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Sample-based quality estimation of query results in relational database environments

机译：关系数据库环境中查询结果的基于样本的质量估计

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摘要

The quality of data in relational databases is often uncertain, and the relationship between the quality of the underlying base tables and the set of potential query results, a type of information product (IP), that could be produced from them has not been fully investigated. This paper provides a basis for the systematic analysis of the quality of such IPs. This research uses the relational algebra framework to develop estimates for the quality of query results based on the quality estimates of samples taken from the base tables. Our procedure requires an initial sample from the base tables; these samples are then used for all possible information IPs. Each specific query governs the quality assessment of the relevant samples. By using the same sample repeatedly, our approach is relatively cost effective. We introduce the reference-table procedure, which can be used for quality estimation in general. In addition, for each of the basic algebraic operators, we discuss simpler procedures that may be applicable. Special attention is devoted to the join operation. We examine various, relevant statistical issues, including how to deal with the impact on quality of missing rows in base tables. Finally, we address several implementation issues related to sampling.
机译：关系数据库中数据的质量通常是不确定的，底层基础表的质量与潜在查询结果集（一种可能从中产生的信息产品（IP））之间的关系尚未得到充分研究。 。本文为对此类IP的质量进行系统分析提供了基础。这项研究使用关系代数框架，根据从基表中获取的样本的质量估算来开发查询结果质量的估算。我们的过程需要基础表中的初始样本。然后将这些样本用于所有可能的信息IP。每个特定的查询都控制相关样本的质量评估。通过重复使用相同的样本，我们的方法相对具有成本效益。我们介绍了参考表程序，该程序通常可用于质量估计。此外，对于每个基本代数运算符，我们讨论可能适用的更简单的过程。特别注意加入操作。我们研究了各种相关的统计问题，包括如何处理对基表中缺失行的质量的影响。最后，我们解决了与抽样有关的几个实施问题。

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