Patchwork — A query-driven locally adaptive data space partitioning
The major goal of spatial access methods in query optimization is to deliver the exact or a minimal superset of the result set and to perform this task at minimal cost. We present a clustering spatial access method that directly delivers exact result sets. Minimal cost is guaranteed through a cost-based adaptation strategy that dynamically determines and realizes storage clusters best suited for a set of spatial range queries.
We introduce a tessalation of the data space which allows irregular, arbitrary small and large patches. Such patches can be adapted to query ranges in order to answer queries at minimal cost. The adaptation cost is kept small by performing only local repartitioning. Thus only a small number of neighbouring patches are merged or split during an adaptation step. The directory part has to be simple to perform range queries at minimal cost and to allow frequent adaptation updates at moderate cost. An implementation and evaluation in a database prototype system environment is under developement.
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