• Corpus ID: 238252940

MATE: Multi-Attribute Table Extraction

@article{Esmailoghli2022MATEMT,
  title={MATE: Multi-Attribute Table Extraction},
  author={Mahdi Esmailoghli and Jorge-Arnulfo Quian'e-Ruiz and Ziawasch Abedjan},
  journal={Proc. VLDB Endow.},
  year={2022},
  volume={15},
  pages={1684-1696}
}
A core operation in data discovery is to find joinable tables for a given table. Real-world tables include both unary and n-ary join keys. However, existing table discovery systems are optimized for unary joins and are ineffective and slow in the existence of n-ary keys. In this paper, we introduce Mate, a table discovery system that leverages a novel hash-based index that enables n-ary join discovery through a space-efficient super key. We design a filtering layer that uses a novel hash, Xash… 

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