Implementing relational database operations in a cube-connected multicomputer system

Parallel architectures for database processing should incorporate parallel CPU as well as parallel I/O (disk access) capability. The need to support parallel I/O gives rise to two important issues - data combination and non-uniform data distribution. Strategies for performing database operations in a cube-connected multicomputer system with parallel I/O are presented in this paper. The cube interconnection subsumes many other structures such as the tree, ring, etc. This property is exploited to efficiently support database operations such as Select, Aggregate, Join, and Project. The strategies presented here are unique in that they account for the non-uniform distribution of data across parallel paths by incorporating data redistribution steps as part of the overall algorithm. The two main data redistribution operations used are tuple balancing and merging. A simple analysis of the join and project operations is carried out assuming non-uniform data distributions. A more detailed simulation and study of issues related to query processing will be carried out as part of the future work.

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