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: 5.7287508e-05
Overall Rank: 6,562 | 56.02%
DOI: 10.14778/3611479.3611509
PDF: Download (CC BY-NC-ND 4.0)

Incoming Non-self Citations Over Time

Authors

1. Zezhou Huang (Columbia University)
2. Rathijit Sen (Microsoft)
3. Jiaxiang Liu (Columbia University)
4. Eugene Wu (Columbia University)

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
6,242	The Fast and the Private: Task-based Dataset Search	2024	CIDR	5.8223943e-05
6,765	Mitigating the Impedance Mismatch between Prediction Query Execution and Database Engine	2025	SIGMOD	5.6695399e-05
7,950	Biathlon: Harnessing Model Resilience for Accelerating ML Inference Pipelines	2024	VLDB	5.402957e-05
10,218	In-Database Data Imputation	2024	SIGMOD	5.0461625e-05
10,523	Eliminating Redundant Feature Tests in Decision Tree and Random Forest Inference on SQL Predicates	2026	SIGMOD	4.9605343e-05
10,525	EncoderForge: Generating Efficient SQL for Encoders in Machine Learning Inference Pipelines	2026	SIGMOD	4.9605343e-05
10,529	Factorized and Vectorized Execution: Optimizing Analytical and Semantic Queries over Relations	2026	SIGMOD	4.9605343e-05
10,725	InferF: Declarative Factorization of AI/ML Inferences over Joins	2026	SIGMOD	4.9605343e-05
10,903	ReSequel: Robust LLM-assisted Query Rewriting and Optimization using Templatization and Sampling	2026	VLDB	4.9605343e-05
11,307	Quantum Data Management in the NISQ Era	2025	VLDB	4.9605343e-05

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	0.00059660827
71	DuckDB: an Embeddable Analytical Database	2019	SIGMOD	0.00037688945
105	The MADlib Analytics Library or MAD Skills, the SQL	2012	VLDB	0.00033605348
138	Join Synopses for Approximate Query Answering	1999	SIGMOD	0.00029532435
161	DB2 with BLU Acceleration: So Much More than Just a Column Store	2013	VLDB	0.00027629724
208	EmptyHeaded: A Relational Engine for Graph Processing	2016	SIGMOD	0.00024929198
228	Fast Serializable Multi-Version Concurrency Control for Main-Memory Database Systems	2015	SIGMOD	0.00023872855
357	FAQ: Questions Asked Frequently	2016	PODS	0.00020048899
415	SystemML: Declarative Machine Learning on Spark	2016	VLDB	0.00018619173
436	Shark: SQL and Rich Analytics at Scale	2013	SIGMOD	0.00018274105
506	Towards a Unified Architecture for in-RDBMS Analytics	2012	SIGMOD	0.00017158546
522	Learning Linear Regression Models over Factorized Joins	2016	SIGMOD	0.00016893112
538	MLbase: A Distributed Machine-learning System	2013	CIDR	0.00016725463
793	Random Sampling over Joins Revisited	2018	SIGMOD	0.00013903938
1,568	AJAR: Aggregations and Joins over Annotated Relations	2016	PODS	0.00010178045
2,316	On Functional Aggregate Queries with Additive Inequalities	2019	PODS	8.6404062e-05
2,407	Declarative Recursive Computation on an RDBMS or, Why You Should Use a Database For Distributed Machine Learning	2019	VLDB	8.4928721e-05
2,673	A Layered Aggregate Engine for Analytics Workloads	2019	SIGMOD	8.1276375e-05
3,122	Incremental View Maintenance with Triple Lock Factorization Benefits	2018	SIGMOD	7.6091671e-05
3,520	MLog: Towards Declarative In-Database Machine Learning	2017	VLDB	7.2180592e-05
3,982	TCUDB: Accelerating Database with Tensor Processors	2022	SIGMOD	6.8663329e-05
5,671	PGMJoins: Random Join Sampling with Graphical Models	2021	SIGMOD	6.026372e-05
10,063	Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem	2022	VLDB	5.0751118e-05
10,064	Distributed Numerical and Machine Learning Computations via Two-Phase Execution of Aggregated Join Trees	2021	VLDB	5.0751093e-05

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#	Overall Rank	Paper	Year	Venue
1	5,032	Reducing Multidatabase Query Response Time By Tree Balancing	1995	SIGMOD
2	9,681	Are Joins over LSM-trees Ready? Take RocksDB as an Example	2025	VLDB
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9	10,523	Eliminating Redundant Feature Tests in Decision Tree and Random Forest Inference on SQL Predicates	2026	SIGMOD
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