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How to Evaluate Multiple Range-Sum Queries Progressively

机译:如何逐步评估多个范围和查询

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摘要

Users of decision support system typically submit batches of range-sum queries simultaneously rather than issuing individual, unrelated queries. We propose a wavelet based technique that exploits I/O sharing across a query batch to evaluate the set of queries progressively and efficiently. The challenge is that now controlling the structure of errors across query results becomes more critical than minimizing error per individual query. Consequently, we define a class of structural error penalty functions and show how they are controlled by our technique. Experiments demonstrate that our technique is efficient as an exact algorithm, and the progressive estimates are accurate, even after less than one I/O per query.
机译:决策支持系统的用户通常同时提交批量的范围和查询,而不是发出单独的,不相关的查询。我们提出了一种基于小波的技术,该技术利用整个查询批处理中的I / O共享来逐步有效地评估查询集。挑战在于,现在控制跨查询结果的错误结构比最小化每个单个查询的错误更为关键。因此,我们定义了一类结构错误惩罚函数,并显示了如何通过我们的技术来控制它们。实验表明,即使每个查询少于一个I / O,我们的技术作为一种精确算法也是有效的,并且渐进估计是准确的。

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