cs.DB · 2026-08-29 · No. 99

Databases, 2026-08-29.

2 new papers in cs.DB. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

2 entries
  1. 01

    Compositional Online Learning for Semantic Data Processing Systems

    Paweł Liskowski, Fuheng Zhao, Benjamin Han, Anupam Datta, Dimitris Tsirogiannis

    cs.DB · cs.AI

    An LLM call in a semantic data processing system is expensive enough to dominate query cost, yet slow enough to hide a CPU-side learner's update behind its round-trip. In production, LLM compute accounts for $80-90\%$ of query cost, and each call costs $10^5-10^7\times$ a relational predicate. The latency window inverts a design constraint of classical adaptive query processing, where online learners had to stay lightweight to avoid...

    arxiv.org/abs/2608.27244 · PDF

  2. 02

    IBLTs Measure Before They Decode: Self-Sizing Set Reconciliation from Pre-Peeling Counts

    Min Wu, Ji Qi, Chengdui Luo, Shudong Lu, Zhengsheng Ye, Zhengyang Wei

    cs.DB · cs.DC

    Set reconciliation recovers the symmetric difference $A\triangle B$ with communication far below the data volume. Invertible Bloom Lookup Tables (IBLTs) are a standard tool, but their capacity must match the unknown difference cardinality~$d$. In database deployments, $d$ spans orders of magnitude, so undersizing causes rescans or replays while oversizing wastes network and memory. We show that an IBLT measures $d$ before decoding. Each cell...

    arxiv.org/abs/2608.26537 · PDF

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