temporal validity and order of results. (ii) We propose an efficient algorithm for generating operator trees, applicable to arbitrary schemas. (iii) We integrate these trees into an operator mesh that shares common expressions. (iv) We develop techniques that utilize the operator mesh for efficient query processing. The techniques adapt dynamically to changes in the schema and input characteristics. Finally, (v) we present methods for purging expired tuples, minimizing either CPU, or memory requirements. Copyright 2007 ACM.
ISSN 0730-8078
Rights © ACM, 2007. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings 2007 ACM SIGMOD International Conference on Management of Data, Beijing, China, 14-17 June 2007, p. 605-616
Language English
Format Conference paper
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