Window Function Optimization: Co-Evaluation and Other Techniques

August 06, 2026 ยท Grace Period ยท ๐Ÿ› PVLDB, 19(11): 3525-3537, 2026

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Authors Daniel Lindner, Felix Naumann, Alberto Lerner arXiv ID 2608.06043 Category cs.DB: Databases Citations 0 Venue PVLDB, 19(11): 3525-3537, 2026
Abstract
Window functions are among the most expressive features of modern SQL. Surprisingly, relatively little has been written about their optimization. Some techniques exist, such as pushing predicates through a window under ideal conditions, but known optimizations no longer apply when those conditions are even slightly unmet. We show that these limitations are not fundamental, but persist because a reasoning framework for window function optimization has been missing. We provide such a framework, introducing techniques we call Frame Analysis, Partition Analysis, and a new execution strategy called Co-Evaluation. These clarify when and how optimizations can be applied. Co-Evaluation, in particular, allows early evaluation of predicates even when they depend on the window function's result. We present each technique and organize the results as a table of algebraic equivalences for window functions. We test these optimizations in an open-source engine, where they never hurt performance and make certain common queries up to 40.7 times faster, with larger tables yielding larger gains.
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