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Parallel execution of hash joins in parallel databases

机译:在并行数据库中并行执行哈希联接

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We explore two important issues, processor allocation and the use of hash filters, to improve the parallel execution of hash joins. To exploit the opportunity of pipelining for hash join execution, a scheme to transform a bushy execution tree to an allocation tree is first devised. In an allocation tree, each node denotes a pipeline. Then, using the concept of synchronous execution time, processors are allocated to the nodes in the allocation tree in such a way that inner relations in a pipeline can be made available at approximately the same time. Also, the approach of hash filtering is investigated to further improve the parallel execution of hash joins. Extensive performance studies are conducted via simulation to demonstrate the importance of processor allocation and to evaluate various schemes using hash filters. It is experimentally shown that processor allocation is, in general, the dominant factor of performance, and the effect of hash filtering becomes more prominent as the number of relations in a query increases.
机译:我们探讨了两个重要问题,即处理器分配和哈希过滤器的使用,以改善哈希联接的并行执行。为了利用流水线进行哈希联接执行的机会,首先设计了一种将浓密执行树转换为分配树的方案。在分配树中,每个节点表示一个管道。然后,使用同步执行时间的概念,将处理器分配给分配树中的节点,使流水线中的内部关系可以大致同时使用。另外,研究了哈希过滤的方法,以进一步改善哈希联接的并行执行。通过仿真进行了广泛的性能研究,以证明处理器分配的重要性并使用哈希过滤器评估各种方案。实验表明,处理器分配通常是性能的主要因素,并且随着查询中关系数量的增加,哈希过滤的效果变得更加突出。

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