Tighter Upper Bounds for Join Cardinality Estimates
Summary: Tightens join cardinality upper bounds via data sketching and randomized hashing to help optimizers prune costly multiway plans. Extends to multiway cyclic joins; evaluates tightness on GooglePlus graphs, delivering degree-of-magnitude upper bounds and proposing a new join-statistic for plan selection. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Walter Cai
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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 |
|---|---|---|---|---|
| 71 | How Good Are Query Optimizers, Really? | 2016 | VLDB | 0.00059446482 |
| 680 | Towards a Robust Query Optimizer: A Principled and Practical Approach | 2005 | SIGMOD | 0.00018193263 |
| 1,104 | Cardinality Estimation Done Right: Index-Based Join Sampling | 2017 | CIDR | 0.0001398479 |
| 1,194 | Join Size Estimation Subject to Filter Conditions | 2015 | VLDB | 0.00013411666 |
| 1,268 | Proactive Re-Optimization | 2005 | SIGMOD | 0.00012914584 |
| 1,320 | Quickr: Lazily Approximating Complex AdHoc Queries in BigData Clusters | 2016 | SIGMOD | 0.00012606067 |
| 1,452 | What do Shannon-type Inequalities, Submodular Width, and Disjunctive Datalog have to do with one another? | 2017 | PODS | 0.00011922523 |
| 2,062 | PIQL: Success-Tolerant Query Processing in the Cloud | 2012 | VLDB | 9.654149e-05 |
| 2,254 | Two-Level Sampling for Join Size Estimation | 2017 | SIGMOD | 9.1871115e-05 |
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