A large number of continual range queries could be issued against numerical data streams, such as stock prices, sensor readings, temperatures, and others. To efficiently process these long-running queries, only the potentially relevant queries should be evaluated against the data. We develop a virtual construct-based query indexing approach to efficiently identifying the range queries that match each data object in the streams. A set of virtual constructs, e.g., intervals in 1D space or rectangular regions in 2D space, are predefined such that it is efficient to find all the virtual constructs containing any given data object. Each virtual construct has a unique ID and an associated query ID list. The query index is built as follows. Each range query is first decomposed into one or more virtual constructs. The query ID is then inserted into the query ID lists associated with those decomposed virtual constructs. Search becomes extremely efficient. For a given data object, we first find all virtual constructs covering it. Then, we report the matched queries from the ID lists associated with the covering virtual constructs.
By: Kun-Lung Wu, Shyh-Kwei Chen, Philip S. Yu
Published in: RC23249 in 2004
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