An Architecture for Compiling UDF-centric Workflows
Summary: An architecture to automatically compile UDF-centric workflows for complex analytics, targeting computation bottlenecks. Data/UDF/hardware-aware optimizations produce per-workflow code in TUPLEWARE, achieving up to three orders of magnitude speedups against alternatives. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Andrew Crotty
- 2. Alex Galakatos
- 3. Kayhan Dursun
- 4. Tim Kraska
- 5. Carsten Binnig
- 6. Ugur Cetintemel
- 7. Stan Zdonik
Incoming Citations (Sorted by Pagerank)
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Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,383 | How to Architect a Query Compiler | 2016 | SIGMOD | 8.9198524e-05 |
| 11,290 | To UDFs and Beyond: Demonstration of a Fully Decomposed Data Processor for General Data Wrangling Tasks | 2023 | VLDB | 4.1905499e-05 |
| 1,884 | Tuplex: Data Science in Python at Native Code Speed | 2021 | SIGMOD | 0.00010206514 |
| 6,863 | Declarative Sub-Operators for Universal Data Processing | 2023 | VLDB | 4.9003859e-05 |
| 10,469 | UDFBench: A Tool for Benchmarking UDF Queries on SQL Engines | 2025 | SIGMOD | 4.1905499e-05 |
| 6,646 | Functional-Style SQL UDFs With a Capital 'F' | 2020 | SIGMOD | 4.9734285e-05 |
| 9,765 | The UDFBench Benchmark for General-purpose UDF Queries | 2025 | VLDB | 4.2815042e-05 |
| 6,191 | Accelerating Python UDFs in Vectorized Query Execution | 2022 | CIDR | 5.1598046e-05 |
| 2,421 | Tupleware: "Big" Data, Big Analytics, Small Clusters | 2015 | CIDR | 8.8471956e-05 |
| 8,580 | Efficient Execution of User-Defined Functions in SQL Queries | 2023 | VLDB | 4.4876382e-05 |