The Design and Implementation of Seeded Trees: An Efficient Method for Spatial Joins

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—Existing methods for spatial joins require pre-existing spatial indices or other precomputation, but such approaches are inefficient and limited in generality. Operand data sets of spatial joins may not all have precomputed indices, particularly when they are dynamically generated by other selection or join operations. Also, existing spatial indices are mostly designed for spatial selections, and are not always efficient for joins. This paper explores the design and implementation of seeded trees [1], which are effective for spatial joins and efficient to construct at join time. Seeded trees are R-tree-like structures, but divided into seed levels and grown levels. This structure facilitates using information regarding the join to accelerate the join process, and allows efficient buffer management. In addition to the basic structure and behavior of seeded trees, we present techniques for efficient seeded tree construction, a new buffer management strategy to lower I/O costs, and the...

Ming-Ling Lo, Chinya V. Ravishankar

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