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arXiv · 2508.15109

Homomorphism Calculus for User-Defined Aggregations

Ziteng Wang·Ruijie Fang·Linus Zheng·Dixin Tang·Isil Dillig
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Abstract

Data processing frameworks like Apache Spark and Flink provide built-in support for user-defined aggregation functions (UDAFs), enabling the integration of domain-specific logic. However, for these frameworks to support \emph{efficient} UDAF execution, the function needs to satisfy a \emph{homomorphism property}, which ensures that partial results from independent computations can be merged correctly. Motivated by this problem, this paper introduces a novel \emph{homomorphism calculus} that can both verify and refute whether a UDAF is a dataframe homomorphism. If so, our calculus also enables the construction of a corresponding merge operator which can be used for incremental computation and parallel execution. We have implemented an algorithm based on our proposed calculus and evaluate it on real-world UDAFs, demonstrating that our approach significantly outperforms two leading synthesizers.

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Ziteng Wang, Ruijie Fang, Linus Zheng, Dixin Tang, Isil Dillig. 2025-08-20. Homomorphism Calculus for User-Defined Aggregations. https://doi.org/10.1145/3763072

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