2003 · 47 citations · 25 references
ComputingComputer EngineeringComputer ScienceDatabasesParallel AlgorithmsParallel ComputingData ParallelismParallel DatabasesQuery OptimizationQuery ProcessingRelational AlgebraSpatial Database SystemsJoin AlgorithmsJoin ProcessingParallel Join AlgorithmsParallel Spatial DatabasesSpatial Join ProcessingSpatial Joins
Interest in incremental and adaptive query processing has led to the investigation of equijoin evaluation algorithms that are non-blocking. This investigation has yielded a number of algorithms, including the symmetric hash join, the XJoin, the Ripple Join, and their variants. However, to our knowledge no one has proposed a nonblocking spatial join algorithm. In this paper, we propose a parallel non-blocking spatial join algorithm that uses duplicate avoidance rather than duplicate elimination. Results from a prototype implementation in a commercial parallel object-relational DBMS show that it generates answer tuples steadily even in the presence of memory overflow, and that its rate of producing answer tuples scales with the number of processors. Also, when allowed to run to completion, its performance is comparable with the state-of-the-art blocking parallel spatial join algorithm.
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The R*-tree: an efficient and robust access method for points and rectangles
Norbert Beckmann, Hans‐Peter Kriegel, Ralf Schneider et al. · 1990 · 4.2K citations · Full text
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