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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)

Paper ID
h6421feb9d6ebb633
Venue
VLDB
Year
2021
Pagerank
5.0943545e-05
Overall Rank
10,021 | 32.63%
DOI
10.14778/3450980.3450991

Incoming Non-self Citations Over Time

Authors

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
6,458 In-Database Machine Learning with CorgiPile: Stochastic Gradient Descent without Full Data Shuffle 2022 SIGMOD 5.7773842e-05
6,550 JoinBoost: Grow Trees Over Normalized Data Using Only SQL 2023 VLDB 5.7503043e-05
10,699 Automated Tensor-Relational Decomposition for Large-Scale Sparse Tensor Computation 2026 VLDB 4.9793485e-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.

Rank Cited Paper Year Venue Pagerank
1 Access Path Selection in a Relational Database Management System 1979 SIGMOD 0.0023947656
5 Optimal Aggregation Algorithms for Middleware [Extended Abstract] 2001 PODS 0.0010679641
135 Ripple Joins for Online Aggregation 1999 SIGMOD 0.00029866033
272 An Overview of Query Optimization in Relational Systems 1998 PODS 0.00022509573
337 Trio: A System for Data, Uncertainty, and Lineage 2006 VLDB 0.00020621631
405 Distributed Query Processing In A Relational Data Base System 1978 SIGMOD 0.00019065801
844 Exploiting Inter-Operation Parallelism in XPRS 1992 SIGMOD 0.00013533208
1,746 SMOKE: Fine-grained Lineage at Interactive Speed 2018 VLDB 9.7341914e-05
1,995 Track Join: Distributed Joins with Minimal Network Traffic 2014 SIGMOD 9.2169073e-05
2,400 Declarative Recursive Computation on an RDBMS or, Why You Should Use a Database For Distributed Machine Learning 2019 VLDB 8.5213814e-05
2,830 DB4ML – An In-Memory Database Kernel with Machine Learning Support 2020 SIGMOD 7.9619979e-05
2,975 In-Database Learning with Sparse Tensors 2018 PODS 7.7907759e-05
3,524 MLog: Towards Declarative In-Database Machine Learning 2017 VLDB 7.2337006e-05
3,865 Optimizing Nested Queries with Parameter Sort Orders 2005 VLDB 6.962283e-05
4,069 Dynamically Optimizing Queries over Large Scale Data Platforms 2014 SIGMOD 6.821366e-05
5,289 Tensor Relational Algebra for Distributed Machine Learning System Design 2021 VLDB 6.1940481e-05
6,758 DistME: A Fast and Elastic Distributed Matrix Computation Engine using GPUs 2019 SIGMOD 5.6890461e-05
9,215 Chasing Similarity: Distribution-aware Aggregation Scheduling 2019 VLDB 5.2056826e-05
9,748 PlinyCompute: A Platform for High-Performance, Distributed, Data-Intensive Tool Development 2018 SIGMOD 5.1349531e-05
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