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Best-Effort Top-k Query Processing Under Budgetary Constraints

机译:预算约束下的尽力而为Top-k查询处理

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We consider a novel problem of top-k query processing under budget constraints. We provide both a framework and a set of algorithms to address this problem. Existing algorithms for top-k processing are budget-oblivious, i.e., they do not take budget constraints into account when making scheduling decisions, but focus on the performance to compute the final top-k results. Under budget constraints, these algorithms therefore often return results that are a lot worse than the results that can be achieved with a clever, budget-aware scheduling algorithm. This paper introduces novel algorithms for budget-aware top-k processing that produce results that have a significantly higher quality than those of state-of-the-art budget-oblivious solutions.
机译:我们考虑预算约束下的前k个查询处理的新问题。我们提供了一个框架和一组算法来解决此问题。现有的用于top-k处理的算法可以忽略预算,即,在制定调度决策时,它们不会考虑预算约束,而是专注于计算最终top-k结果的性能。因此,在预算约束下,这些算法返回的结果通常比使用聪明的,具有预算意识的调度算法所能获得的结果差很多。本文介绍了用于预算感知的top-k处理的新颖算法,该算法所产生的结果的质量比最新的预算无关的解决方案要高得多。

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