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Optimization of Nested Queries Using the NF2 Algebra

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2016

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SIGMOD '16: Proceedings of the 2016 International Conference on Management of Data. New York, NY, USA: ACM, 2016, pp. 1765-1780. Available under: doi: 10.1145/2882903.2915241

Zusammenfassung

A key promise of SQL is that the optimizer will find the most efficient execution plan, regardless of how the query is formulated. In general, query optimizers of modern database systems are able to keep this promise, with the notable exception of nested queries. While several optimization techniques for nested queries have been proposed, their adoption in practice has been limited. In this paper, we argue that the NF2 (non-first normal form) algebra, which was originally designed to process nested tables, is a better approach to nested query optimization as it fulfills two key requirements. First, the NF2 algebra can represent all types of nested queries as well as both existing and novel optimization techniques based on its equivalences. Second, performance benefits can be achieved with little changes to existing transformation-based query optimizers as the NF2 algebra is an extension of the relational algebra.

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2016 ACM SIGMOD/PODS Conference : International Conference on Management of Data, 26. Juni 2016 - 1. Juli 2016, San Francisco, CA, USA
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ISO 690HÖLSCH, Jürgen, Michael GROSSNIKLAUS, Marc H. SCHOLL, 2016. Optimization of Nested Queries Using the NF2 Algebra. 2016 ACM SIGMOD/PODS Conference : International Conference on Management of Data. San Francisco, CA, USA, 26. Juni 2016 - 1. Juli 2016. In: SIGMOD '16: Proceedings of the 2016 International Conference on Management of Data. New York, NY, USA: ACM, 2016, pp. 1765-1780. Available under: doi: 10.1145/2882903.2915241
BibTex
@inproceedings{Holsch2016Optim-33583,
  year={2016},
  doi={10.1145/2882903.2915241},
  title={Optimization of Nested Queries Using the NF<sup>2</sup> Algebra},
  publisher={ACM},
  address={New York, NY, USA},
  booktitle={SIGMOD '16: Proceedings of the 2016 International Conference on Management of Data},
  pages={1765--1780},
  author={Hölsch, Jürgen and Grossniklaus, Michael and Scholl, Marc H.}
}
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