MM-infer:一个多模型图式推断工具

P. Koupil, Sebastián Hricko, I. Holubová
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引用次数: 6

摘要

以多模型数据为代表的大数据的多样性给数据管理带来了新的复杂性维度。需要处理一组不同但相互关联的模型是一项具有挑战性的任务。在我们的演示中,我们展示了我们的原型实现MM-infer,它确保对多模型数据的公共模式进行推断。它支持流行的数据模型及其相互组合的所有三种类型,即模型间引用、模型嵌入和跨模型冗余。按照目前的趋势,该实现可以高效地处理大量数据。据我们所知,我们的工具是第一个在多模型数据库世界中处理模式推断的工具。
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MM-infer: A Tool for Inference of Multi-Model Schemas
The variety feature of Big Data, represented by multi-model data, has brought a new dimension of complexity to data management. The need to process a set of distinct but interlinked models is a challenging task. In our demonstration, we present our prototype implementation MM-infer that ensures inference of a common schema of multi-model data. It supports popular data models and all three types of their mutual combinations, i.e., inter-model references, the embedding of models, and cross-model redundancy. Following the current trends, the implementation can efficiently process large amounts of data. To the best of our knowledge, ours is the first tool addressing schema inference in the world of multi-model databases.
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