Yihong Zhang
Max Willsey
Zachary Tatlock
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A corrigendum was issued for this paper on March 31, 2022. You can download the corrigendum from the Supplemental Material section of this citation page.
Abstract
We present a new approach to e-matching based on relational join; in particular, we apply recent database query execution techniques to guarantee worst-case optimal run time. Compared to the conventional backtracking approach that always searches the e-graph "top down", our new relational e-matching approach can better exploit pattern structure by searching the e-graph according to an optimized query plan. We also establish the first data complexity result for e-matching, bounding run time as a function of the e-graph size and output size. We prototyped and evaluated our technique in the state-of-the-art egg e-graph framework. Compared to a conventional baseline, relational e-matching is simpler to implement and orders of magnitude faster in practice.
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Corrigendum to "Relational e-matching" by Zhang et al., Proceedings of the ACM on Programming Languages, Volume 6, Issue POPL (PACMPL 6:POPL).
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Index Terms
- Relational e-matching
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