PGMJoins: Random Join Sampling with Graphical Models
Summary: PGMJoins uses probabilistic graphical models to derive provably uniform samples of join results (n-way key-joins, many-to-many, cyclic/acyclic). Introduces SP-MPA for efficient uniform sampling of the true joint distribution and optimizes graph structure and inference, achieving 2x–28x speedups on TPC-H, JOB, TPC-DS, and Twitter versus prior work. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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Incoming Citations (Sorted by Pagerank)
Showing 9 of 9 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,266 | Learned Cardinality Estimation: An In-depth Study | 2022 | SIGMOD | 7.3074684e-05 |
| 4,953 | On Join Sampling and the Hardness of Combinatorial Output-Sensitive Join Algorithms | 2023 | PODS | 5.8085795e-05 |
| 6,879 | Detect, Distill and Update: Learned DB Systems Facing Out of Distribution Data | 2023 | SIGMOD | 4.8971368e-05 |
| 7,920 | JoinBoost: Grow Trees Over Normalized Data Using Only SQL | 2023 | VLDB | 4.6163888e-05 |
| 9,852 | Machine Unlearning in Learned Databases: An Experimental Analysis | 2024 | SIGMOD | 4.2714575e-05 |
| 10,324 | Towards Efficient Random-Order Enumeration for Join Queries | 2026 | VLDB | 4.1945683e-05 |
| 10,481 | FAAQP: Fast and Accurate Approximate Query Processing based on Bitmap-augmented Sum-Product Network | 2025 | SIGMOD | 4.1945683e-05 |
| 10,981 | Enabling Adaptive Sampling for Intra-Window Join: Simultaneously Optimizing Quantity and Quality | 2024 | SIGMOD | 4.1945683e-05 |
| 11,285 | Approximate Queries over Concurrent Updates | 2023 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 18 of 18 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 372 | Selectivity Estimation using Probabilistic Models | 2001 | SIGMOD | 0.00025354779 |
| 3,048 | Fast, Randomized Join-Order Selection — Why Use Transformations? | 1994 | VLDB | 7.6543116e-05 |
| 10,254 | Secure Multi-Party Sampling over Joins | 2026 | VLDB | 4.1945683e-05 |
| 11,698 | Tighter Upper Bounds for Join Cardinality Estimates | 2018 | SIGMOD | 4.1945683e-05 |
| 2,254 | Two-Level Sampling for Join Size Estimation | 2017 | SIGMOD | 9.1897043e-05 |
| 5,104 | Guaranteeing the O~(AGM/OUT) Runtime for Uniform Sampling and Size Estimation over Joins | 2023 | PODS | 5.6946113e-05 |
| 18 | On Random Sampling over Joins | 1999 | SIGMOD | 0.00092385438 |
| 8,959 | Reservoir Sampling over Joins | 2024 | SIGMOD | 4.4206222e-05 |
| 1,369 | Random Sampling over Joins Revisited | 2018 | SIGMOD | 0.00012339777 |
| 11,453 | XLJoins | 2021 | SIGMOD | 4.1945683e-05 |