Fast Incremental Discovery of Pointwise Order Dependencies
Summary: Incremental discovery of pointwise order dependencies (PODs) under insertions. Uses novel indexing for Sigma and D to detect violations with log(|D|) cost, and a DeltaSigma refinement to update Sigma; experiments show up to orders-of-magnitude speedups over full recomputation. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Zijing Tan
- 2. Ai Ran
- 3. Shuai Ma
- 4. Sheng Qin
Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,698 | Workload-driven, Lazy Discovery of Data Dependencies for Query Optimization | 2022 | CIDR | 4.4604438e-05 |
| 8,836 | Fast Approximate Denial Constraint Discovery | 2023 | VLDB | 4.4350633e-05 |
| 9,748 | Efficient Differential Dependency Discovery | 2024 | VLDB | 4.2856385e-05 |
| 10,499 | Incremental Rule Discovery in Response to Parameter Updates | 2025 | SIGMOD | 4.1905499e-05 |
| 11,004 | Capturing More Associations by Referencing External Graphs | 2024 | VLDB | 4.1905499e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 16 of 16 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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