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JoinBoost: Grow Trees Over Normalized Data Using Only SQL

Summary: JoinBoost rewrites tree training over normalized join graphs into portable pure SQL, avoiding denormalization, materialization, and data export. Factorized gradient boosting enables efficient residual updates, delivering competitive or superior performance and scalability. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
hc1f40661e942518d
Venue
VLDB
Year
2023
Pagerank
5.7503043e-05
Overall Rank
6,550 | 55.97%
DOI
10.14778/3611479.3611509

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{huang_vldb23,
        title = {{JoinBoost: Grow Trees Over Normalized Data Using Only SQL}},
        author = {Huang, Zezhou and Sen, Rathijit and Liu, Jiaxiang and Wu, Eugene},
        journal = {PVLDB},
        series = {{VLDB} '23},
        volume = {16},
        number = {11},
        pages = {3071--3084},
        doi = {10.14778/3611479.3611509},
        url = {https://doi.org/10.14778/3611479.3611509},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 10 of 10 citing papers.

Rank Citing Paper Year Venue Pagerank
6,229 The Fast and the Private: Task-based Dataset Search 2024 CIDR 5.8444773e-05
6,742 Mitigating the Impedance Mismatch between Prediction Query Execution and Database Engine 2025 SIGMOD 5.6910432e-05
7,978 Biathlon: Harnessing Model Resilience for Accelerating ML Inference Pipelines 2024 VLDB 5.4136835e-05
10,181 In-Database Data Imputation 2024 SIGMOD 5.0653015e-05
10,446 Eliminating Redundant Feature Tests in Decision Tree and Random Forest Inference on SQL Predicates 2026 SIGMOD 4.9793485e-05
10,448 EncoderForge: Generating Efficient SQL for Encoders in Machine Learning Inference Pipelines 2026 SIGMOD 4.9793485e-05
10,452 Factorized and Vectorized Execution: Optimizing Analytical and Semantic Queries over Relations 2026 SIGMOD 4.9793485e-05
10,653 InferF: Declarative Factorization of AI/ML Inferences over Joins 2026 SIGMOD 4.9793485e-05
10,832 ReSequel: Robust LLM-assisted Query Rewriting and Optimization using Templatization and Sampling 2026 VLDB 4.9793485e-05
11,243 Quantum Data Management in the NISQ Era 2025 VLDB 4.9793485e-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.

Rank Cited Paper Year Venue Pagerank
17 Provenance Semirings 2007 PODS 0.00059752575
71 DuckDB: an Embeddable Analytical Database 2019 SIGMOD 0.00037720227
105 The MADlib Analytics Library or MAD Skills, the SQL 2012 VLDB 0.00033638251
138 Join Synopses for Approximate Query Answering 1999 SIGMOD 0.00029627449
163 DB2 with BLU Acceleration: So Much More than Just a Column Store 2013 VLDB 0.0002749118
208 EmptyHeaded: A Relational Engine for Graph Processing 2016 SIGMOD 0.00024884544
228 Fast Serializable Multi-Version Concurrency Control for Main-Memory Database Systems 2015 SIGMOD 0.00023920439
357 FAQ: Questions Asked Frequently 2016 PODS 0.00020020639
415 SystemML: Declarative Machine Learning on Spark 2016 VLDB 0.0001865959
432 Shark: SQL and Rich Analytics at Scale 2013 SIGMOD 0.00018339357
503 Towards a Unified Architecture for in-RDBMS Analytics 2012 SIGMOD 0.00017202276
521 Learning Linear Regression Models over Factorized Joins 2016 SIGMOD 0.00016929744
537 MLbase: A Distributed Machine-learning System 2013 CIDR 0.00016768109
795 Random Sampling over Joins Revisited 2018 SIGMOD 0.00013938779
1,570 AJAR: Aggregations and Joins over Annotated Relations 2016 PODS 0.0001020855
2,299 On Functional Aggregate Queries with Additive Inequalities 2019 PODS 8.6727773e-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
2,663 A Layered Aggregate Engine for Analytics Workloads 2019 SIGMOD 8.1581558e-05
3,112 Incremental View Maintenance with Triple Lock Factorization Benefits 2018 SIGMOD 7.6357579e-05
3,524 MLog: Towards Declarative In-Database Machine Learning 2017 VLDB 7.2337006e-05
3,972 TCUDB: Accelerating Database with Tensor Processors 2022 SIGMOD 6.8881464e-05
5,657 PGMJoins: Random Join Sampling with Graphical Models 2021 SIGMOD 6.0488437e-05
10,020 Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem 2022 VLDB 5.0943606e-05
10,021 Distributed Numerical and Machine Learning Computations via Two-Phase Execution of Aggregated Join Trees 2021 VLDB 5.0943545e-05
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