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Estimating Join Selectivities using Bandwidth-Optimized Kernel Density Models
Summary: Bandwidth-optimized KDE for join selectivity; builds from join-result samples and combines base-table KDEs for single- and multi-join cardinalities. Outperforms sketching and sampling baselines on synthetic and real data with GPU-efficient evaluation.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 11519
- Venue
- VLDB
- Year
- 2017
- Pagerank
- 7.7974762e-05
- Overall Rank
- 2,969 | 79.35%
- DOI
-
-
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 26 of 26 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 758 |
Deep Unsupervised Cardinality Estimation |
2020 |
VLDB |
0.0001706608 |
| 910 |
NeuroCard: One Cardinality Estimator for All Tables |
2021 |
VLDB |
0.00015423056 |
| 1,638 |
Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation |
2022 |
VLDB |
0.00011049779 |
| 1,703 |
Are We Ready For Learned Cardinality Estimation? |
2021 |
VLDB |
0.00010836769 |
| 2,364 |
Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries |
2020 |
SIGMOD |
8.9554751e-05 |
| 2,762 |
FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation |
2021 |
VLDB |
8.1585394e-05 |
| 2,783 |
Flow-Loss: Learning Cardinality Estimates That Matter |
2021 |
VLDB |
8.1293383e-05 |
| 3,449 |
Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation |
2022 |
VLDB |
7.0824319e-05 |
| 3,499 |
Fauce: Fast and Accurate Deep Ensembles with Uncertainty for Cardinality Estimation |
2021 |
VLDB |
7.0376445e-05 |
| 3,778 |
A Learned Sketch for Subgraph Counting |
2021 |
SIGMOD |
6.7747398e-05 |
| 3,924 |
A Unified Deep Model of Learning from both Data and Queries for Cardinality Estimation |
2021 |
SIGMOD |
6.6271553e-05 |
| 3,990 |
FactorJoin: A New Cardinality Estimation Framework for Join Queries |
2023 |
SIGMOD |
6.5581983e-05 |
| 4,359 |
Astrid: Accurate Selectivity Estimation for String Predicates using Deep Learning |
2021 |
VLDB |
6.2569955e-05 |
| 4,434 |
Lightweight and Accurate Cardinality Estimation by Neural Network Gaussian Process |
2022 |
SIGMOD |
6.1929999e-05 |
| 4,543 |
FACE: A Normalizing Flow based Cardinality Estimator |
2022 |
VLDB |
6.1011198e-05 |
| 5,401 |
ALECE: An Attention-based Learned Cardinality Estimator for SPJ Queries on Dynamic Workloads |
2024 |
VLDB |
5.5285035e-05 |
| 5,880 |
COMPASS: Online Sketch-based Query Optimization for In-Memory Databases |
2021 |
SIGMOD |
5.2898074e-05 |
| 7,610 |
Learning to be a Statistician: Learned Estimator for Number of Distinct Values |
2022 |
VLDB |
4.6965039e-05 |
| 8,127 |
Robust Query Processing: Mission Possible |
2020 |
VLDB |
4.579056e-05 |
| 9,142 |
Design and Analysis of a Processing-in-DIMM Join Algorithm: A Case Study with UPMEM DIMMs |
2023 |
SIGMOD |
4.3853149e-05 |
| 9,691 |
Selectivity Estimation for Queries Containing Predicates over Set-Valued Attributes |
2023 |
SIGMOD |
4.3035354e-05 |
| 9,878 |
PRICE: A Pretrained Model for Cross-Database Cardinality Estimation |
2025 |
VLDB |
4.2656547e-05 |
| 9,945 |
SSCard: Substring Cardinality Estimation using Suffix Tree-Guided Learned FM-Index |
2026 |
SIGMOD |
4.2432653e-05 |
| 10,590 |
ACE: A Cardinality Estimator for Set-Valued Queries |
2025 |
VLDB |
4.1945683e-05 |
| 10,942 |
Sub-optimal Join Order Identification with L1-error |
2024 |
SIGMOD |
4.1945683e-05 |
| 10,981 |
Enabling Adaptive Sampling for Intra-Window Join: Simultaneously Optimizing Quantity and Quality |
2024 |
SIGMOD |
4.1945683e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 22 of 22 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 1 |
Access Path Selection in a Relational Database Management System |
1979 |
SIGMOD |
0.0040449103 |
| 18 |
On Random Sampling over Joins |
1999 |
SIGMOD |
0.00092385438 |
| 71 |
How Good Are Query Optimizers, Really? |
2016 |
VLDB |
0.00059038975 |
| 99 |
On the Propagation of Errors in the Size of Join Results |
1991 |
SIGMOD |
0.00050022914 |
| 182 |
LEO - DB2's LEarning Optimizer |
2001 |
VLDB |
0.00036962631 |
| 224 |
CORDS: Automatic Discovery of Correlations and Soft Functional Dependencies |
2004 |
SIGMOD |
0.00032746205 |
| 372 |
Selectivity Estimation using Probabilistic Models |
2001 |
SIGMOD |
0.00025354779 |
| 512 |
STHoles: A Multidimensional Workload-Aware Histogram |
2001 |
SIGMOD |
0.00021380733 |
| 549 |
Tracking Join and Self-Join Sizes in Limited Storage |
1999 |
PODS |
0.00020376603 |
| 553 |
Bifocal Sampling for Skew-Resistant Join Size Estimation |
1996 |
SIGMOD |
0.00020272061 |
| 629 |
Preventing Bad Plans by Bounding the Impact of Cardinality Estimation Errors |
2009 |
VLDB |
0.00018942366 |
| 650 |
Robust Query Processing through Progressive Optimization |
2004 |
SIGMOD |
0.00018659177 |
| 811 |
On the Relative Cost of Sampling for Join Selectivity Estimation |
1994 |
PODS |
0.00016425612 |
| 1,070 |
Analyzing Plan Diagrams of Database Query Optimizers |
2005 |
VLDB |
0.00014316791 |
| 1,105 |
Cardinality Estimation Done Right: Index-Based Join Sampling |
2017 |
CIDR |
0.00013990395 |
| 1,193 |
Join Size Estimation Subject to Filter Conditions |
2015 |
VLDB |
0.00013414989 |
| 1,287 |
Hardware-Oblivious Parallelism for In-Memory Column-Stores |
2013 |
VLDB |
0.00012820443 |
| 1,547 |
Lightweight Graphical Models for Selectivity Estimation Without Independence Assumptions |
2011 |
VLDB |
0.00011442359 |
| 2,165 |
Self-Tuning, GPU-Accelerated Kernel Density Models for Multidimensional Selectivity Estimation |
2015 |
SIGMOD |
9.389622e-05 |
| 3,013 |
Cardinality Estimation Using Sample Views with Quality Assurance |
2007 |
SIGMOD |
7.7137441e-05 |
| 3,305 |
Robust Query Processing in Co-Processor-accelerated Databases |
2016 |
SIGMOD |
7.2460965e-05 |
| 5,220 |
Similarity Join Size Estimation using Locality Sensitive Hashing |
2011 |
VLDB |
5.6216111e-05 |
Semantically Similar Papers
| Overall Rank |
Paper |
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Venue |
Pagerank |
| 1,981 |
Improved Selectivity Estimation by Combining Knowledge from Sampling and Synopses |
2018 |
VLDB |
9.8687545e-05 |
| 3,651 |
Conditional Selectivity for Statistics on Query Expressions |
2004 |
SIGMOD |
6.8768678e-05 |
| 2,142 |
Pessimistic Cardinality Estimation: Tighter Upper Bounds for Intermediate Join Cardinalities |
2019 |
SIGMOD |
9.4507296e-05 |
| 2,254 |
Two-Level Sampling for Join Size Estimation |
2017 |
SIGMOD |
9.1897043e-05 |
| 1,105 |
Cardinality Estimation Done Right: Index-Based Join Sampling |
2017 |
CIDR |
0.00013990395 |
| 3,990 |
FactorJoin: A New Cardinality Estimation Framework for Join Queries |
2023 |
SIGMOD |
6.5581983e-05 |
| 5,082 |
A Comparison of Selectivity Estimators for Range Queries on Metric Attributes |
1999 |
SIGMOD |
5.711623e-05 |
| 2,364 |
Deep Learning Models for Selectivity Estimation of Multi-Attribute Queries |
2020 |
SIGMOD |
8.9554751e-05 |
| 372 |
Selectivity Estimation using Probabilistic Models |
2001 |
SIGMOD |
0.00025354779 |
| 2,165 |
Self-Tuning, GPU-Accelerated Kernel Density Models for Multidimensional Selectivity Estimation |
2015 |
SIGMOD |
9.389622e-05 |