Evaluating Rank Joins with Optimal Cost
Summary: Generalized analysis of rank-join under monotone scores and ranked access; shows HRJN may read inputs suboptimally and that computing optimal stopping is NP-hard in general. For bounded-query-complexity cases, gives an algorithm that infers tight benefit bounds and attains constant-factor optimal cost. (summarized by gpt-5-mini on Feb 09 2026)
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7 | Optimal Aggregation Algorithms for Middleware [Extended Abstract] | 2001 | PODS | 0.0015496097 |
| 552 | Supporting Incremental Join Queries on Ranked Inputs | 2001 | VLDB | 0.00020310903 |
| 674 | Supporting Top-k Join Queries in Relational Databases | 2003 | VLDB | 0.00018327585 |
| 1,262 | RankSQL: Query Algebra and Optimization for Relational Top-k Queries | 2005 | SIGMOD | 0.00012986539 |
| 6,829 | Depth Estimation for Ranking Query Optimization | 2007 | VLDB | 4.9136064e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,275 | Adopting Worst-Case Optimal Joins in Relational Database Systems | 2020 | VLDB | 9.1262202e-05 |
| 12,191 | Efficient Rank Join with Aggregation Constraints | 2011 | VLDB | 4.1945683e-05 |
| 8,061 | Efficient Computation of Quantiles over Joins | 2023 | PODS | 4.5943269e-05 |
| 674 | Supporting Top-k Join Queries in Relational Databases | 2003 | VLDB | 0.00018327585 |
| 5,855 | Optimal Join Algorithms Meet Top-k | 2020 | SIGMOD | 5.3006096e-05 |
| 552 | Supporting Incremental Join Queries on Ranked Inputs | 2001 | VLDB | 0.00020310903 |
| 7,692 | Processing Top-k Join Queries | 2010 | VLDB | 4.6761366e-05 |
| 2,393 | Rank-aware Query Optimization | 2004 | SIGMOD | 8.9016542e-05 |
| 5,373 | Robust and Efficient Algorithms for Rank Join Evaluation | 2009 | SIGMOD | 5.5425231e-05 |
| 4,069 | Proximity Rank Join | 2010 | VLDB | 6.4789031e-05 |