BIRNE: Mixed-paradigm Workload Execution in SQL Engines

Previous work on UDF compilation strategies has proven that SQL engines can be used as efficient execution environments for imperative workloads over relational data. In this paper, we present BIRNE, a major extension of our Flummi compiler, with support for mixed-paradigm workloads, such that database-resident programs can be expressed using both imperative and functional constructs. To this end, we introduce a specialized form of control flow graphs that we call control flow plans, that allow us to express the control flow and data dependencies, such that we can use plain SQL as the target for compilation. We show that this approach allows us to compile a wide range of workloads into a single SQL query, and that it can outperform existing approaches in terms of overall runtime in many cases.

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Published
2025-06-22
DOI
https://doi.org/10.1145/3735106.3736535
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
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article

BIRNE: Mixed-paradigm Workload Execution in SQL Engines

Tim Fischer, Denis Hirn
Parallel Computing and Optimization Techniques
article

BIRNE: Mixed-paradigm Workload Execution in SQL Engines

Tim Fischer, Denis Hirn
article en

Abstract

Previous work on UDF compilation strategies has proven that SQL engines can be used as efficient execution environments for imperative workloads over relational data. In this paper, we present BIRNE, a major extension of our Flummi compiler, with support for mixed-paradigm workloads, such that database-resident programs can be expressed using both imperative and functional constructs. To this end, we introduce a specialized form of control flow graphs that we call control flow plans, that allow us to express the control flow and data dependencies, such that we can use plain SQL as the target for compilation. We show that this approach allows us to compile a wide range of workloads into a single SQL query, and that it can outperform existing approaches in terms of overall runtime in many cases.

University of Tübingen (DE)
Openalex Percentile: Top 86%
Parallel Computing and Optimization Techniques
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