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<p>A query processing strategy which is based on pipelining and data-flow techniques is presented. Timing equations are developed for calculating the performance of four join algorithms: nested block, hash, sort-merge, and pipelined sort-merge. They are used to execute the join operation in a query in distributed fashion and in pipelined fashion. Based on these equations and similar sets of equations developed for other relational algebraic operations, the performance of query execution was evaluated using the different join algorithms. The effects of varying the values of processing time, I/O time, communication time, buffer size, and join selectively on the performance of the pipelined join algorithms are investigated. The results are compared to the results obtained by employing the same algorithms for executing queries using the distributed processing approach which does not exploit the vertical concurrency of the pipelining approach. These results establish the benefits of pipelining</p>
relational databases; distributed databases; timing equations; relational join algorithms; pipelined query processing environment; nested block; hash; sort-merge; pipelined sort-merge; query execution; distributed processing; database theory; distributed databases; merging; performance evaluation; pipeline processing; relational databases; sorting

K. Mikkilineni and S. Su, "An Evaluation of Relational Join Algorithms in a Pipelined Query Processing Environment," in IEEE Transactions on Software Engineering, vol. 14, no. , pp. 838-848, 1988.
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