Distributed Numerical and Machine Learning Computations via Two-Phase Execution of Aggregated Join Trees
Summary: Two-phase execution for numerical/ML workloads expressed as aggregated join trees (joins then aggregation). Pilot run collects lineage to enable record-level planning before execution; experiments show this relational two-phase approach as an effective platform for distributed ML. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Dimitrije Jankov (Rice University)
- 2. Binhang Yuan (Rice University)
- 3. Shangyu Luo (Rice University)
- 4. Chris Jermaine (Rice University)
BibTeX Citation
@article{jankov_vldb21,
title = {{Distributed Numerical and Machine Learning Computations via Two-Phase Execution of Aggregated Join Trees}},
author = {Jankov, Dimitrije and Yuan, Binhang and Luo, Shangyu and Jermaine, Chris},
journal = {PVLDB},
series = {{VLDB} '21},
volume = {14},
number = {7},
pages = {1228--1240},
doi = {10.14778/3450980.3450991},
url = {https://doi.org/10.14778/3450980.3450991},
year = {2021}
}
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,339 | In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle | 2022 | SIGMOD | 5.907165e-05 |
| 6,585 | JoinBoost: Grow Trees Over Normalized Data Using Only SQL | 2023 | VLDB | 5.8350362e-05 |
| 10,514 | Automated Tensor-Relational Decomposition for Large-Scale Sparse Tensor Computation | 2026 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 19 of 19 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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