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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
- 12798
- Venue
- VLDB
- Year
- 2022
- Pagerank
- 5.481452e-05
- Overall Rank
- 5,486 | 61.88%
- 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 |
| 739 |
Delta Lake: High-Performance ACID Table Storage over Cloud Object Stores |
2020 |
VLDB |
0.00017365933 |
| 1,107 |
Froid: Optimization of Imperative Programs in a Relational Database |
2018 |
VLDB |
0.0001397627 |
| 1,634 |
Cloudburst: Stateful Functions-as-a-Service |
2020 |
VLDB |
0.00011061792 |
| 1,875 |
An Architecture for Compiling UDF-centric Workflows |
2015 |
VLDB |
0.00010243959 |
| 1,884 |
Tuplex: Data Science in Python at Native Code Speed |
2021 |
SIGMOD |
0.00010206514 |
| 2,366 |
Data Market Platforms: Trading Data Assets to Solve Data Problems |
2020 |
VLDB |
8.9521259e-05 |
| 2,616 |
Opening the Black Boxes in Data Flow Optimization |
2012 |
VLDB |
8.4457819e-05 |
| 2,809 |
Extending Relational Query Processing with ML Inference |
2020 |
CIDR |
8.0869552e-05 |
| 3,409 |
End-to-end Optimization of Machine Learning Prediction Queries |
2022 |
SIGMOD |
7.1240791e-05 |
| 4,813 |
Putting Pandas in a Box |
2021 |
CIDR |
5.8993009e-05 |
| 5,741 |
Babelfish: Efficient Execution of Polyglot Queries |
2022 |
VLDB |
5.3450701e-05 |
| 6,191 |
Accelerating Python UDFs in Vectorized Query Execution |
2022 |
CIDR |
5.1598046e-05 |
Semantically Similar Papers
| Overall Rank |
Paper |
Year |
Venue |
Pagerank |
| 9,348 |
The Key to Effective UDF Optimization: Before Inlining, First Perform Outlining |
2025 |
VLDB |
4.3504473e-05 |
| 6,703 |
YeSQL: “You extend SQL” with Rich and Highly Performant User-Defined Functions in Relational Databases |
2022 |
VLDB |
4.9514593e-05 |
| 1,875 |
An Architecture for Compiling UDF-centric Workflows |
2015 |
VLDB |
0.00010243959 |
| 12,324 |
Fast and Dynamic OLAP Exploration Using UDFs |
2009 |
SIGMOD |
4.1905499e-05 |
| 6,646 |
Functional-Style SQL UDFs With a Capital 'F' |
2020 |
SIGMOD |
4.9734285e-05 |
| 6,374 |
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 |
5.0874998e-05 |
| 6,191 |
Accelerating Python UDFs in Vectorized Query Execution |
2022 |
CIDR |
5.1598046e-05 |
| 10,469 |
UDFBench: A Tool for Benchmarking UDF Queries on SQL Engines |
2025 |
SIGMOD |
4.1905499e-05 |
| 8,580 |
Efficient Execution of User-Defined Functions in SQL Queries |
2023 |
VLDB |
4.4876382e-05 |
| 9,765 |
The UDFBench Benchmark for General-purpose UDF Queries |
2025 |
VLDB |
4.2815042e-05 |