Back to papers
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)
- Paper ID
- 12797
- Venue
- VLDB
- Year
- 2022
- Pagerank
- 5.4866534e-05
- Overall Rank
- 5,476 | 61.91%
- DOI
-
10.14778/3551793.3551860
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
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.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 746 |
Delta Lake: High-Performance ACID Table Storage over Cloud Object Stores |
2020 |
VLDB |
0.00017326979 |
| 1,108 |
Froid: Optimization of Imperative Programs in a Relational Database |
2018 |
VLDB |
0.00013984276 |
| 1,632 |
Cloudburst: Stateful Functions-as-a-Service |
2020 |
VLDB |
0.0001107213 |
| 1,873 |
An Architecture for Compiling UDF-centric Workflows |
2015 |
VLDB |
0.00010253002 |
| 1,882 |
Tuplex: Data Science in Python at Native Code Speed |
2021 |
SIGMOD |
0.0001021625 |
| 2,359 |
Data Market Platforms: Trading Data Assets to Solve Data Problems |
2020 |
VLDB |
8.9607667e-05 |
| 2,611 |
Opening the Black Boxes in Data Flow Optimization |
2012 |
VLDB |
8.4536967e-05 |
| 2,804 |
Extending Relational Query Processing with ML Inference |
2020 |
CIDR |
8.0935487e-05 |
| 3,407 |
End-to-end Optimization of Machine Learning Prediction Queries |
2022 |
SIGMOD |
7.1295646e-05 |
| 4,813 |
Putting Pandas in a Box |
2021 |
CIDR |
5.9049746e-05 |
| 5,731 |
Babelfish: Efficient Execution of Polyglot Queries |
2022 |
VLDB |
5.3502065e-05 |
| 6,189 |
Accelerating Python UDFs in Vectorized Query Execution |
2022 |
CIDR |
5.1647573e-05 |
Semantically Similar Papers
| Overall Rank |
Paper |
Year |
Venue |
Pagerank |
| 9,343 |
The Key to Effective UDF Optimization: Before Inlining, First Perform Outlining |
2025 |
VLDB |
4.3546206e-05 |
| 1,873 |
An Architecture for Compiling UDF-centric Workflows |
2015 |
VLDB |
0.00010253002 |
| 6,701 |
YeSQL: “You extend SQL” with Rich and Highly Performant User-Defined Functions in Relational Databases |
2022 |
VLDB |
4.9561066e-05 |
| 12,316 |
Fast and Dynamic OLAP Exploration Using UDFs |
2009 |
SIGMOD |
4.1945683e-05 |
| 6,645 |
Functional-Style SQL UDFs With a Capital 'F' |
2020 |
SIGMOD |
4.978205e-05 |
| 6,375 |
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 |
5.0923872e-05 |
| 6,189 |
Accelerating Python UDFs in Vectorized Query Execution |
2022 |
CIDR |
5.1647573e-05 |
| 10,459 |
UDFBench: A Tool for Benchmarking UDF Queries on SQL Engines |
2025 |
SIGMOD |
4.1945683e-05 |
| 8,583 |
Efficient Execution of User-Defined Functions in SQL Queries |
2023 |
VLDB |
4.4919445e-05 |
| 9,763 |
The UDFBench Benchmark for General-purpose UDF Queries |
2025 |
VLDB |
4.2856106e-05 |