• DOI:10.1145/3318464.3380579
Corpus ID: 208617519

Learning Multi-Dimensional Indexes

@article{Nathan2020LearningMI,
  title={Learning Multi-Dimensional Indexes},
  author={V. Nathan and J. Ding and M. Alizadeh and T. Kraska},
  journal={Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data},
  year={2020}
}

V. Nathan, J. Ding, +1 author T. Kraska

Published 2020

Computer Science

Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data

Scanning and filtering over multi-dimensional tables are key operations in modern analytical database engines. To optimize the performance of these operations, databases often create clustered indexes over a single dimension or multi-dimensional indexes such as R-Trees, or use complex sort orders (e.g., Z-ordering). However, these schemes are often hard to tune and their performance is inconsistent across different datasets and queries. In this paper, we introduce Flood, a multi-dimensional in… CONTINUE READING

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