Containerized Execution of UDFs: An Experimental Evaluation
Summary: First study spanning containerized UDF life cycle, bottlenecks, and cross-engine extensibility for arbitrary-language UDFs. Binary-based communication cuts overhead (>2.4x vs text); Arrow Flight near-native speeds; start-up times 0.07–7s. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Karla Saur (Microsoft)
- 2. Tara Mirmira (University of California San Diego)
- 3. Konstantinos Karanasos (Meta)
- 4. Jesús Camacho-Rodríguez (Microsoft)
BibTeX Citation
@article{saur_vldb22,
title = {{Containerized Execution of UDFs: An Experimental Evaluation}},
author = {Saur, Karla and Mirmira, Tara and Karanasos, Konstantinos and Camacho-Rodríguez, Jesús},
journal = {PVLDB},
series = {{VLDB} '22},
volume = {15},
number = {11},
pages = {3158--3171},
doi = {10.14778/3551793.3551860},
url = {https://doi.org/10.14778/3551793.3551860},
year = {2022}
}
Incoming Citations (Sorted by Pagerank)
Showing 5 of 5 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 7,978 | Biathlon: Harnessing Model Resilience for Accelerating ML Inference Pipelines | 2024 | VLDB | 5.4136835e-05 |
| 7,996 | Databricks Lakeguard: Supporting Fine-grained Access Control and Multi-user Capabilities for Apache Spark Workloads | 2025 | SIGMOD | 5.4108483e-05 |
| 8,352 | Towards Building Autonomous Data Services on Azure | 2023 | SIGMOD | 5.3488341e-05 |
| 10,250 | AnyBlox: A Framework for Self-Decoding Datasets | 2025 | VLDB | 5.051964e-05 |
| 10,932 | IMLane: Composable Framework for Efficient AI Function Execution in Database Engine | 2026 | VLDB | 4.9793485e-05 |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 12 of 12 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 | 9,588 | The Key to Effective UDF Optimization: Before Inlining, First Perform Outlining | 2025 | VLDB |
| 2 | 6,212 | YeSQL: "You extend SQL" with Rich and Highly Performant User-Defined Functions in Relational Databases | 2022 | VLDB |
| 3 | 1,444 | An Architecture for Compiling UDF-centric Workflows | 2015 | VLDB |
| 4 | 12,800 | Fast and Dynamic OLAP Exploration Using UDFs | 2009 | SIGMOD |
| 5 | 6,400 | Functional-Style SQL UDFs With a Capital 'F' | 2020 | SIGMOD |
| 6 | 6,085 | Dear User-Defined Functions, Inlining isn't working out so great for us. Let's try batching to make our relationship work. Sincerely, SQL | 2024 | CIDR |
| 7 | 5,719 | Accelerating Python UDFs in Vectorized Query Execution | 2022 | CIDR |
| 8 | 11,168 | UDFBench: A Tool for Benchmarking UDF Queries on SQL Engines | 2025 | SIGMOD |
| 9 | 7,983 | Efficient Execution of User-Defined Functions in SQL Queries | 2023 | VLDB |
| 10 | 9,694 | The UDFBench Benchmark for General-purpose UDF Queries | 2025 | VLDB |