DPconv: Super-Polynomially Faster Join Ordering

We revisit the join ordering problem in query optimization. The standard exact algorithm, DPccp, has a worst-case running time of O(3 n ). This is prohibitively expensive for large queries, which are not that uncommon anymore. We develop a new algorithmic framework based on subset convolution. DPconv achieves a super-polynomial speedup over DPccp, breaking the O(3 n ) time-barrier for the first time. We show that the framework instantiation for the C max cost function is up to 30x faster than DPccp for large clique queries.

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Publication Details

Journal
Proceedings of the ACM on Management of Data
Published
2024-12-18
DOI
https://doi.org/10.1145/3698809
Primary Topic
Data Management and Algorithms
Type
article
Field-Weighted Citation Impact
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article

DPconv: Super-Polynomially Faster Join Ordering

Mihail Stoian, Andreas Kipf
Proceedings of the ACM on Management of Data
Data Management and Algorithms
article

DPconv: Super-Polynomially Faster Join Ordering

Mihail Stoian, Andreas Kipf
article en

Abstract

We revisit the join ordering problem in query optimization. The standard exact algorithm, DPccp, has a worst-case running time of O(3 n ). This is prohibitively expensive for large queries, which are not that uncommon anymore. We develop a new algorithmic framework based on subset convolution. DPconv achieves a super-polynomial speedup over DPccp, breaking the O(3 n ) time-barrier for the first time. We show that the framework instantiation for the C max cost function is up to 30x faster than DPccp for large clique queries.

Proceedings of the ACM on Management of DataVol. 2(6)
Openalex Percentile: Top 74%
Data Management and Algorithms
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