Worst Case Optimal Joins on Relational and XML data

Yuxing Chen
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引用次数: 3

Abstract

In recent data management ecosystem, one of the greatest challenges is the data variety. Data varies in multiple formats such as relational and (semi-)structured data. Traditional database handles a single type of data format and thus its ability to deal with different types of data formats is limited. To overcome such limitation, we propose a multi-model processing framework for relational and semi-structured data (i.e. XML), and design a worst-case optimal join algorithm. The salient feature of our algorithm is that it can guarantee that the intermediate results are no larger than the worst-case join results. Preliminary results show that our multi-model algorithm significantly outperforms the baseline join methods in terms of running time and intermediate result size.
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最坏情况下关系和XML数据的最优连接
在最近的数据管理生态系统中,最大的挑战之一是数据的多样性。数据有多种格式,如关系数据和(半)结构化数据。传统数据库处理单一类型的数据格式,因此其处理不同类型数据格式的能力受到限制。为了克服这种限制,我们提出了一个多模型处理框架,用于关系和半结构化数据(即XML),并设计了一个最坏情况最优连接算法。该算法的显著特点是可以保证中间结果不大于最坏情况下的连接结果。初步结果表明,我们的多模型算法在运行时间和中间结果大小方面明显优于基线连接方法。
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