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Bmad-tree: an efficient data structure for parallel processing

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2 Author(s)
Das, S.K. ; Dept. of Comput. Sci., North Texas Univ., Denton, TX, USA ; Demuynck, M.A.

B-trees are used for accessing large database files, stored in lexicographic order on the secondary storage devices. Algorithms for concurrent B-tree data structures achieve only limited speedup when implemented on a parallel computer. To improve the performance, we propose a variant of the Blink-tree, called the Bmad -tree, which allows insertion without node splits, with multiple access in its leaf nodes, and dilation in both the index and the leaf nodes. Parallel algorithms for search, insert and restructuring are designed for partitioned, locked and distributed models. Only part of an insertion node is locked during the insert, and simultaneous insertions by multiple processors in the same node are allowed. A restructuring algorithm runs periodically in the background and requires at most one wait by any search or update operation. Our implementations demonstrate that the Bmad-tree algorithms outperform the best known Blink-trees, and compare favorably with linear hashing. We achieve good speedup (e.g., 4.79 with 8 processors) for partitioned algorithms, and moderate speedup (2.49 with 8 processors) for locked algorithms, even including overhead costs. The insert times obtained for Bmad-trees are 50% to 60% less than that for the Blink -trees in partitioned implementations, and 70% to 80% less in locked implementations. The speedup results on the distributed memory platform (a network of workstations) were not that encouraging due to high communication costs

Published in:

Parallel and Distributed Processing, 1996., Eighth IEEE Symposium on

Date of Conference:

23-26 Oct 1996

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