The Case for Deep Query Optimisation
Summary: Proposes Deep Query Optimisation (DQO): decompose physical operators into fine-grained subcomponents to enumerate sub-plans offline/at query time, enabling deeper plan search than shallow QO. Defines MAVs and the Algorithmic View Selection Problem (AVSP), evaluates DQO on hash-based grouping, and sketches a research agenda. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jens Dittrich
- 2. Joris Nix
Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,525 | Database Technology for the Masses: Sub-Operators as First-Class Entities | 2021 | VLDB | 5.0223854e-05 |
| 6,863 | Declarative Sub-Operators for Universal Data Processing | 2023 | VLDB | 4.9003859e-05 |
| 8,053 | Building Advanced SQL Analytics From Low-Level Plan Operators | 2021 | SIGMOD | 4.5925468e-05 |
| 8,098 | Modularis: Modular Relational Analytics over Heterogeneous Distributed Platforms | 2021 | VLDB | 4.5824106e-05 |
| 8,123 | Maximus: A Modular Accelerated Query Engine for Data Analytics on Heterogeneous Systems | 2025 | SIGMOD | 4.5770901e-05 |
| 8,408 | The next 50 Years in Database Indexing or: The Case for Automatically Generated Index Structures | 2022 | VLDB | 4.5159669e-05 |
| 8,515 | UPLIFT: Parallelization Strategies for Feature Transformations in Machine Learning Workloads | 2022 | VLDB | 4.4901466e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 15 of 15 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,990 | AniPQO: Almost Non-intrusive Parametric Query Optimization for Nonlinear Cost Functions | 2003 | VLDB | 9.8491124e-05 |
| 1,201 | A General Framework for the Optimization of Object-Oriented Queries | 1992 | SIGMOD | 0.00013341955 |
| 2,652 | Multi-Objective Parametric Query Optimization | 2015 | VLDB | 8.3662031e-05 |
| 9,956 | How to Optimize SQL Queries? A Comparison Between Split, Holistic, and Hybrid Approaches | 2025 | VLDB | 4.2332427e-05 |
| 3,505 | Efficient and Provable Multi-Query Optimization | 2017 | PODS | 7.0304901e-05 |
| 6,826 | Depth Estimation for Ranking Query Optimization | 2007 | VLDB | 4.9090969e-05 |
| 11,352 | DeepO: A Learned Query Optimizer | 2022 | SIGMOD | 4.1905499e-05 |
| 454 | An Overview of Query Optimization in Relational Systems | 1998 | PODS | 0.00022796106 |
| 3,658 | Towards a Hands-Free Query Optimizer through Deep Learning | 2019 | CIDR | 6.8700949e-05 |
| 9,117 | Deep Query Optimization | 2019 | SIGMOD | 4.3885415e-05 |