This paper presents and analyzes algorithms for parallel processing of relational database operations in a general multiprocessor framework. To analyze alternative algorithms, we introduce an analysis methodology which incorporates I/O, CPU, and message costs and which can be adjusted to fit different multiprocessor architectures. Algorithms are presented and analyzed for sorting, projection, and join operations. While some of these algorithms have been presented and analyzed previously, we have generalized each in order to handle the case where the number of pages is significantly larger than the number of processors. In addition, we present and analyze algorithms for the parallel execution of update and aggregate operations.

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