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CoPhy: A Scalable, Portable, and Interactive Index Advisor for Large Workloads

Summary: CoPhy offers scalable, portable, interactive index tuning for large workloads. Reveals a structured solution space and exploits linear optimization for efficient search, delivering up to 10x gains over prior methods. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10456
Venue
VLDB
Year
2011
Pagerank
9.5040429e-05
Overall Rank
1,904 | 86.94%
DOI
10.14778/1985796.1985798

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{dash_vldb11,
        title = {{CoPhy: A Scalable, Portable, and Interactive Index Advisor for Large Workloads}},
        author = {Dash, Debabrata and Polyzotis, Neoklis and Ailamaki, Anastasia},
        journal = {PVLDB},
        series = {{VLDB} '11},
        volume = {4},
        number = {6},
        pages = {362--373},
        doi = {10.14778/1985796.1985798},
        url = {https://doi.org/10.14778/1985796.1985798},
        year = {2011}
}

Incoming Citations (Sorted by Pagerank)

Showing 26 of 26 citing papers.

Rank Citing Paper Year Venue Pagerank
1,070 NoDB: Efficient Query Execution on Raw Data Files 2012 SIGMOD 0.0001232307
1,279 AI Meets AI: Leveraging Query Executions to Improve Index Recommendations 2019 SIGMOD 0.00011361878
1,481 Magic mirror in my hand, which is the best in the land? An Experimental Evaluation of Index Selection Algorithms 2020 VLDB 0.00010644613
3,998 Deploying a Steered Query Optimizer in Production at Microsoft 2022 SIGMOD 6.9676473e-05
4,643 Learned Index Benefits: Machine Learning Based Index Performance Estimation 2022 VLDB 6.5907466e-05
4,968 Towards Scalable Hybrid Stores: Constraint-Based Rewriting to the Rescue 2019 SIGMOD 6.4206525e-05
5,091 Budget-aware Index Tuning with Reinforcement Learning 2022 SIGMOD 6.3669569e-05
5,156 Only Aggressive Elephants are Fast Elephants 2012 VLDB 6.3410921e-05
5,558 HMAB: Self-Driving Hierarchy of Bandits for Integrated Physical Database Design Tuning 2023 VLDB 6.1749098e-05
5,766 Endure: A Robust Tuning Paradigm for LSM Trees Under Workload Uncertainty 2022 VLDB 6.094771e-05
6,327 Breaking It Down: An In-depth Study of Index Advisors 2024 VLDB 5.9124005e-05
6,462 PilotScope: Steering Databases with Machine Learning Drivers 2024 VLDB 5.8717744e-05
7,076 Refactoring Index Tuning Process with Benefit Estimation 2024 VLDB 5.7098893e-05
7,428 Invisible Glue: Scalable Self-Tuning Multi-Stores 2015 CIDR 5.6205394e-05
8,410 Robust and Budget-Constrained Encoding Configurations for In-Memory Database Systems 2022 VLDB 5.4309397e-05
8,703 Divergent Physical Design Tuning for Replicated Databases 2012 SIGMOD 5.3813751e-05
9,106 AirIndex: Versatile Index Tuning Through Data and Storage 2023 SIGMOD 5.3226167e-05
9,615 Wii: Dynamic Budget Reallocation In Index Tuning 2024 SIGMOD 5.2436464e-05
9,775 Twisted Twin: A Collaborative and Competitive Memory Management Approach in HTAP Systems 2025 VLDB 5.2209769e-05
9,966 Generating Application-Specific Data Layouts for In-memory Databases 2019 VLDB 5.1870939e-05
10,413 Understanding and Detecting Query Performance Regression in Practical Index Tuning: [Experiments & Analysis] 2026 SIGMOD 5.093636e-05
10,815 Esc: An Early-Stopping Checker for Budget-aware Index Tuning 2025 VLDB 5.093636e-05
11,277 Index Advisors on Quantum Platforms 2024 VLDB 5.093636e-05
11,306 Looking Deeply into the Magic Mirror: An Interactive Analysis of Database Index Selection Approaches 2024 VLDB 5.093636e-05
11,613 Budget-Conscious Fine-Grained Configuration Optimization for Spatio-Temporal Applications 2022 VLDB 5.093636e-05
11,739 View-Driven Optimization of Database-Backed Web Applications 2020 CIDR 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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