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LAD: Layered Adaptive Data Integration Architecture

机译:LAD:分层自适应数据集成架构

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Web based data integration systems run in an unpredictable and dynamic environment, which makes the traditional query processing approach inapplicable. Problems necessitating AQP (Adaptive Query Processing) techniques include: (1) statistics may be insufficient; (2) statistics may be imprecise; (3) unavailable data sources may make query results incomplete. In this paper, we present a novel data integration architecture LAD (Layered Adaptive Data integration architecture) to resolve problems mentioned above. Adopted adaptive techniques include: (1) defer making the initial plan if there are not enough high quality statistics; (2) perform re-optimizing operation if distinct deflection is detected; (3) exploit data redundancy to deal with unavailable data sources. Experiment results show that LAD provides satisfactory adaptability and efficiency in the face of uncertainty and dynamics.
机译:基于Web的数据集成系统在不可预测和动态的环境中运行,这使得传统的查询处理方法不可应用。需要AQP(自适应查询处理)技术的问题包括:(1)统计可能不足; (2)统计可能不精确; (3)不可用的数据源可能会使查询结果不完整。在本文中,我们提出了一种新的数据集成架构LAD(分层自适应数据集成架构)以解决上述问题。采用的自适应技术包括:(1)推迟制定初始计划如果没有足够的高质量统计数据; (2)如果检测到不同的偏转,则执行重新优化操作; (3)利用数据冗余以处理不可用的数据源。实验结果表明,面对不确定和动态,LAD提供了令人满意的适应性和效率。

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