Abstract
This paper presents Plug&Join, a new generic algorithm for efficiently processing a broad class of different join types in extensible database systems. Depending on the join predicate Plug&Join is called with a suitable type of index structure as a parameter. If the inner relation fits in memory, the algorithm builds a memory resident index of the desired type on the inner relation and probes all tuples of the outer relation against the index. Otherwise, a memory resident index is created by sampling the inner relation. The index is then used as a partitioning function for both relations.
In order to demonstrate the flexibility of Plug&Join, we present how to implement equi joins, spatial joins and subset joins by using memory resident B+-trees, R-trees and S-trees, respectively. Moreover, results obtained from different experiments for the spatial join show that Plug&Join is competitive to special- purpose methods like the Partition Based Spatial-Merge Join algorithm.
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van den Bercken, J., Schneider, M., Seeger, B. (2000). Plug&Join: An Easy-To-Use Generic Algorithm for Efficiently Processing Equi and Non-equi Joins. In: Zaniolo, C., Lockemann, P.C., Scholl, M.H., Grust, T. (eds) Advances in Database Technology — EDBT 2000. EDBT 2000. Lecture Notes in Computer Science, vol 1777. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46439-5_34
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DOI: https://doi.org/10.1007/3-540-46439-5_34
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