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arXiv · 2505.20683

In-memory Incremental Maintenance of Provenance Sketches [extended version]

Pengyuan Li·Boris Glavic·Dieter Gawlick·Vasudha Krishnaswamy·Zhen Hua Liu·Danica Porobic·Xing Niu
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Abstract

Provenance-based data skipping compactly over-approximates the provenance of a query using so-called provenance sketches and utilizes such sketches to speed-up the execution of subsequent queries by skipping irrelevant data. However, a sketch captured at some time in the past may become stale if the data has been updated subsequently. Thus, there is a need to maintain provenance sketches. In this work, we introduce In-Memory incremental Maintenance of Provenance sketches (IMP), a framework for maintaining sketches incrementally under updates. At the core of IMP is an incremental query engine for data annotated with sketches that exploits the coarse-grained nature of sketches to enable novel optimizations. We experimentally demonstrate that IMP significantly reduces the cost of sketch maintenance, thereby enabling the use of provenance sketches for a broad range of workloads that involve updates.

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Pengyuan Li, Boris Glavic, Dieter Gawlick, Vasudha Krishnaswamy, Zhen Hua Liu, Danica Porobic, Xing Niu. 2025-05-27. In-memory Incremental Maintenance of Provenance Sketches [extended version]. https://arxiv.org/abs/2505.20683

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