Towards Efficient Random-Order Enumeration for Join Queries
Summary: Efficient uniformly random-order enumeration for join queries, including cyclic ones, with worst-case guarantees and no query-specific preprocessing. Achieves near-optimal expected delay via AGM-bounded analysis, plug-in adaptation to common indexes, plus practical speed/memory optimizations. (summarized by gpt-5.4-mini on Apr 12 2026)
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Authors
- 1. Pengyu Chen
- 2. Zizheng Guo
- 3. Jianwei Yang
- 4. Dongjing Miao
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 503 | Worst-case Optimal Join Algorithms | 2012 | PODS | 0.00021517145 |
| 1,372 | Random Sampling over Joins Revisited | 2018 | SIGMOD | 0.0001233325 |
| 1,556 | Beyond Worst-case Analysis for Joins with Minesweeper | 2014 | PODS | 0.00011383141 |
| 2,298 | Joins via Geometric Resolutions: Worst-case and Beyond | 2015 | PODS | 9.0746479e-05 |
| 3,374 | On the Enumeration Complexity of Unions of Conjunctive Queries | 2019 | PODS | 7.1631303e-05 |
| 3,386 | Answering (Unions of) Conjunctive Queries using Random Access and Random-Order Enumeration | 2020 | PODS | 7.151562e-05 |
| 4,926 | On Join Sampling and the Hardness of Combinatorial Output-Sensitive Join Algorithms | 2023 | PODS | 5.8184457e-05 |
| 5,085 | Guaranteeing the O~(AGM/OUT) Runtime for Uniform Sampling and Size Estimation over Joins | 2023 | PODS | 5.7040225e-05 |
| 5,952 | PGMJoins: Random Join Sampling with Graphical Models | 2021 | SIGMOD | 5.2547498e-05 |
| 6,345 | A Relational Framework for Classifier Engineering | 2017 | PODS | 5.0970607e-05 |
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