Aero: Adaptive Query Processing of ML Queries
Summary: Aero uses adaptive query processing for ML queries, coping with opaque UDF statistics and data-dependent plan choices. Dynamic predicate evaluation order, runtime UDF routing, and resource reallocation yield up to 6.4x speedups with no accuracy loss. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Gaurav Tarlok Kakkar (Georgia Institute of Technology)
- 2. Jiashen Cao (Georgia Institute of Technology)
- 3. Aubhro Sengupta (Georgia Institute of Technology)
- 4. Joy Arulraj (Georgia Institute of Technology)
- 5. Hyesoon Kim (Georgia Institute of Technology)
BibTeX Citation
@inproceedings{kakkar_sigmod25,
title = {{Aero: Adaptive Query Processing of ML Queries}},
author = {Kakkar, Gaurav Tarlok and Cao, Jiashen and Sengupta, Aubhro and Arulraj, Joy and Kim, Hyesoon},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3725408},
url = {https://dl.acm.org/doi/10.1145/3725408},
year = {2025}
}Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,464 | Self-Enhancing Video Data Management System for Compositional Events with Large Language Models | 2025 | SIGMOD | 5.2634238e-05 |
| 9,917 | The UDFBench Benchmark for General-purpose UDF Queries | 2025 | VLDB | 5.1955087e-05 |
| 10,130 | Does A Fish Need a Bicycle? The Case for On-Chip NPUs in DBMS | 2026 | CIDR | 5.093636e-05 |
| 10,623 | KEN: An Execution Engine for Unstructured Database Systems | 2026 | VLDB | 5.093636e-05 |
| 10,917 | Deja Vu: Efficient Video-Language Query Engine with Learning-based Inter-Frame Computation Reuse | 2025 | VLDB | 5.093636e-05 |
Previous
Page 1 / 1
Next
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.
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 9,882 | Demonstration of Accelerating Machine Learning Inference Queries with Correlative Proxy Models | 2022 | VLDB |
| 2 | 2,420 | Lero: A Learning-to-Rank Query Optimizer | 2023 | VLDB |
| 3 | 2,293 | Extending Relational Query Processing with ML Inference | 2020 | CIDR |
| 4 | 10,185 | A Backend-Agnostic Compiler for Approximate Query Processing with Probabilistic Tensor Algebra | 2026 | SIGMOD |
| 5 | 5,132 | Facilitating SQL Query Composition and Analysis | 2020 | SIGMOD |
| 6 | 2,865 | End-to-end Optimization of Machine Learning Prediction Queries | 2022 | SIGMOD |
| 7 | 10,886 | AQETuner: Reliable Query-level Configuration Tuning for Analytical Query Engines | 2025 | VLDB |
| 8 | 11,845 | Query-Driven Learning for Next Generation Predictive Modeling & Analytics | 2019 | SIGMOD |
| 9 | 295 | Accelerating Machine Learning Inference with Probabilistic Predicates | 2018 | SIGMOD |
| 10 | 4,789 | Learned Approximate Query Processing: Make it Light, Accurate and Fast | 2021 | CIDR |