Abstract
In this paper we study the problem of declustering twodimensional datasets with replication over parallel devices to improve range query performance. The related problem of declustering without replication has been well studied. It has been established that strictly optimal declustering schemes do not exist if data is not replicated. In addition to the usual problem of identifying a good allocation, the replicated version of the problem needs to address the issue of identifying a good retrieval schedule for a given query. We address both problems in this paper. An efficient algorithm for finding a lowest cost retrieval schedule is developed. This algorithm works for any query, not just range queries. Two replicated placement schemes are presented - one that results in a strictly optimal allocation, and another that guarantees a retrieval cost that is either optimal or 1 more than the optimal for any range query.
Portions of this work were supported by Grant EIA-9903545 from the National Science Foundation, Contract N00014-02-1-0364 from the Ofice of Naval Research, by sponsors of the Center for Education and Research in Information Assurance and Security, the GAANN fellowship, NSF CAREER grant IIS-9985019 and NSF Grant 9972883.
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Frikken, K., Atallah, M., Prabhakar, S., Safavi-Naini, R. (2002). Optimal Parallel I/O for Range Queries through Replication. In: Hameurlain, A., Cicchetti, R., Traunmüller, R. (eds) Database and Expert Systems Applications. DEXA 2002. Lecture Notes in Computer Science, vol 2453. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46146-9_66
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DOI: https://doi.org/10.1007/3-540-46146-9_66
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