Spatial query processing for high resolutions

Kriegel, Hans‐Peter; Pfeifle, Martin; Pötke, Marco; Seidl, Armin H.

doi:10.1109/dasfaa.2003.1192364

Cited by 6 publications

(1 citation statement)

References 20 publications

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“…If such a badly approximated MBR were used to index a query, search efficiency of the query index would become worse. For example, in Figure 14 In order to resolve the problem, we exploit the object decomposition method [14]. The object decomposition method divides a query region into an arbitrary number of pieces and constructs an MBR for each piece.…”

Section: Extension Of the Query Indexing Methodsmentioning

confidence: 99%

Continuous query processing in data streams using duality of data and queries

Lim

Lee

et al. 2006

Proceedings of the 2006 ACM SIGMOD International Conference on Management of Data

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Recent data stream systems such as TelegraphCQ have employed the well-known property of duality between data and queries. In these systems, query processing methods are classified into two dual categories -data-initiative and query-initiative -depending on whether query processing is initiated by selecting a data element or a query. Although the duality property has been widely recognized, previous data stream systems do not fully take advantages of this property since they use the two dual methods independently: data-initiative methods only for continuous queries and query-initiative methods only for ad-hoc queries. We contend that continuous query processing can be better optimized by adopting an approach that integrates the two dual methods. Our primary contribution is based on the observation that spatial join is a powerful tool for achieving this objective. In this paper, we first present a new viewpoint of transforming the continuous query processing problem to a multi-dimensional spatial join problem. We then present a continuous query processing algorithm based on spatial join, which we name Spatial Join CQ. This algorithm processes continuous queries by finding the pairs of overlapping regions from a set of data elements and a set of queries, both defined as regions in the multi-dimensional space. The algorithm achieves the advantages of the two dual methods simultaneously. Experimental results show that the proposed algorithm outperforms earlier algorithms by up to 36 times for simple selection continuous queries and by up to 7 times for sliding window join queries.

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Section: Extension Of the Query Indexing Methodsmentioning

confidence: 99%