Accelerating User-Defined Aggregate Functions (UDAF) with Block-wide Execution and JIT Compilation on GPUs

Yogatama, Bobbi; Miller, Brandon; Wang, Yunsong; Markall, Graham; Hemstad, Jacob; Kimball, Gregory; Yu, Xiangyao

doi:10.1145/3592980.3595307

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2024

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Cited by 2 publications

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Sharing Queries with Nonequivalent User-defined Aggregate Functions

Zhang,

Farouk

2024

ACM Trans. Database Syst.

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This paper presents SUDAF , a declarative framework that allows users to write UDAF (User-Defined Aggregate Function) as mathematical expressions and use them in SQL statements. SUDAF rewrites partial aggregates of UDAFs using built-in aggregate functions and supports efficient dynamic caching and reusing of partial aggregates. Our experiments show that rewriting UDAFs using built-in functions can significantly speed up queries with UDAFs, and the proposed sharing approach can yield up to two orders of magnitude improvement in query execution time. The paper studies also an extension of SUDAF to support sharing partial results between arbitrary queries with UDAFs. We show a connection with the problem of query rewriting using views and introduce a new class of rewritings, called SUDAF rewritings, which enables to use views that have aggregate functions different from the ones used in the input query. We investigate the underlying rewriting-checking and rewriting-existing problem. Our main technical result is a reduction of these problems to respectively rewriting-checking and rewriting-existing of the so-called aggregate candidates , a class of rewritings that has been deeply investigated in the literature.

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