Lightning Fast and Space Efficient Inequality Joins
Summary: Introduces fast inequality join algorithms using sorted arrays, permutation encodings of cross-array positions, and space-efficient bit-arrays with Bloom-filter-like indices. Centralized PostgreSQL and distributed Spark SQL implementations outperform traditional methods, showing scalable, orders-of-magnitude speedups. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zuhair Khayyat
- 2. William Lucia
- 3. Meghna Singh
- 4. Mourad Ouzzani
- 5. Paolo Papotti
- 6. Jorge-Arnulfo Quiané-Ruiz
- 7. Nan Tang
- 8. Panos Kalnis
Incoming Citations (Sorted by Pagerank)
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|---|---|---|---|---|
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| 9,838 | Efficiently Joining Large Relations on Multi-GPU Systems | 2025 | VLDB | 4.2740344e-05 |
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| 3,515 | Scalable Computation of Acyclic Joins (Extended Abstract) | 2006 | PODS | 7.0220813e-05 |
| 5,511 | On Producing Join Results Early | 2003 | PODS | 5.4699346e-05 |
| 2,275 | Adopting Worst-Case Optimal Joins in Relational Database Systems | 2020 | VLDB | 9.1262202e-05 |
| 3,898 | Efficient Join Algorithms For Large Database Tables in a Multi-GPU Environment | 2021 | VLDB | 6.6551268e-05 |
| 7,250 | A Scalable and Generic Approach to Range Joins | 2022 | VLDB | 4.78908e-05 |
| 11,358 | Scaling Equi-Joins | 2022 | SIGMOD | 4.1945683e-05 |
| 11,890 | Let's Rethink Join Optimization in Distributed Systems | 2015 | CIDR | 4.1945683e-05 |