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arXiv · 2507.10391

Instance-Optimized String Fingerprints

Mihail Stoian·Johannes Thürauf·Andreas Zimmerer·Alexander van Renen·Andreas Kipf
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Abstract

Recent research found that cloud data warehouses are text-heavy. However, their capabilities for efficiently processing string columns remain limited, relying primarily on techniques like dictionary encoding and prefix-based partition pruning. In recent work, we introduced string fingerprints - a lightweight secondary index structure designed to approximate LIKE predicates, albeit with false positives. This approach is particularly compelling for columnar query engines, where fingerprints can help reduce both compute and I/O overhead. We show that string fingerprints can be optimized for specific workloads using mixed-integer optimization, and that they can generalize to unseen table predicates. On an IMDb column evaluated in DuckDB v1.3, this yields table-scan speedups of up to 1.36$\times$.

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Mihail Stoian, Johannes Thürauf, Andreas Zimmerer, Alexander van Renen, Andreas Kipf. 2025-07-14. Instance-Optimized String Fingerprints. https://arxiv.org/abs/2507.10391

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