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 |
|---|---|---|---|---|
| 8 | Optimal Aggregation Algorithms for Middleware [Extended Abstract] | 2001 | PODS | 0.0015436578 |
| 551 | Supporting Incremental Join Queries on Ranked Inputs | 2001 | VLDB | 0.00020310856 |
| 673 | Supporting Top-k Join Queries in Relational Databases | 2003 | VLDB | 0.00018325667 |
| 1,207 | RankSQL: Query Algebra and Optimization for Relational Top-k Queries | 2005 | SIGMOD | 0.0001327437 |
| 6,826 | Depth Estimation for Ranking Query Optimization | 2007 | VLDB | 4.9090969e-05 |
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,281 | Adopting Worst-Case Optimal Joins in Relational Database Systems | 2020 | VLDB | 9.122455e-05 |
| 12,199 | Efficient Rank Join with Aggregation Constraints | 2011 | VLDB | 4.1905499e-05 |
| 8,065 | Efficient Computation of Quantiles over Joins | 2023 | PODS | 4.5899218e-05 |
| 673 | Supporting Top-k Join Queries in Relational Databases | 2003 | VLDB | 0.00018325667 |
| 5,845 | Optimal Join Algorithms Meet Top-k | 2020 | SIGMOD | 5.3057391e-05 |
| 551 | Supporting Incremental Join Queries on Ranked Inputs | 2001 | VLDB | 0.00020310856 |
| 7,660 | Processing Top-k Join Queries | 2010 | VLDB | 4.6814547e-05 |
| 2,249 | Rank-aware Query Optimization | 2004 | SIGMOD | 9.1956569e-05 |
| 5,379 | Robust and Efficient Algorithms for Rank Join Evaluation | 2009 | SIGMOD | 5.5375923e-05 |
| 4,072 | Proximity Rank Join | 2010 | VLDB | 6.4726748e-05 |