Convolution and Cross-Correlation of Count Sketches Enables Fast Cardinality Estimation of Multi-Join Queries
Summary: Combines Count Sketch with convolution/cross-correlation to support AMS-style cardinality estimation for complex multi-way equi-joins, finally getting fast updates for multi-join sketches. Unbiased estimator with AMS-level error guarantees; orders-of-magnitude faster maintenance, often better accuracy. (summarized by gpt-5.4-mini on May 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Mike Heddes (University of California Irvine)
- 2. Igor Nunes (University of California Irvine)
- 3. Tony Givargis (University of California Irvine)
- 4. Alex Nicolau (University of California Irvine)
BibTeX Citation
@inproceedings{heddes_sigmod24,
title = {{Convolution and Cross-Correlation of Count Sketches Enables Fast Cardinality Estimation of Multi-Join Queries}},
author = {Heddes, Mike and Nunes, Igor and Givargis, Tony and Nicolau, Alex},
series = {{SIGMOD} '24},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3654932},
url = {https://dl.acm.org/doi/10.1145/3654932},
year = {2024}
}Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,958 | A Practical Theory of Generalization in Selectivity Learning | 2025 | VLDB | 5.1879626e-05 |
| 9,971 | Athena: An Effective Learning-based Framework for Query Optimizer Performance Improvement | 2025 | SIGMOD | 5.1845938e-05 |
| 10,295 | Sublime: Sublinear Error & Space for Unbounded Skewed Streams | 2026 | SIGMOD | 5.093636e-05 |
| 10,438 | CorrBound: Cardinality Estimation Accounting for Inter- and Intra-relation Correlations | 2026 | SIGMOD | 5.093636e-05 |
| 10,875 | Data-Agnostic Cardinality Learning from Imperfect Workloads | 2025 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 24 of 24 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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