2025/07/14 by Mihail Stoian, Johannes Thürauf, Stoian, Mihail +7
Computer Science · Social Sciences · #Biometric Identification and Security #Databases (cs.DB) #FOS: Computer and information sciences #Forensic Fingerprint Detection Methods #Handwritten Text Recognition Techniques
paper · pdf · doi:10.48550/arxiv.2507.10391
openalex publication_date 2025/07/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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×.