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A Comparative Study and Component Analysis of Query Plan Representation Techniques in ML4DB Studies

Summary: Benchmarks 10 query-plan representations across cost estimation, index selection, and query optimization, testing cross-task transferability. Component analysis reveals error-metric-dependent effects and challenges assumptions about tree-model importance. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
h20bf28e1c791d4a5
Venue
VLDB
Year
2024
Pagerank
6.1123461e-05
Overall Rank
5,482 | 63.16%
DOI
10.14778/3636218.3636235
PDF
Download (CC BY-NC-ND 4.0)

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{zhao_vldb24,
        title = {{A Comparative Study and Component Analysis of Query Plan Representation Techniques in ML4DB Studies}},
        author = {Zhao, Yue and Li, Zhaodonghui and Cong, Gao},
        journal = {PVLDB},
        series = {{VLDB} '24},
        volume = {17},
        number = {4},
        pages = {823--835},
        doi = {10.14778/3636218.3636235},
        url = {https://doi.org/10.14778/3636218.3636235},
        year = {2024}
}

Incoming Citations (Sorted by Pagerank)

Showing 13 of 13 citing papers.

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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
15 How Good Are Query Optimizers, Really? 2016 VLDB 0.00061067652
85 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00035876108
88 Automated Selection of Materialized Views and Indexes for SQL Databases 2000 VLDB 0.00035340164
123 Schism: a Workload-Driven Approach to Database Replication and Partitioning 2010 VLDB 0.00030749898
144 Neo: A Learned Query Optimizer 2019 VLDB 0.00029090793
151 An Efficient, Cost-Driven Index Selection Tool for Microsoft SQL Server 1997 VLDB 0.00028664776
272 An Overview of Query Optimization in Relational Systems 1998 PODS 0.0002251422
361 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00020000855
378 AutoAdmin "What-if" Index Analysis Utility 1998 SIGMOD 0.00019541534
462 An End-to-End Learning-based Cost Estimator 2020 VLDB 0.00017836105
480 The Making of TPC-DS 2006 VLDB 0.00017615432
560 Plan-Structured Deep Neural Network Models for Query Performance Prediction 2019 VLDB 0.00016408613
981 Cardinality Estimation in DBMS: A Comprehensive Benchmark Evaluation 2022 VLDB 0.00012713454
1,065 Are We Ready For Learned Cardinality Estimation? 2021 VLDB 0.00012202293
1,280 AI Meets AI: Leveraging Query Executions to Improve Index Recommendations 2019 SIGMOD 0.00011224914
1,396 Magic mirror in my hand, which is the best in the land? An Experimental Evaluation of Index Selection Algorithms 2020 VLDB 0.00010788714
2,248 QueryFormer: A Tree Transformer Model for Query Plan Representation 2022 VLDB 8.7567205e-05
2,342 Learned Cardinality Estimation: An In-depth Study 2022 SIGMOD 8.6074783e-05
2,518 Learned Cardinality Estimation: A Design Space Exploration and A Comparative Evaluation 2022 VLDB 8.3532841e-05
3,563 Astrid: Accurate Selectivity Estimation for String Predicates using Deep Learning 2021 VLDB 7.2023194e-05
3,979 Efficient Deep Learning Pipelines for Accurate Cost Estimations Over Large Scale Query Workload 2021 SIGMOD 6.8791817e-05
4,536 One Model to Rule them All: Towards Zero-Shot Learning for Databases 2022 CIDR 6.552998e-05
5,188 Database Workload Characterization with Query Plan Encoders 2022 VLDB 6.2346845e-05
6,408 A Unified Transferable Model for ML-Enhanced DBMS 2022 CIDR 5.7921918e-05
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