User-defined functions (UDFs) extend the expressiveness of declarative SQL with functional capabilities, but also pose a core bottleneck in query processing due to the impedance mismatch between the UDF and SQL execution environments, and the limitations of the query optimizers to consistently produce good plans for UDF queries. Research and commercial approaches propose remedies for performant UDF query execution ranging from logical optimization and heuristics to physical optimization and compilation techniques. Each work however follows a different path to evaluate their proposed techniques. Despite the practical significance of optimizing UDF queries, UDFs have not been so far the focus of the database benchmarks. In this paper, we present UDFBench, a UDF-centric database benchmark based on real-world schema and data. We identify the core overheads in UDF query execution and design the UDFBench UDFs and queries to enable experimentation with these overheads, alone or in tandem with others. Finally, to showcase the portability and scope of UDFBench, we present an experimental analysis on five popular databases with different characteristics.

Modern data applications in areas such as text mining, document analysis, and data science, involve complex algorithms and logic that cannot be expressed in SQL. Therefore, SQL databases employ user-defined functions (UDFs) to extend their supported functionality. However, this comes at a significant performance cost as UDFs routinely become the bottleneck in query execution. To deal with this problem, we present QFusor, an optimizer plugin for UDF queries in relational databases. QFusor minimizes the performance overheads introduced by the impedance mismatch between the UDF and SQL execution environments by employing techniques such as vectorization, parallelization, tracing JIT compilation, and operator fusion for various types of UDF (scalar, aggregate, table UDFs) and relational operators. QFusor follows a pluggable, engine-agnostic design and can work with several popular SQL databases offering a significant boost in their UDF query performance.