Query-Driven Learning for Next Generation Predictive Modeling & Analytics
Summary: Query-driven learning to democratize analytics: learn lightweight ML models from query workloads that run off-cloud. Unique focus on local, resource-aware AQP for analytic aggregates (COUNT/MIN/MAX), enabling accurate approximations with low cost by adapting models on-the-fly. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Fotis Savva (University of Glasgow)
BibTeX Citation
@inproceedings{savva_sigmod19,
title = {{Query-Driven Learning for Next Generation Predictive Modeling \& Analytics}},
author = {Savva, Fotis},
series = {{SIGMOD} '19},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3299869.3300101},
url = {https://dl.acm.org/doi/10.1145/3299869.3300101},
year = {2019}
}Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|
Previous
Page 1 / 1
Next
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.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9 | Online Aggregation | 1997 | SIGMOD | 0.00077458002 |
| 461 | Query-based Workload Forecasting for Self-Driving Database Management Systems | 2018 | SIGMOD | 0.00018068441 |
| 819 | Quickr: Lazily Approximating Complex AdHoc Queries in BigData Clusters | 2016 | SIGMOD | 0.00013815639 |
| 1,198 | Overview of Data Exploration Techniques | 2015 | SIGMOD | 0.00011706307 |
| 1,827 | G-OLA: Generalized On-Line Aggregation for Interactive Analysis on Big Data | 2015 | SIGMOD | 9.6690206e-05 |
| 1,995 | Database Learning: Toward a Database that Becomes Smarter Every Time | 2017 | SIGMOD | 9.3403665e-05 |
| 5,359 | QUIET: Continuous Query-driven Index Tuning | 2003 | VLDB | 6.2492097e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 1,995 | Database Learning: Toward a Database that Becomes Smarter Every Time | 2017 | SIGMOD |
| 2 | 1,468 | Towards a Learning Optimizer for Shared Clouds | 2019 | VLDB |
| 3 | 3,482 | Towards Predicting Query Execution Time for Concurrent and Dynamic Database Workloads | 2013 | VLDB |
| 4 | 9,215 | Deep Query Optimization | 2019 | SIGMOD |
| 5 | 5,394 | Leveraging Query Logs and Machine Learning for Parametric Query Optimization | 2022 | VLDB |
| 6 | 295 | Accelerating Machine Learning Inference with Probabilistic Predicates | 2018 | SIGMOD |
| 7 | 1,799 | DBEst: Revisiting Approximate Query Processing Engines with Machine Learning Models | 2019 | SIGMOD |
| 8 | 5,132 | Facilitating SQL Query Composition and Analysis | 2020 | SIGMOD |
| 9 | 4,789 | Learned Approximate Query Processing: Make it Light, Accurate and Fast | 2021 | CIDR |
| 10 | 9,353 | On Efficient Approximate Queries over Machine Learning Models | 2023 | VLDB |