Relational e-matching

Author:

Zhang Yihong1,Wang Yisu Remy1,Willsey Max1ORCID,Tatlock Zachary1

Affiliation:

1. University of Washington, USA

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.

Funder

National Science Foundation

Applications Driving Architectures (ADA) Research Center

Publisher

Association for Computing Machinery (ACM)

Subject

Safety, Risk, Reliability and Quality,Software

Reference28 articles.

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2. Andreas Amler. 2017. Evaluation of Worst-Case Optimal Join Algorithm. Master’s thesis. Andreas Amler. 2017. Evaluation of Worst-Case Optimal Join Algorithm. Master’s thesis.

3. Porting doop to Soufflé

4. Size Bounds and Query Plans for Relational Joins

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