Abstract
Relational Keyword Search (R-KWS) provides an intuitive way to query relational data without requiring SQL, or knowledge of the underlying schema. In this article we describe a comprehensive framework for R-KWS covering snapshot queries on conventional tables and continuous queries on relational streams. Our contributions are summarized as follows: (i) We provide formal semantics, addressing the temporal validity and order of results, spanning uniformly over tables and streams; (ii) we investigate two general methodologies for query processing, graph based and operator based, that resolve several problems of previous approaches; and (iii) we develop a range of algorithms and optimizations covering both methodologies. We demonstrate the effectiveness of R-KWS, as well as the significant performance benefits of the proposed techniques, through extensive experiments with static and streaming datasets.
| Original language | English |
|---|---|
| Article number | 17 |
| Journal | ACM Transactions on Database Systems |
| Volume | 34 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 1 Aug 2009 |
| Externally published | Yes |
Keywords
- Data graph
- Data streams
- Query processing
- Relational databases
- Search
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